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Lefevre TJ, Wei W, Mukhaleva E, Meda Venkata SP, Chandan NR, Abraham S, Li Y, Dessauer CW, Vaidehi N, Smrcka AV. Stabilization of interdomain interactions in G protein α subunits as a determinant of Gα i subtype signaling specificity. J Biol Chem 2024; 300:107211. [PMID: 38522511 DOI: 10.1016/j.jbc.2024.107211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 03/07/2024] [Accepted: 03/12/2024] [Indexed: 03/26/2024] Open
Abstract
Highly homologous members of the Gαi family, Gαi1-3, have distinct tissue distributions and physiological functions, yet their biochemical and functional properties are very similar. We recently identified PDZ-RhoGEF (PRG) as a novel Gαi1 effector that is poorly activated by Gαi2. In a proteomic proximity labeling screen we observed a strong preference for Gαi1 relative to Gαi2 with respect to engagement of a broad range of potential targets. We investigated the mechanistic basis for this selectivity using PRG as a representative target. Substitution of either the helical domain (HD) from Gαi1 into Gαi2 or substitution of a single amino acid, A230 in Gαi2 with the corresponding D in Gαi1, largely rescues PRG activation and interactions with other potential Gαi targets. Molecular dynamics simulations combined with Bayesian network models revealed that in the GTP bound state, separation at the HD-Ras-like domain (RLD) interface is more pronounced in Gαi2 than Gαi1. Mutation of A230 to D in Gαi2 stabilizes HD-RLD interactions via ionic interactions with R145 in the HD which in turn modify the conformation of Switch III. These data support a model where D229 in Gαi1 interacts with R144 and stabilizes a network of interactions between HD and RLD to promote protein target recognition. The corresponding A230 in Gαi2 is unable to stabilize this network leading to an overall lower efficacy with respect to target interactions. This study reveals distinct mechanistic properties that could underly differential biological and physiological consequences of activation of Gαi1 or Gαi2 by G protein-coupled receptors.
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Affiliation(s)
- Tyler J Lefevre
- Department of Pharmacology, University of Michigan Medical School, Ann Arbor, Michigan, USA; Program in Chemical Biology, University of Michigan, Ann Arbor, Michigan, USA
| | - Wenyuan Wei
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA
| | - Elizaveta Mukhaleva
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA
| | | | - Naincy R Chandan
- Department of Pharmacology, University of Michigan Medical School, Ann Arbor, Michigan, USA; Genentech, South San Francisco, California, USA
| | - Saji Abraham
- Department of Pharmacology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Yong Li
- Department of Integrative Biology and Pharmacology McGovern Medical School, UTHealth, Houston, Texas, USA
| | - Carmen W Dessauer
- Department of Integrative Biology and Pharmacology McGovern Medical School, UTHealth, Houston, Texas, USA
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA
| | - Alan V Smrcka
- Department of Pharmacology, University of Michigan Medical School, Ann Arbor, Michigan, USA.
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2
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Hall J, Zhang Z, Bhattacharya S, Wang D, Alcantara M, Liang Y, Swiderski P, Forman S, Kwak L, Vaidehi N, Kortylewski M. Oligo-PROTAC strategy for cell-selective and targeted degradation of activated STAT3. Mol Ther Nucleic Acids 2024; 35:102137. [PMID: 38384444 PMCID: PMC10879796 DOI: 10.1016/j.omtn.2024.102137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 01/31/2024] [Indexed: 02/23/2024]
Abstract
Decoy oligodeoxynucleotides (ODNs) allow targeting undruggable transcription factors, such as STAT3, but their limited potency and lack of delivery methods hampered translation. To overcome these challenges, we conjugated a STAT3-specific decoy to thalidomide, a ligand to cereblon in E3 ubiquitin ligase complex, to generate a proteolysis-targeting chimera (STAT3DPROTAC). STAT3DPROTAC downregulated STAT3 in target cells, but not STAT1 or STAT5. Computational modeling of the STAT3DPROTAC ternary complex predicted two surface lysines, K601 and K626, in STAT3 as potential ubiquitination sites. Accordingly, K601/K626 point mutations in STAT3, as well as proteasome inhibition or cereblon deletion, alleviated STAT3DPROTAC effect. Next, we conjugated STAT3DPROTAC to a CpG oligonucleotide targeting Toll-like receptor 9 (TLR9) to generate myeloid/B cell-selective C-STAT3DPROTAC. Naked C-STAT3DPROTAC was spontaneously internalized by TLR9+ myeloid cells, B cells, and human and mouse lymphoma cells but not by T cells. C-STAT3DPROTAC effectively decreased STAT3 protein levels and also STAT3-regulated target genes critical for lymphoma cell proliferation and/or survival (BCL2L1, CCND2, and MYC). Finally, local C-STAT3DPROTAC administration to human Ly3 lymphoma-bearing mice triggered tumor regression, while control C-STAT3D and C-SCR treatments had limited effects. Our results underscore the feasibility of using a PROTAC strategy for cell-selective, decoy oligonucleotide-based STAT3 targeting of and potentially other tumorigenic transcription factors for cancer therapy.
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Affiliation(s)
- Jeremy Hall
- Department of Immuno-Oncology, Beckman Research Institute, City of Hope, Duarte, CA 91010, USA
| | - Zhuoran Zhang
- Department of Immuno-Oncology, Beckman Research Institute, City of Hope, Duarte, CA 91010, USA
| | - Supriyo Bhattacharya
- Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, Duarte, CA 91010, USA
| | - Dongfang Wang
- Department of Immuno-Oncology, Beckman Research Institute, City of Hope, Duarte, CA 91010, USA
| | - Marice Alcantara
- Department of Immuno-Oncology, Beckman Research Institute, City of Hope, Duarte, CA 91010, USA
| | - Yong Liang
- DNA/RNA Synthesis Core Facility, Beckman Research Institute, City of Hope, Duarte, CA 91010, USA
| | - Piotr Swiderski
- DNA/RNA Synthesis Core Facility, Beckman Research Institute, City of Hope, Duarte, CA 91010, USA
| | - Stephen Forman
- Department of Hematology & Hematopoietic Cell Transplantation, Beckman Research Institute, City of Hope, Duarte, CA 91010, USA
| | - Larry Kwak
- Department of Hematology & Hematopoietic Cell Transplantation, Beckman Research Institute, City of Hope, Duarte, CA 91010, USA
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, Duarte, CA 91010, USA
| | - Marcin Kortylewski
- Department of Immuno-Oncology, Beckman Research Institute, City of Hope, Duarte, CA 91010, USA
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3
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Mattson NM, Chan AKN, Miyashita K, Mukhaleva E, Chang WH, Yang L, Ma N, Wang Y, Pokharel SP, Li M, Liu Q, Xu X, Chen R, Singh P, Zhang L, Elsayed Z, Chen B, Keen D, Pirrotte P, Rosen ST, Chen J, LaBarge MA, Shively JE, Vaidehi N, Rockne RC, Feng M, Chen CW. A novel class of inhibitors that disrupts the stability of integrin heterodimers identified by CRISPR-tiling-instructed genetic screens. Nat Struct Mol Biol 2024; 31:465-475. [PMID: 38316881 PMCID: PMC10948361 DOI: 10.1038/s41594-024-01211-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 01/02/2024] [Indexed: 02/07/2024]
Abstract
The plasma membrane is enriched for receptors and signaling proteins that are accessible from the extracellular space for pharmacological intervention. Here we conducted a series of CRISPR screens using human cell surface proteome and integrin family libraries in multiple cancer models. Our results identified ITGAV (integrin αV) and its heterodimer partner ITGB5 (integrin β5) as the essential integrin α/β pair for cancer cell expansion. High-density CRISPR gene tiling further pinpointed the integral pocket within the β-propeller domain of ITGAV for integrin αVβ5 dimerization. Combined with in silico compound docking, we developed a CRISPR-Tiling-Instructed Computer-Aided (CRISPR-TICA) pipeline for drug discovery and identified Cpd_AV2 as a lead inhibitor targeting the β-propeller central pocket of ITGAV. Cpd_AV2 treatment led to rapid uncoupling of integrin αVβ5 and cellular apoptosis, providing a unique class of therapeutic action that eliminates the integrin signaling via heterodimer dissociation. We also foresee the CRISPR-TICA approach to be an accessible method for future drug discovery studies.
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Affiliation(s)
- Nicole M Mattson
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Anthony K N Chan
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
- Division of Epigenetic and Transcriptional Engineering, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Kazuya Miyashita
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Elizaveta Mukhaleva
- Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Wen-Han Chang
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Lu Yang
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
- Division of Epigenetic and Transcriptional Engineering, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Ning Ma
- Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Yingyu Wang
- Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Sheela Pangeni Pokharel
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
- Division of Epigenetic and Transcriptional Engineering, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Mingli Li
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Qiao Liu
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Xiaobao Xu
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Renee Chen
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Priyanka Singh
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Leisi Zhang
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Zeinab Elsayed
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Bryan Chen
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Denise Keen
- City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Patrick Pirrotte
- Integrated Mass Spectrometry Shared Resource, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
- Cancer and Cell Biology Division, Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Steven T Rosen
- City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Jianjun Chen
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
- City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Mark A LaBarge
- City of Hope Comprehensive Cancer Center, Duarte, CA, USA
- Department of Population Sciences, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - John E Shively
- City of Hope Comprehensive Cancer Center, Duarte, CA, USA
- Department of Immunology and Theranostics, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, Duarte, CA, USA
- City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Russell C Rockne
- Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, Duarte, CA, USA
- City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Mingye Feng
- City of Hope Comprehensive Cancer Center, Duarte, CA, USA
- Department of Immuno-Oncology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Chun-Wei Chen
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA.
- Division of Epigenetic and Transcriptional Engineering, Beckman Research Institute, City of Hope, Duarte, CA, USA.
- City of Hope Comprehensive Cancer Center, Duarte, CA, USA.
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4
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Chan AK, Han L, Delaney CD, Wang X, Mukhaleva E, Li M, Yang L, Pokharel SP, Mattson N, Garcia M, Wang B, Xu X, Zhang L, Singh P, Elsayed Z, Chen R, Kuang B, Wang J, Yuan YC, Chen B, Chan LN, Rosen ST, Horne D, Müschen M, Chen J, Vaidehi N, Armstrong SA, Su R, Chen CW. Therapeutic targeting Tudor domains in leukemia via CRISPR-Scan Assisted Drug Discovery. Sci Adv 2024; 10:eadk3127. [PMID: 38394203 PMCID: PMC10889360 DOI: 10.1126/sciadv.adk3127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 01/22/2024] [Indexed: 02/25/2024]
Abstract
Epigenetic dysregulation has been reported in multiple cancers including leukemias. Nonetheless, the roles of the epigenetic reader Tudor domains in leukemia progression and therapy remain unexplored. Here, we conducted a Tudor domain-focused CRISPR screen and identified SGF29, a component of SAGA/ATAC acetyltransferase complexes, as a crucial factor for H3K9 acetylation, ribosomal gene expression, and leukemogenesis. To facilitate drug development, we integrated the CRISPR tiling scan with compound docking and molecular dynamics simulation, presenting a generally applicable strategy called CRISPR-Scan Assisted Drug Discovery (CRISPR-SADD). Using this approach, we identified a lead inhibitor that selectively targets SGF29's Tudor domain and demonstrates efficacy against leukemia. Furthermore, we propose that the structural genetics approach used in our study can be widely applied to diverse fields for de novo drug discovery.
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Affiliation(s)
- Anthony K.N. Chan
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
- Division of Epigenetic and Transcriptional Engineering, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Li Han
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
- School of Pharmacy, China Medical University, Shenyang, Liaoning, China
| | - Christopher D. Delaney
- Duke University School of Medicine, Durham, NC, USA
- Department of Pediatrics, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Xueer Wang
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Elizaveta Mukhaleva
- Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Mingli Li
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Lu Yang
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
- Division of Epigenetic and Transcriptional Engineering, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Sheela Pangeni Pokharel
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
- Division of Epigenetic and Transcriptional Engineering, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Nicole Mattson
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Michelle Garcia
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
- Department of Chemistry, Dartmouth College, Hanover, NH, USA
| | - Bintao Wang
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Xiaobao Xu
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Leisi Zhang
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Priyanka Singh
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Zeinab Elsayed
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Renee Chen
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Benjamin Kuang
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Jinhui Wang
- City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Yate-Ching Yuan
- Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Bryan Chen
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Lai N. Chan
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
- Department of Cancer Biology, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | | | - David Horne
- City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Markus Müschen
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Jianjun Chen
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
- City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, Duarte, CA, USA
- City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Scott A. Armstrong
- Department of Pediatrics, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Rui Su
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
- City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Chun-Wei Chen
- Department of Systems Biology, Beckman Research Institute, City of Hope, Duarte, CA, USA
- Division of Epigenetic and Transcriptional Engineering, Beckman Research Institute, City of Hope, Duarte, CA, USA
- City of Hope Comprehensive Cancer Center, Duarte, CA, USA
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5
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Knight KM, Obarow EG, Wei W, Mani S, Esteller MI, Cui M, Ma N, Martin SA, Brinson E, Hewitt N, Soden GM, Logothetis DE, Vaidehi N, Dohlman HG. Molecular annotation of G protein variants in a neurological disorder. Cell Rep 2023; 42:113462. [PMID: 37980565 PMCID: PMC10872635 DOI: 10.1016/j.celrep.2023.113462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 10/04/2023] [Accepted: 11/02/2023] [Indexed: 11/21/2023] Open
Abstract
Heterotrimeric G proteins transduce extracellular chemical messages to generate appropriate intracellular responses. Point mutations in GNAO1, encoding the G protein αo subunit, have been implicated in a pathogenic condition characterized by seizures, movement disorders, intellectual disability, and developmental delay (GNAO1 disorder). However, the effects of these mutations on G protein structure and function are unclear. Here, we report the effects of 55 mutations on Gαo conformation, thermostability, nucleotide binding, and hydrolysis, as well as interaction with Gβγ subunits, receptors, and effectors. Our effort reveals four functionally distinct groups of mutants, including one group that sequesters receptors and another that sequesters Gβγ, both acting in a genetically dominant manner. These findings provide a more comprehensive understanding of disease-relevant mutations and reveal that GNAO1 disorder is likely composed of multiple mechanistically distinct disorders that will likely require multiple therapeutic strategies.
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Affiliation(s)
- Kevin M Knight
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Elizabeth G Obarow
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Wenyuan Wei
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010, USA
| | - Sepehr Mani
- Department of Pharmaceutical Sciences, Northeastern University, Boston, MA 02115, USA
| | - Maria I Esteller
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Meng Cui
- Department of Pharmaceutical Sciences, Northeastern University, Boston, MA 02115, USA
| | - Ning Ma
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010, USA
| | - Sarah A Martin
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Emily Brinson
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Natalie Hewitt
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Gaby M Soden
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Diomedes E Logothetis
- Department of Pharmaceutical Sciences, Northeastern University, Boston, MA 02115, USA.
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010, USA.
| | - Henrik G Dohlman
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
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6
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Knight KM, Obarow EG, Wei W, Mani S, Esteller MI, Cui M, Ma N, Martin SA, Brinson E, Hewitt N, Soden GM, Logothetis DE, Vaidehi N, Dohlman HG. Molecular annotation of G protein variants in a neurological disorder. Cell Rep 2023; 42:113578. [PMID: 38043061 PMCID: PMC10882632 DOI: 10.1016/j.celrep.2023.113578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2023] Open
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7
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Mukhaleva E, Yang T, Sadler F, Sivaramakrishnan S, Ma N, Vaidehi N. Cellular Lipids Regulate the Conformational Ensembles of the Disordered Intracellular Loop 3 in β2 Adrenergic Receptor. bioRxiv 2023:2023.11.28.569080. [PMID: 38077083 PMCID: PMC10705491 DOI: 10.1101/2023.11.28.569080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
The structurally disordered intracellular loops (ICLs) of G protein-coupled receptors (GPCRs) play a critical role in G protein coupling. In our previous work, we used a combination of FRET-based and computational methodologies to show that the third intracellular loop (ICL3) modulates the activity and G protein coupling selectivity in GPCRs. In the current study, we have uncovered the role of several lipid components in modulating the conformational ensemble of ICL3 of the β2-adrenergic receptor (β2AR). Our findings indicate that phosphatidylinositol 4,5-bisphosphate (PIP2) in the inner leaflet of the membrane bilayer acts as a stabilizing anchor for ICL3, opening the intracellular cavity to facilitate G protein coupling. This interaction between PIP2 and ICL3 causes tilting of β2AR within the cellular membrane. Notably, this tilting of the receptor is supported by ganglioside GM3 stabilizing the extracellular loops on the outer leaflet of the bilayer, thereby exerting an allosteric effect on the orthosteric ligand binding pocket. Our results underscore the significance of lipids in modulating GPCR activity, proposing an allosteric mechanism that occurs through the receptor's orientation within the membrane.
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Affiliation(s)
- Elizaveta Mukhaleva
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, CA, USA
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - Tianyi Yang
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - Fredrik Sadler
- Biochemistry, Molecular Biology and Biophysics Graduate Program, University of Minnesota, Minneapolis, MN, USA
- Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN, USA
| | - Sivaraj Sivaramakrishnan
- Biochemistry, Molecular Biology and Biophysics Graduate Program, University of Minnesota, Minneapolis, MN, USA
- Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN, USA
| | - Ning Ma
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - Nagarajan Vaidehi
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, CA, USA
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA, USA
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8
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de March CA, Ma N, Billesbølle CB, Tewari J, del Torrent CL, van der Velden WJC, Ojiro I, Takayama I, Faust B, Li L, Vaidehi N, Manglik A, Matsunami H. Engineered odorant receptors illuminate structural principles of odor discrimination. bioRxiv 2023:2023.11.16.567230. [PMID: 38014344 PMCID: PMC10680712 DOI: 10.1101/2023.11.16.567230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
A central challenge in olfaction is understanding how the olfactory system detects and distinguishes odorants with diverse physicochemical properties and molecular configurations. Vertebrate animals perceive odors via G protein-coupled odorant receptors (ORs). In humans, ~400 ORs enable the sense of smell. The OR family is composed of two major classes: Class I ORs are tuned to carboxylic acids while Class II ORs, representing the vast majority of the human repertoire, respond to a wide variety of odorants. How ORs recognize chemically diverse odorants remains poorly understood. A fundamental bottleneck is the inability to visualize odorant binding to ORs. Here, we uncover fundamental molecular properties of odorant-OR interactions by employing engineered ORs crafted using a consensus protein design strategy. Because such consensus ORs (consORs) are derived from the 17 major subfamilies of human ORs, they provide a template for modeling individual native ORs with high sequence and structural homology. The biochemical tractability of consORs enabled four cryoEM structures of distinct consORs with unique ligand recognition properties. The structure of a Class I consOR, consOR51, showed high structural similarity to the native human receptor OR51E2 and yielded a homology model of a related member of the human OR51 family with high predictive power. Structures of three Class II consORs revealed distinct modes of odorant-binding and activation mechanisms between Class I and Class II ORs. Thus, the structures of consORs lay the groundwork for understanding molecular recognition of odorants by the OR superfamily.
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Affiliation(s)
- Claire A. de March
- Department of Molecular Genetics and Microbiology, Duke University, Durham, NC, USA
- Institut de Chimie des Substances Naturelles, UPR2301 CNRS, Université Paris-Saclay, Gifsur- Yvette, 91190, France
| | - Ning Ma
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | | | - Jeevan Tewari
- Department of Molecular Genetics and Microbiology, Duke University, Durham, NC, USA
| | - Claudia Llinas del Torrent
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA, USA
- Laboratory of Computational Medicine, Biostatistics Unit, Faculty of Medicine, Universitat Autònoma Barcelona, 08193 Bellaterra, Barcelona, Spain; Department of Anesthesia and Perioperative Care, University of California, San Francisco, CA, USA
| | - Wijnand J. C. van der Velden
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - Ichie Ojiro
- Department of Molecular Genetics and Microbiology, Duke University, Durham, NC, USA
| | - Ikumi Takayama
- Department of Molecular Genetics and Microbiology, Duke University, Durham, NC, USA
- Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, Koganei, Tokyo 184-8588, Japan
| | - Bryan Faust
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA, USA
| | - Linus Li
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA, USA
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - Aashish Manglik
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA, USA
- Laboratory of Computational Medicine, Biostatistics Unit, Faculty of Medicine, Universitat Autònoma Barcelona, 08193 Bellaterra, Barcelona, Spain; Department of Anesthesia and Perioperative Care, University of California, San Francisco, CA, USA
| | - Hiroaki Matsunami
- Department of Molecular Genetics and Microbiology, Duke University, Durham, NC, USA
- Department of Neurobiology, Duke Institute for Brain Sciences, Duke University, Durham, NC, USA
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9
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Mukhaleva E, Ma N, van der Velden WJC, Gogoshin G, Branciamore S, Bhattacharya S, Rodin AS, Vaidehi N. Bayesian network models identify co-operative GPCR:G protein interactions that contribute to G protein coupling. bioRxiv 2023:2023.10.09.561618. [PMID: 37873104 PMCID: PMC10592737 DOI: 10.1101/2023.10.09.561618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Cooperative interactions in protein-protein interfaces demonstrate the interdependency or the linked network-like behavior of interface interactions and their effect on the coupling of proteins. Cooperative interactions also could cause ripple or allosteric effects at a distance in protein-protein interfaces. Although they are critically important in protein-protein interfaces it is challenging to determine which amino acid pair interactions are cooperative. In this work we have used Bayesian network modeling, an interpretable machine learning method, combined with molecular dynamics trajectories to identify the residue pairs that show high cooperativity and their allosteric effect in the interface of G protein-coupled receptor (GPCR) complexes with G proteins. Our results reveal a strong co-dependency in the formation of interface GPCR:G protein contacts. This observation indicates that cooperativity of GPCR:G protein interactions is necessary for the coupling and selectivity of G proteins and is thus critical for receptor function. We have identified subnetworks containing polar and hydrophobic interactions that are common among multiple GPCRs coupling to different G protein subtypes (Gs, Gi and Gq). These common subnetworks along with G protein-specific subnetworks together confer selectivity to the G protein coupling. This work underscores the potential of data-driven Bayesian network modeling in elucidating the intricate dependencies and selectivity determinants in GPCR:G protein complexes, offering valuable insights into the dynamic nature of these essential cellular signaling components.
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Affiliation(s)
- Elizaveta Mukhaleva
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, CA 91010
| | - Ning Ma
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
| | - Wijnand J. C. van der Velden
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
| | - Grigoriy Gogoshin
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
| | - Sergio Branciamore
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, CA 91010
| | - Supriyo Bhattacharya
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
| | - Andrei S. Rodin
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, CA 91010
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, CA 91010
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10
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Cao Y, van der Velden WJC, Namkung Y, Nivedha AK, Cho A, Sedki D, Holleran B, Lee N, Leduc R, Muk S, Le K, Bhattacharya S, Vaidehi N, Laporte SA. Unraveling allostery within the angiotensin II type 1 receptor for Gα q and β-arrestin coupling. Sci Signal 2023; 16:eadf2173. [PMID: 37552769 PMCID: PMC10640921 DOI: 10.1126/scisignal.adf2173] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 07/20/2023] [Indexed: 08/10/2023]
Abstract
G protein-coupled receptors engage both G proteins and β-arrestins, and their coupling can be biased by ligands and mutations. Here, to resolve structural elements and mechanisms underlying effector coupling to the angiotensin II (AngII) type 1 receptor (AT1R), we combined alanine scanning mutagenesis of the entire sequence of the receptor with pharmacological profiling of Gαq and β-arrestin engagement to mutant receptors and molecular dynamics simulations. We showed that Gαq coupling to AT1R involved a large number of residues spread across the receptor, whereas fewer structural regions of the receptor contributed to β-arrestin coupling regulation. Residue stretches in transmembrane domain 4 conferred β-arrestin bias and represented an important structural element in AT1R for functional selectivity. Furthermore, we identified allosteric small-molecule binding sites that were enclosed by communities of residues that produced biased signaling when mutated. Last, we showed that allosteric communication within AT1R emanating from the Gαq coupling site spread beyond the orthosteric AngII-binding site and across different regions of the receptor, including currently unresolved structural regions. Our findings reveal structural elements and mechanisms within AT1R that bias Gαq and β-arrestin coupling and that could be harnessed to design biased receptors for research purposes and to develop allosteric modulators.
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Affiliation(s)
- Yubo Cao
- Department of Pharmacology and Therapeutics, McGill University, Montréal, Québec H3G 1Y6, Canada
| | - Wijnand J. C. van der Velden
- Department of Computational & Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California 91010, USA
| | - Yoon Namkung
- Department of Medicine, McGill University Health Center, McGill University, Montréal, Québec H4A 3J1, Canada
| | - Anita K. Nivedha
- Department of Computational & Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California 91010, USA
| | - Aaron Cho
- Department of Medicine, McGill University Health Center, McGill University, Montréal, Québec H4A 3J1, Canada
| | - Dana Sedki
- Department of Medicine, McGill University Health Center, McGill University, Montréal, Québec H4A 3J1, Canada
| | - Brian Holleran
- Department of Pharmacology-Physiology, Université de Sherbrooke, Sherbrooke, Québec, J1H 5N4, Canada
| | - Nicholas Lee
- Department of Medicine, McGill University Health Center, McGill University, Montréal, Québec H4A 3J1, Canada
| | - Richard Leduc
- Department of Pharmacology-Physiology, Université de Sherbrooke, Sherbrooke, Québec, J1H 5N4, Canada
| | - Sanychen Muk
- Department of Computational & Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California 91010, USA
| | - Keith Le
- Department of Computational & Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California 91010, USA
| | - Supriyo Bhattacharya
- Department of Computational & Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California 91010, USA
| | - Nagarajan Vaidehi
- Department of Computational & Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California 91010, USA
| | - Stéphane A. Laporte
- Department of Pharmacology and Therapeutics, McGill University, Montréal, Québec H3G 1Y6, Canada
- Department of Medicine, McGill University Health Center, McGill University, Montréal, Québec H4A 3J1, Canada
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11
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Hall J, Zhang Z, Wang D, Bhattacharya S, Alcantara M, Liang Y, Swiderski P, Forman S, Kwak L, Vaidehi N, Kortylewski M. Oligo-PROTAC strategy for cell-selective and targeted degradation of activated STAT3. bioRxiv 2023:2023.08.01.551552. [PMID: 37577590 PMCID: PMC10418257 DOI: 10.1101/2023.08.01.551552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Decoy-oligodeoxynucleotides (D-ODNs) can target undruggable transcription factors, such as STAT3. However, challenges in D-ODN delivery and potency hampered their translation. To overcome these limitations, we conjugated STAT3-specific D-ODN to thalidomide (Tha), a known ligand to cereblon (CRBN, a component of E3 ubiquitin ligase) to generate a proteolysis-targeting chimera (STAT3D PROTAC ). STAT3D PROTAC downregulated STAT3, but not STAT1 or STAT5, in target cells. Computational modeling of the STAT3D PROTAC ternary complex predicted two surface lysines on STAT3, K601 and K626 as potential ubiquitination sites for the PROTAC bound E3 ligase. Accordingly, K601/K626 point mutations in STAT3, as well as proteasome inhibitors, and CRBN deletion alleviated STAT3D PROTAC effect. Next, we conjugated STAT3D PROTAC to a CpG ligand targeting Toll-like receptor 9 (TLR9) to generate myeloid/B-cell-selective C-STAT3D PROTAC conjugate. Naked C-STAT3D PROTAC was spontaneously internalized by TLR9 + myeloid cells, B cells as well as human Ly18 and mouse A20 lymphoma cells, but not by T cells. C-STAT3D PROTAC decreased STAT3 levels to 50% at 250 nM and over 85% at 2 µM dosing in myeloid cells. We also observed significantly improved downregulation of STAT3 target genes involved in lymphoma cell proliferation and/or survival ( BCL2L1, CCND2, MYC ). Finally, we assessed the antitumor efficacy of C-STAT3D PROTAC compared to C-STAT3D or scrambled control (C-SCR) against human lymphoma xenotransplants. Local C-STAT3D PROTAC administration triggered lymphoma regression while control treatments had limited effects. Our results underscore feasibility of using PROTAC strategy for cell-selective, decoy oligonucleotide-based targeting of STAT3 and potentially other tumorigenic transcription factors for cancer therapy.
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12
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Gusach A, Lee Y, Khoshgrudi AN, Mukhaleva E, Ma N, Koers EJ, Chen Q, Edwards PC, Huang F, Kim J, Mancia F, Verprintsev DB, Vaidehi N, Weyand SN, Tate CG. Molecular recognition of an aversive odorant by the murine trace amine-associated receptor TAAR7f. bioRxiv 2023:2023.07.07.547762. [PMID: 37461561 PMCID: PMC10350033 DOI: 10.1101/2023.07.07.547762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
There are two main families of G protein-coupled receptors that detect odours in humans, the odorant receptors (ORs) and the trace amine-associated receptors (TAARs). Their amino acid sequences are distinct, with the TAARs being most similar to the aminergic receptors such as those activated by adrenaline, serotonin and histamine. To elucidate the structural determinants of ligand recognition by TAARs, we have determined the cryo-EM structure of a murine receptor, mTAAR7f, coupled to the heterotrimeric G protein Gs and bound to the odorant N,N-dimethylcyclohexylamine (DMCH) to an overall resolution of 2.9 Å. DMCH is bound in a hydrophobic orthosteric binding site primarily through van der Waals interactions and a strong charge-charge interaction between the tertiary amine of the ligand and an aspartic acid residue. This site is distinct and non-overlapping with the binding site for the odorant propionate in the odorant receptor OR51E2. The structure, in combination with mutagenesis data and molecular dynamics simulations suggests that the activation of the receptor follows a similar pathway to that of the β-adrenoceptors, with the significant difference that DMCH interacts directly with one of the main activation microswitch residues.
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Affiliation(s)
- Anastasiia Gusach
- MRC Laboratory of Molecular Biology, Francis Crick Avenue,
Cambridge CB2 0QH, UK
| | - Yang Lee
- MRC Laboratory of Molecular Biology, Francis Crick Avenue,
Cambridge CB2 0QH, UK
| | - Armin Nikpour Khoshgrudi
- Centre of Membrane Proteins and Receptors (COMPARE), University
of Birmingham and University of Nottingham, Midlands, NG7 2RD, UK
- Division of Physiology, Pharmacology & Neuroscience, School
of Life Sciences, University of Nottingham, Nottingham, NG7 2UH, UK
| | - Elizaveta Mukhaleva
- Department of Computational and Quantitative Medicine, Beckman
Research Institute of the City of Hope, 1500 E Duarte Road, Duarte, CA-91006, USA
| | - Ning Ma
- Department of Computational and Quantitative Medicine, Beckman
Research Institute of the City of Hope, 1500 E Duarte Road, Duarte, CA-91006, USA
| | - Eline J. Koers
- Centre of Membrane Proteins and Receptors (COMPARE), University
of Birmingham and University of Nottingham, Midlands, NG7 2RD, UK
- Division of Physiology, Pharmacology & Neuroscience, School
of Life Sciences, University of Nottingham, Nottingham, NG7 2UH, UK
| | - Qingchao Chen
- MRC Laboratory of Molecular Biology, Francis Crick Avenue,
Cambridge CB2 0QH, UK
| | - Patricia C. Edwards
- MRC Laboratory of Molecular Biology, Francis Crick Avenue,
Cambridge CB2 0QH, UK
| | - Fanglu Huang
- Department of Biochemistry, University of Cambridge, Tennis Court
Road, Cambridge, UK
| | - Jonathan Kim
- Department of Physiology and Cellular Biophysics, Columbia
University, Irving Medical Center, New York, NY 10032, USA
| | - Filippo Mancia
- Department of Physiology and Cellular Biophysics, Columbia
University, Irving Medical Center, New York, NY 10032, USA
| | - Dmitry B. Verprintsev
- Centre of Membrane Proteins and Receptors (COMPARE), University
of Birmingham and University of Nottingham, Midlands, NG7 2RD, UK
- Division of Physiology, Pharmacology & Neuroscience, School
of Life Sciences, University of Nottingham, Nottingham, NG7 2UH, UK
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman
Research Institute of the City of Hope, 1500 E Duarte Road, Duarte, CA-91006, USA
| | - Simone N. Weyand
- Department of Biochemistry, University of Cambridge, Tennis Court
Road, Cambridge, UK
- Department of Medicine, University of Cambridge, Victor Phillip
Dahdaleh Building, Heart & Lung Research Institute, Papworth Road, Cambridge Biomedical
Campus, Cambridge, CB2 0BB, UK
- Cambridge Institute for Medical Research, Keith Peters Building,
Biomedical Campus, Hills Rd, Cambridge CB2 0XY, UK
- EMBL’s European Bioinformatics Institute (EMBL-EBI),
Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Christopher G. Tate
- MRC Laboratory of Molecular Biology, Francis Crick Avenue,
Cambridge CB2 0QH, UK
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13
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Lefevre TJ, Wei W, Mukhaleva E, Venkata SPM, Chandan NR, Abraham S, Li Y, Dessauer CW, Vaidehi N, Smrcka AV. Stabilization of Interdomain Interactions in G protein α i Subunits Determines Gα i Subtype Signaling Specificity. bioRxiv 2023:2023.03.10.532072. [PMID: 37066214 PMCID: PMC10103935 DOI: 10.1101/2023.03.10.532072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Highly homologous members of the Gαi family, Gαi1-3, have distinct tissue distributions and physiological functions, yet the functional properties of these proteins with respect to GDP/GTP binding and regulation of adenylate cyclase are very similar. We recently identified PDZ-RhoGEF (PRG) as a novel Gαi1 effector, however, it is poorly activated by Gαi2. Here, in a proteomic proximity labeling screen we observed a strong preference for Gαi1 relative to Gαi2 with respect to engagement of a broad range of potential targets. We investigated the mechanistic basis for this selectivity using PRG as a representative target. Substitution of either the helical domain (HD) from Gαi1 into Gαi2 or substitution of a single amino acid, A230 in Gαi2 to the corresponding D in Gαi1, largely rescues PRG activation and interactions with other Gαi targets. Molecular dynamics simulations combined with Bayesian network models revealed that in the GTP bound state, dynamic separation at the HD-Ras-like domain (RLD) interface is prevalent in Gαi2 relative to Gαi1 and that mutation of A230s4h3.3 to D in Gαi2 stabilizes HD-RLD interactions through formation of an ionic interaction with R145HD.11 in the HD. These interactions in turn modify the conformation of Switch III. These data support a model where D229s4h3.3 in Gαi1 interacts with R144HD.11 stabilizes a network of interactions between HD and RLD to promote protein target recognition. The corresponding A230 in Gαi2 is unable to form the "ionic lock" to stabilize this network leading to an overall lower efficacy with respect to target interactions. This study reveals distinct mechanistic properties that could underly differential biological and physiological consequences of activation of Gαi1 or Gαi2 by GPCRs.
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Affiliation(s)
- Tyler J. Lefevre
- Department of Pharmacology, University of Michigan Medical School, Ann Arbor, MI
- Program in Chemical Biology, University of Michigan, Ann Arbor, MI
| | - Wenyuan Wei
- Department of Integrative Biology and Pharmacology McGovern Medical School, UTHealth, Houston, TX
| | - Elizaveta Mukhaleva
- Department of Integrative Biology and Pharmacology McGovern Medical School, UTHealth, Houston, TX
| | | | - Naincy R. Chandan
- Department of Pharmacology, University of Michigan Medical School, Ann Arbor, MI
- Genentech, South San Francisco, CA
| | - Saji Abraham
- Department of Pharmacology, University of Michigan Medical School, Ann Arbor, MI
| | - Yong Li
- Department of Integrative Biology and Pharmacology McGovern Medical School, UTHealth, Houston, TX
| | - Carmen W. Dessauer
- Department of Integrative Biology and Pharmacology McGovern Medical School, UTHealth, Houston, TX
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA
| | - Alan V. Smrcka
- Department of Pharmacology, University of Michigan Medical School, Ann Arbor, MI
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14
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Lee J, Robinson ME, Sun R, Kume K, Ma N, Cosgun KN, Chan LN, Leveille E, Geng H, Vykunta VS, Shy BR, Marson A, Katz S, Chen J, Paietta E, Meffre E, Vaidehi N, Müschen M. Dynamic phosphatase-recruitment controls B-cell selection and oncogenic signaling. bioRxiv 2023:2023.03.13.532151. [PMID: 36993276 PMCID: PMC10054997 DOI: 10.1101/2023.03.13.532151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Initiation of B-cell receptor (BCR) 1 signaling, and subsequent antigen-encounter in germinal centers 2,3 represent milestones of B-lymphocyte development that are both marked by sharp increases of CD25 surface-expression. Oncogenic signaling in B-cell leukemia (B-ALL) 4 and lymphoma 5 also induced CD25-surface expression. While CD25 is known as an IL2-receptor chain on T- and NK-cells 6-9 , the significance of its expression on B-cells was unclear. Our experiments based on genetic mouse models and engineered patient-derived xenografts revealed that, rather than functioning as an IL2-receptor chain, CD25 expressed on B-cells assembled an inhibitory complex including PKCδ and SHIP1 and SHP1 phosphatases for feedback control of BCR-signaling or its oncogenic mimics. Recapitulating phenotypes of genetic ablation of PKCδ 10 - 12 , SHIP1 13,14 and SHP1 14, 15,16 , conditional CD25-deletion decimated early B-cell subsets but expanded mature B-cell populations and induced autoimmunity. In B-cell malignancies arising from early (B-ALL) and late (lymphoma) stages of B-cell development, CD25-loss induced cell death in the former and accelerated proliferation in the latter. Clinical outcome annotations mirrored opposite effects of CD25-deletion: high CD25 expression levels predicted poor clinical outcomes for patients with B-ALL, in contrast to favorable outcomes for lymphoma-patients. Biochemical and interactome studies revealed a critical role of CD25 in BCR-feedback regulation: BCR-signaling induced PKCδ-mediated phosphorylation of CD25 on its cytoplasmic tail (S 268 ). Genetic rescue experiments identified CD25-S 268 tail-phosphorylation as central structural requirement to recruit SHIP1 and SHP1 phosphatases to curb BCR-signaling. A single point mutation CD25 S268A abolished recruitment and activation of SHIP1 and SHP1 to limit duration and strength of BCR-signaling. Loss of phosphatase-function, autonomous BCR-signaling and Ca 2+ -oscillations induced anergy and negative selection during early B-cell development, as opposed to excessive proliferation and autoantibody production in mature B-cells. These findings highlight the previously unrecognized role of CD25 in assembling inhibitory phosphatases to control oncogenic signaling in B-cell malignancies and negative selection to prevent autoimmune disease.
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15
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Sattler M, Mambetsariev I, Fricke J, Tan T, Liu S, Vaidehi N, Pisick E, Mirzapoiazova T, Rock AG, Merla A, Sharma S, Salgia R. A Closer Look at EGFR Inhibitor Resistance in Non-Small Cell Lung Cancer through the Lens of Precision Medicine. J Clin Med 2023; 12:jcm12051936. [PMID: 36902723 PMCID: PMC10003860 DOI: 10.3390/jcm12051936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 02/22/2023] [Accepted: 02/26/2023] [Indexed: 03/05/2023] Open
Abstract
The development of EGFR small-molecule inhibitors has provided significant benefit for the affected patient population. Unfortunately, current inhibitors are no curative therapy, and their development has been driven by on-target mutations that interfere with binding and thus inhibitory activity. Genomic studies have revealed that, in addition to these on-target mutations, there are also multiple off-target mechanisms of EGFR inhibitor resistance and novel therapeutics that can overcome these challenges are sought. Resistance to competitive 1st-generation and covalent 2nd- and 3rd-generation EGFR inhibitors is overall more complex than initially thought, and novel 4th-generation allosteric inhibitors are expected to suffer from a similar fate. Additional nongenetic mechanisms of resistance are significant and can include up to 50% of the escape pathways. These potential targets have gained recent interest and are usually not part of cancer panels that look for alterations in resistant patient specimen. We discuss the duality between genetic and nongenetic EGFR inhibitor drug resistance and summarize current team medicine approaches, wherein clinical developments, hand in hand with drug development research, drive potential opportunities for combination therapy.
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Affiliation(s)
- Martin Sattler
- Department of Medical Oncology, Dana-Farber Cancer Institute, 450 Brookline Ave., Boston, MA 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Correspondence:
| | - Isa Mambetsariev
- Department of Medical Oncology and Therapeutics Research, City of Hope, 1500 E Duarte Road, Duarte, CA 91010, USA
| | - Jeremy Fricke
- Department of Medical Oncology and Therapeutics Research, City of Hope, 1500 E Duarte Road, Duarte, CA 91010, USA
| | - Tingting Tan
- Department of Medical Oncology and Therapeutics Research, City of Hope, 1500 E Duarte Road, Duarte, CA 91010, USA
| | - Sariah Liu
- Department of Medical Oncology and Therapeutics Research, City of Hope, 1500 E Duarte Road, Duarte, CA 91010, USA
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, City of Hope, 1500 E Duarte Road, Duarte, CA 91010, USA
| | - Evan Pisick
- City of Hope Chicago, 2520 Elisha Avenue, Zion, IL 60099, USA
| | - Tamara Mirzapoiazova
- Department of Medical Oncology and Therapeutics Research, City of Hope, 1500 E Duarte Road, Duarte, CA 91010, USA
| | - Adam G. Rock
- Department of Medical Oncology and Therapeutics Research, City of Hope, 1500 E Duarte Road, Duarte, CA 91010, USA
| | - Amartej Merla
- Department of Medical Oncology and Therapeutics Research, City of Hope, 1500 E Duarte Road, Duarte, CA 91010, USA
| | - Sunil Sharma
- Division of Applied Cancer Research and Drug Discovery, Translational Genomic Research Institute (Tgen), 445 N 5th St, Phoenix, AZ 85004, USA
| | - Ravi Salgia
- Department of Medical Oncology and Therapeutics Research, City of Hope, 1500 E Duarte Road, Duarte, CA 91010, USA
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16
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Sadler F, Ma N, Ritt M, Sharma Y, Vaidehi N, Sivaramakrishnan S. Autoregulation of GPCR signalling through the third intracellular loop. Nature 2023; 615:734-741. [PMID: 36890236 PMCID: PMC10033409 DOI: 10.1038/s41586-023-05789-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 02/03/2023] [Indexed: 03/10/2023]
Abstract
The third intracellular loop (ICL3) of the G protein-coupled receptor (GPCR) fold is important for the signal transduction process downstream of receptor activation1-3. Despite this, the lack of a defined structure of ICL3, combined with its high sequence divergence among GPCRs, complicates characterization of its involvement in receptor signalling4. Previous studies focusing on the β2 adrenergic receptor (β2AR) suggest that ICL3 is involved in the structural process of receptor activation and signalling5-7. Here we derive mechanistic insights into the role of ICL3 in β2AR signalling, observing that ICL3 autoregulates receptor activity through a dynamic conformational equilibrium between states that block or expose the receptor's G protein-binding site. We demonstrate the importance of this equilibrium for receptor pharmacology, showing that G protein-mimetic effectors bias the exposed states of ICL3 to allosterically activate the receptor. Our findings additionally reveal that ICL3 tunes signalling specificity by inhibiting receptor coupling to G protein subtypes that weakly couple to the receptor. Despite the sequence diversity of ICL3, we demonstrate that this negative G protein-selection mechanism through ICL3 extends to GPCRs across the superfamily, expanding the range of known mechanisms by which receptors mediate G protein subtype selective signalling. Furthermore, our collective findings suggest ICL3 as an allosteric site for receptor- and signalling pathway-specific ligands.
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Affiliation(s)
- Fredrik Sadler
- Biochemistry, Molecular Biology and Biophysics Graduate Program, University of Minnesota, Minneapolis, MN, USA
- Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN, USA
| | - Ning Ma
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, CA, USA
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - Michael Ritt
- Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN, USA
| | - Yatharth Sharma
- Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN, USA
| | - Nagarajan Vaidehi
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, CA, USA
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - Sivaraj Sivaramakrishnan
- Biochemistry, Molecular Biology and Biophysics Graduate Program, University of Minnesota, Minneapolis, MN, USA.
- Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN, USA.
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17
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Billesbølle CB, de March CA, van der Velden WJC, Ma N, Tewari J, Del Torrent CL, Li L, Faust B, Vaidehi N, Matsunami H, Manglik A. Structural basis of odorant recognition by a human odorant receptor. Nature 2023; 615:742-749. [PMID: 36922591 PMCID: PMC10580732 DOI: 10.1038/s41586-023-05798-y] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 02/06/2023] [Indexed: 03/17/2023]
Abstract
Our sense of smell enables us to navigate a vast space of chemically diverse odour molecules. This task is accomplished by the combinatorial activation of approximately 400 odorant G protein-coupled receptors encoded in the human genome1-3. How odorants are recognized by odorant receptors remains unclear. Here we provide mechanistic insight into how an odorant binds to a human odorant receptor. Using cryo-electron microscopy, we determined the structure of the active human odorant receptor OR51E2 bound to the fatty acid propionate. Propionate is bound within an occluded pocket in OR51E2 and makes specific contacts critical to receptor activation. Mutation of the odorant-binding pocket in OR51E2 alters the recognition spectrum for fatty acids of varying chain length, suggesting that odorant selectivity is controlled by tight packing interactions between an odorant and an odorant receptor. Molecular dynamics simulations demonstrate that propionate-induced conformational changes in extracellular loop 3 activate OR51E2. Together, our studies provide a high-resolution view of chemical recognition of an odorant by a vertebrate odorant receptor, providing insight into how this large family of G protein-coupled receptors enables our olfactory sense.
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Affiliation(s)
| | - Claire A de March
- Department of Molecular Genetics and Microbiology, Duke University, Durham, NC, USA
- Institut de Chimie des Substances Naturelles, UPR2301 CNRS, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Wijnand J C van der Velden
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - Ning Ma
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - Jeevan Tewari
- Department of Molecular Genetics and Microbiology, Duke University, Durham, NC, USA
| | - Claudia Llinas Del Torrent
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA, USA
- Laboratory of Computational Medicine, Biostatistics Unit, Faculty of Medicine, Universitat Autònoma Barcelona, Bellaterra, Barcelona, Spain
| | - Linus Li
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA, USA
| | - Bryan Faust
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA, USA
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA, USA.
| | - Hiroaki Matsunami
- Department of Molecular Genetics and Microbiology, Duke University, Durham, NC, USA.
- Department of Neurobiology, Duke Institute for Brain Sciences, Duke University, Durham, NC, USA.
| | - Aashish Manglik
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA, USA.
- Department of Anesthesia and Perioperative Care, University of California, San Francisco, CA, USA.
- Chan Zuckerberg Biohub, San Francisco, CA, USA.
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18
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Hewitt N, Ma N, Arang N, Martin SA, Prakash A, DiBerto JF, Knight KM, Ghosh S, Olsen RHJ, Roth BL, Gutkind JS, Vaidehi N, Campbell SL, Dohlman HG. Catalytic site mutations confer multiple states of G protein activation. Sci Signal 2023; 16:eabq7842. [PMID: 36787384 PMCID: PMC10021883 DOI: 10.1126/scisignal.abq7842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 01/31/2023] [Indexed: 02/16/2023]
Abstract
Heterotrimeric guanine nucleotide-binding proteins (G proteins) that function as molecular switches for cellular growth and metabolism are activated by GTP and inactivated by GTP hydrolysis. In uveal melanoma, a conserved glutamine residue critical for GTP hydrolysis in the G protein α subunit is often mutated in Gαq or Gα11 to either leucine or proline. In contrast, other glutamine mutations or mutations in other Gα subtypes are rare. To uncover the mechanism of the genetic selection and the functional role of this glutamine residue, we analyzed all possible substitutions of this residue in multiple Gα isoforms. Through cell-based measurements of activity, we showed that some mutants were further activated and inactivated by G protein-coupled receptors. Through biochemical, molecular dynamics, and nuclear magnetic resonance-based structural studies, we showed that the Gα mutants were functionally distinct and conformationally diverse, despite their shared inability to hydrolyze GTP. Thus, the catalytic glutamine residue contributes to functions beyond GTP hydrolysis, and these functions include subtype-specific, allosteric modulation of receptor-mediated subunit dissociation. We conclude that G proteins do not function as simple on-off switches. Rather, signaling emerges from an ensemble of active states, a subset of which are favored in disease and may be uniquely responsive to receptor-directed ligands.
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Affiliation(s)
- Natalie Hewitt
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Ning Ma
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010, USA
| | - Nadia Arang
- Department of Pharmacology, University of California San Diego, San Diego, CA, 92093, USA
- Moores Cancer Center, University of California San Diego, La Jolla, CA 92093, USA
| | - Sarah A. Martin
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Ajit Prakash
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jeffrey F. DiBerto
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Kevin M. Knight
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Soumadwip Ghosh
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010, USA
- Current address: Illumina Inc, 5200 Illumina Way, San Diego, CA 92037, USA
| | - Reid H. J. Olsen
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Current address: GPCR Pharmacology, Discovery Biology, Exscientia Ai, Oxford, UK OX4 4GE
| | - Bryan L. Roth
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - J. Silvio Gutkind
- Department of Pharmacology, University of California San Diego, San Diego, CA, 92093, USA
- Moores Cancer Center, University of California San Diego, La Jolla, CA 92093, USA
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010, USA
| | - Sharon L. Campbell
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Henrik G. Dohlman
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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19
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Nivedha AK, Lee S, Vaidehi N. Biased agonists differentially modulate the receptor conformation ensembles in Angiotensin II type 1 receptor. J Mol Graph Model 2023; 118:108365. [PMID: 36335829 PMCID: PMC9769363 DOI: 10.1016/j.jmgm.2022.108365] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 10/05/2022] [Accepted: 10/14/2022] [Indexed: 11/06/2022]
Abstract
The structural features that contribute to the efficacy of biased agonists targeting G protein-coupled receptors (GPCRs) towards G proteins or β-arrestin (β-arr) signaling pathways is nebulous, although such knowledge is critical in designing biased ligands. The dynamics of the agonist-GPCR complex is one of the critical factors in determining agonist bias. Angiotensin II type I receptor (AT1R) is an ideal model system to study the molecular basis of bias since it has multiple β-arr2 and Gq protein biased agonists as well as experimentally solved three dimensional structures. Using Molecular Dynamics (MD) simulations for the Angiotensin II type I receptor (AT1R) bound to ten different agonists, we infer that the agonist bound receptor samples conformations with different relative weights, from both the inactive and active state ensembles of the receptor. This concept is perhaps extensible to other class A GPCRs. Such a weighted mixed ensemble recapitulates the inter-residue distance distributions measured for different agonists bound AT1R using DEER experiments. The ratio of the calculated relative strength of the allosteric communication to β-arr2 vs Gq coupling sites scale similarly to the experimentally measured bias factors. Analysis of the inter-residue distance distributions of the activation microswitches involved in class A GPCR activation suggests that β-arr2 biased agonists turn on different combination of microswitches with different relative strengths of activation. We put forth a model that activation microswitches behave like rheostats that tune the relative efficacy of the biased agonists toward the two signaling pathways. Finally, based on our data we propose that the agonist specific residue contacts in the binding site elicit a combinatorial response in the microswitches that in turn differentially modulate the receptor conformation ensembles resulting in differences in coupling to Gq and β-arrestin.
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Affiliation(s)
- Anita K Nivedha
- Department of Computational & Quantitative Medicine, Beckman Research Institute of the City of Hope, 1500 E. Duarte Road, Duarte, California, 91010, USA
| | - Sangbae Lee
- Department of Computational & Quantitative Medicine, Beckman Research Institute of the City of Hope, 1500 E. Duarte Road, Duarte, California, 91010, USA
| | - Nagarajan Vaidehi
- Department of Computational & Quantitative Medicine, Beckman Research Institute of the City of Hope, 1500 E. Duarte Road, Duarte, California, 91010, USA.
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20
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Sandhu M, Cho A, Ma N, Mukhaleva E, Namkung Y, Lee S, Ghosh S, Lee JH, Gloriam DE, Laporte SA, Babu MM, Vaidehi N. Dynamic spatiotemporal determinants modulate GPCR:G protein coupling selectivity and promiscuity. Nat Commun 2022; 13:7428. [PMID: 36460632 PMCID: PMC9718833 DOI: 10.1038/s41467-022-34055-5] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Accepted: 10/11/2022] [Indexed: 12/03/2022] Open
Abstract
Recent studies have shown that G protein coupled receptors (GPCRs) show selective and promiscuous coupling to different Gα protein subfamilies and yet the mechanisms of the range of coupling preferences remain unclear. Here, we use Molecular Dynamics (MD) simulations on ten GPCR:G protein complexes and show that the location (spatial) and duration (temporal) of intermolecular contacts at the GPCR:Gα protein interface play a critical role in how GPCRs selectively interact with G proteins. We identify that some GPCR:G protein interface contacts are common across Gα subfamilies and others specific to Gα subfamilies. Using large scale data analysis techniques on the MD simulation snapshots we derive a spatio-temporal code for contacts that confer G protein selective coupling and validated these contacts using G protein activation BRET assays. Our results demonstrate that promiscuous GPCRs show persistent sampling of the common contacts more than G protein specific contacts. These findings suggest that GPCRs maintain contact with G proteins through a common central interface, while the selectivity comes from G protein specific contacts at the periphery of the interface.
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Affiliation(s)
- Manbir Sandhu
- grid.410425.60000 0004 0421 8357Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010 USA ,grid.240871.80000 0001 0224 711XDepartment of Structural Biology, Center for Data Driven Discovery, St. Jude Children’s Research Hospital, Memphis, TN 38105 USA
| | - Aaron Cho
- grid.63984.300000 0000 9064 4811Department of Medicine, Research Institute of the McGill University Health Centre, Montreal, QC H4A 3J1 Canada
| | - Ning Ma
- grid.410425.60000 0004 0421 8357Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010 USA
| | - Elizaveta Mukhaleva
- grid.410425.60000 0004 0421 8357Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010 USA ,grid.410425.60000 0004 0421 8357Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, CA 91010 USA
| | - Yoon Namkung
- grid.63984.300000 0000 9064 4811Department of Medicine, Research Institute of the McGill University Health Centre, Montreal, QC H4A 3J1 Canada
| | - Sangbae Lee
- grid.410425.60000 0004 0421 8357Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010 USA
| | - Soumadwip Ghosh
- grid.410425.60000 0004 0421 8357Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010 USA
| | - John H. Lee
- grid.410425.60000 0004 0421 8357Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010 USA
| | - David E. Gloriam
- grid.5254.60000 0001 0674 042XDepartment of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, 2100 Copenhagen, Denmark
| | - Stéphane A. Laporte
- grid.63984.300000 0000 9064 4811Department of Medicine, Research Institute of the McGill University Health Centre, Montreal, QC H4A 3J1 Canada ,grid.14709.3b0000 0004 1936 8649Department of Pharmacology and Therapeutics, McGill University, Montréal, QC H3G 1Y6 Canada
| | - M. Madan Babu
- grid.240871.80000 0001 0224 711XDepartment of Structural Biology, Center for Data Driven Discovery, St. Jude Children’s Research Hospital, Memphis, TN 38105 USA ,grid.42475.300000 0004 0605 769XMRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH UK
| | - Nagarajan Vaidehi
- grid.410425.60000 0004 0421 8357Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010 USA ,grid.410425.60000 0004 0421 8357Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, CA 91010 USA
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21
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Ladbury C, Zarinshenas R, Semwal H, Tam A, Vaidehi N, Rodin AS, Liu A, Glaser S, Salgia R, Amini A. Utilization of model-agnostic explainable artificial intelligence frameworks in oncology: a narrative review. Transl Cancer Res 2022; 11:3853-3868. [PMID: 36388027 PMCID: PMC9641128 DOI: 10.21037/tcr-22-1626] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 09/07/2022] [Indexed: 11/25/2022]
Abstract
Background and Objective Machine learning (ML) models are increasingly being utilized in oncology research for use in the clinic. However, while more complicated models may provide improvements in predictive or prognostic power, a hurdle to their adoption are limits of model interpretability, wherein the inner workings can be perceived as a "black box". Explainable artificial intelligence (XAI) frameworks including Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP) are novel, model-agnostic approaches that aim to provide insight into the inner workings of the "black box" by producing quantitative visualizations of how model predictions are calculated. In doing so, XAI can transform complicated ML models into easily understandable charts and interpretable sets of rules, which can give providers with an intuitive understanding of the knowledge generated, thus facilitating the deployment of such models in routine clinical workflows. Methods We performed a comprehensive, non-systematic review of the latest literature to define use cases of model-agnostic XAI frameworks in oncologic research. The examined database was PubMed/MEDLINE. The last search was run on May 1, 2022. Key Content and Findings In this review, we identified several fields in oncology research where ML models and XAI were utilized to improve interpretability, including prognostication, diagnosis, radiomics, pathology, treatment selection, radiation treatment workflows, and epidemiology. Within these fields, XAI facilitates determination of feature importance in the overall model, visualization of relationships and/or interactions, evaluation of how individual predictions are produced, feature selection, identification of prognostic and/or predictive thresholds, and overall confidence in the models, among other benefits. These examples provide a basis for future work to expand on, which can facilitate adoption in the clinic when the complexity of such modeling would otherwise be prohibitive. Conclusions Model-agnostic XAI frameworks offer an intuitive and effective means of describing oncology ML models, with applications including prognostication and determination of optimal treatment regimens. Using such frameworks presents an opportunity to improve understanding of ML models, which is a critical step to their adoption in the clinic.
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Affiliation(s)
- Colton Ladbury
- Department of Radiation Oncology, City of Hope National Medical Center, Duarte, CA, USA
| | - Reza Zarinshenas
- Department of Radiation Oncology, City of Hope National Medical Center, Duarte, CA, USA
| | - Hemal Semwal
- Departments of Bioengineering and Integrated Biology and Physiology, University of California Los Angeles, Los Angeles, CA, USA
| | - Andrew Tam
- Department of Radiation Oncology, City of Hope National Medical Center, Duarte, CA, USA
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, City of Hope National Medical Center, Duarte, CA, USA
| | - Andrei S Rodin
- Department of Computational and Quantitative Medicine, City of Hope National Medical Center, Duarte, CA, USA
| | - An Liu
- Department of Radiation Oncology, City of Hope National Medical Center, Duarte, CA, USA
| | - Scott Glaser
- Department of Radiation Oncology, City of Hope National Medical Center, Duarte, CA, USA
| | - Ravi Salgia
- Department of Medical Oncology, City of Hope National Medical Center, Duarte, CA, USA
| | - Arya Amini
- Department of Radiation Oncology, City of Hope National Medical Center, Duarte, CA, USA
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22
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Abstract
The fungal class D1 G-protein-coupled receptor (GPCR) Ste2 has a different arrangement of transmembrane helices compared with mammalian GPCRs and a distinct mode of coupling to the heterotrimeric G protein Gpa1-Ste2-Ste181. In addition, Ste2 lacks conserved sequence motifs such as DRY, PIF and NPXXY, which are associated with the activation of class A GPCRs2. This suggested that the activation mechanism of Ste2 may also differ. Here we determined structures of Saccharomyces cerevisiae Ste2 in the absence of G protein in two different conformations bound to the native agonist α-factor, bound to an antagonist and without ligand. These structures revealed that Ste2 is indeed activated differently from other GPCRs. In the inactive state, the cytoplasmic end of transmembrane helix H7 is unstructured and packs between helices H1-H6, blocking the G protein coupling site. Agonist binding results in the outward movement of the extracellular ends of H6 and H7 by 6 Å. On the intracellular surface, the G protein coupling site is formed by a 20 Å outward movement of the unstructured region in H7 that unblocks the site, and a 12 Å inward movement of H6. This is a distinct mechanism in GPCRs, in which the movement of H6 and H7 upon agonist binding facilitates G protein coupling.
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Affiliation(s)
| | - Ning Ma
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - Christopher G Tate
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, UK.
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23
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Ghosh S, de March CA, Branciamore S, Kaleem S, Matsunami H, Vaidehi N. Sequence coevolution and structure stabilization modulate olfactory receptor expression. Biophys J 2022; 121:830-840. [PMID: 35065915 PMCID: PMC8947990 DOI: 10.1016/j.bpj.2022.01.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 12/14/2021] [Accepted: 01/19/2022] [Indexed: 11/29/2022] Open
Abstract
Olfactory receptors (ORs) belong to class A G-protein coupled receptors (GPCRs) and are activated by a variety of odorants. To date, there is no three-dimensional structure of an OR available. One of the major bottlenecks in obtaining purified protein for structural studies of ORs is their poor expression in heterologous cells. To design mutants that enhance expression and thereby enable protein purification, we first identified computable physical properties that recapitulate OR and class A GPCR expression and further conducted an iterative computational prediction-experimental test cycle and generated human OR mutants that express as high as biogenic amine receptors for which structures have been solved. In the process of developing the computational method to recapitulate the expression of ORs in membranes, we identified properties, such as amino acid sequence coevolution, and the strength of the interactions between intracellular loop 1 (ICL1) and the helix 8 region of ORs, to enhance their heterologous expression. We identified mutations that are directly located in these regions as well as other mutations not located in these regions but allosterically strengthen the ICL1-helix 8 enhance expression. These mutants also showed functional responses to known odorants. This method to enhance heterologous expression of mammalian ORs will facilitate high-throughput "deorphanization" of ORs, and enable OR purification for biochemical and structural studies to understand odorant-OR interactions.
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Affiliation(s)
- Soumadwip Ghosh
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - Claire A. de March
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC, USA
| | - Sergio Branciamore
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - Sahar Kaleem
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC, USA
| | - Hiroaki Matsunami
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC, USA; Department of Neurobiology, Duke Institute for Brain Sciences, Duke University School of Medicine, Durham, NC, USA.
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA, USA.
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24
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Vaidehi N. Dynamic Spatiotemporal Determinants Modulate GPCR:G protein Coupling Promiscuity and Biased Signaling. FASEB J 2021. [DOI: 10.1096/fasebj.2021.35.s1.03925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Nagarajan Vaidehi
- Computatational &Quantitative MedicineBeckman Research Institute of the City of HopeDuarteCA
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25
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Ma N, Nivedha AK, Vaidehi N. Allosteric communication regulates ligand-specific GPCR activity. FEBS J 2021; 288:2502-2512. [PMID: 33738925 PMCID: PMC9805801 DOI: 10.1111/febs.15826] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 03/14/2021] [Accepted: 03/17/2021] [Indexed: 01/11/2023]
Abstract
G protein-coupled receptors (GPCRs) are membrane-bound proteins that are ubiquitously expressed in many cell types and take part in mediating multiple signaling pathways. GPCRs are dynamic proteins and exist in an equilibrium between an ensemble of conformational states such as inactive and fully active states. This dynamic nature of GPCRs is one of the factors that confers their basal activity even in the absence of any ligand-mediated activation. Ligands selectively bind and stabilize a subset of the conformations from the ensemble leading to a shift in the equilibrium toward the inactive or the active state depending on the nature of the ligand. This ligand-selective effect is achieved through allosteric communication between the ligand binding site and G protein or β-arrestin coupling site. Similarly, the G protein coupling to the receptor exerts the allosteric effect on the ligand binding region leading to increased binding affinity for agonists and decreased affinity for antagonists or inverse agonists. In this review, we enumerate the current state of our understanding of the mechanism of allosteric communication in GPCRs with a specific focus on the critical role of computational methods in delineating the residues involved in allosteric communication. Analyzing allosteric communication mechanism using molecular dynamics simulations has revealed (a) a structurally conserved mechanism of allosteric communication that regulates the G protein coupling, (b) a rational structure-based approach to designing selective ligands, and (c) an approach to designing allosteric GPCR mutants that are either ligand and G protein or β-arrestin selective.
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Affiliation(s)
- Ning Ma
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
| | - Anita K. Nivedha
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010,to whom correspondence should be addressed:
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26
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Lee J, Robinson ME, Ma N, Artadji D, Ahmed MA, Xiao G, Sadras T, Deb G, Winchester J, Cosgun KN, Geng H, Chan LN, Kume K, Miettinen TP, Zhang Y, Nix MA, Klemm L, Chen CW, Chen J, Khairnar V, Wiita AP, Thomas-Tikhonenko A, Farzan M, Jung JU, Weinstock DM, Manalis SR, Diamond MS, Vaidehi N, Müschen M. Author Correction: IFITM3 functions as a PIP3 scaffold to amplify PI3K signalling in B cells. Nature 2021; 592:E3. [PMID: 33712811 DOI: 10.1038/s41586-021-03388-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Jaewoong Lee
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Mark E Robinson
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Ning Ma
- Department of Computational and Quantitative Medicine, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Dewan Artadji
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Mohamed A Ahmed
- Department of Systems Biology, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Gang Xiao
- Department of Systems Biology, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Teresa Sadras
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Gauri Deb
- Department of Systems Biology, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Janet Winchester
- Department of Systems Biology, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Kadriye Nehir Cosgun
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Huimin Geng
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Lai N Chan
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Kohei Kume
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Teemu P Miettinen
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.,Medical Research Council Laboratory for Molecular Cell Biology, University College London, London, UK
| | - Ye Zhang
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Matthew A Nix
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Lars Klemm
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Chun Wei Chen
- Department of Systems Biology, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Jianjun Chen
- Department of Systems Biology, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Vishal Khairnar
- Department of Systems Biology, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Arun P Wiita
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Andrei Thomas-Tikhonenko
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michael Farzan
- Department of Immunology and Microbiology, The Scripps Research Institute, Jupiter, FL, USA
| | - Jae U Jung
- Department of Cancer Biology, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - David M Weinstock
- Dana Farber Cancer Institute, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Scott R Manalis
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.,Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Michael S Diamond
- Department of Medicine, Washington University School of Medicine in St Louis, St Louis, MO, USA.,Department of Molecular Microbiology, Washington University School of Medicine in St Louis, St Louis, MO, USA.,Department of Pathology and Immunology, Washington University School of Medicine in St Louis, St Louis, MO, USA
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Markus Müschen
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA. .,Department of Immunobiology, Yale University, New Haven, CT, USA.
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27
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Knight KM, Ghosh S, Campbell SL, Lefevre TJ, Olsen RHJ, Smrcka AV, Valentin NH, Yin G, Vaidehi N, Dohlman HG. A universal allosteric mechanism for G protein activation. Mol Cell 2021; 81:1384-1396.e6. [PMID: 33636126 DOI: 10.1016/j.molcel.2021.02.002] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 12/01/2020] [Accepted: 01/29/2021] [Indexed: 12/11/2022]
Abstract
G proteins play a central role in signal transduction and pharmacology. Signaling is initiated by cell-surface receptors, which promote guanosine triphosphate (GTP) binding and dissociation of Gα from the Gβγ subunits. Structural studies have revealed the molecular basis of subunit association with receptors, RGS proteins, and downstream effectors. In contrast, the mechanism of subunit dissociation is poorly understood. We use cell signaling assays, molecular dynamics (MD) simulations, and biochemistry and structural analyses to identify a conserved network of amino acids that dictates subunit release. In the presence of the terminal phosphate of GTP, a glycine forms a polar network with an arginine and glutamate, putting torsional strain on the subunit binding interface. This "G-R-E motif" secures GTP and, through an allosteric link, discharges the Gβγ dimer. Replacement of network residues prevents subunit dissociation regardless of agonist or GTP binding. These findings reveal the molecular basis of the final committed step of G protein activation.
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Affiliation(s)
- Kevin M Knight
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Soumadwip Ghosh
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010, USA
| | - Sharon L Campbell
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Tyler J Lefevre
- Department of Pharmacology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Reid H J Olsen
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Alan V Smrcka
- Department of Pharmacology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Natalie H Valentin
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Guowei Yin
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010, USA.
| | - Henrik G Dohlman
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
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28
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Ma N, Lee S, Vaidehi N. Activation Microswitches in Adenosine Receptor A2AFunction as Rheostats in Cell Membrane. Biophys J 2021. [DOI: 10.1016/j.bpj.2020.11.997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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29
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Lippert LG, Ma N, Ritt M, Jain A, Vaidehi N, Sivaramakrishnan S. Kinase inhibitors allosterically disrupt a regulatory interaction to enhance PKCα membrane translocation. J Biol Chem 2021; 296:100339. [PMID: 33508318 PMCID: PMC7949123 DOI: 10.1016/j.jbc.2021.100339] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 01/14/2021] [Accepted: 01/22/2021] [Indexed: 10/28/2022] Open
Abstract
The eukaryotic kinase domain has multiple intrinsically disordered regions whose conformation dictates kinase activity. Small molecule kinase inhibitors (SMKIs) rely on disrupting the active conformations of these disordered regions to inactivate the kinase. While SMKIs are selected for their ability to cause this disruption, the allosteric effects of conformational changes in disordered regions is limited by a lack of dynamic information provided by traditional structural techniques. In this study, we integrated multiscale molecular dynamics simulations with FRET sensors to characterize a novel allosteric mechanism that is selectively triggered by SMKI binding to the protein kinase Cα domain. The indole maleimide inhibitors BimI and sotrastaurin were found to displace the Gly-rich loop (G-loop) that normally shields the ATP-binding site. Displacement of the G-loop interferes with a newly identified, structurally conserved binding pocket for the C1a domain on the N lobe of the kinase domain. This binding pocket, in conjunction with the N-terminal regulatory sequence, masks a diacylglycerol (DAG) binding site on the C1a domain. SMKI-mediated displacement of the G-loop released C1a and exposed the DAG binding site, enhancing protein kinase Cα translocation both to synthetic lipid bilayers and to live cell membranes in the presence of DAG. Inhibitor chemotype determined the extent of the observed allosteric effects on the kinase domain and correlated with the extent of membrane recruitment. Our findings demonstrate the allosteric effects of SMKIs beyond the confines of kinase catalytic conformation and provide an integrated computational-experimental paradigm to investigate parallel mechanisms in other kinases.
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Affiliation(s)
- Lisa G Lippert
- Department of Genetics, Cell Biology, and Development, University of Minnesota, Minneapolis, Minnesota, USA
| | - Ning Ma
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA
| | - Michael Ritt
- Department of Genetics, Cell Biology, and Development, University of Minnesota, Minneapolis, Minnesota, USA
| | - Abhinandan Jain
- The Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA.
| | - Sivaraj Sivaramakrishnan
- Department of Genetics, Cell Biology, and Development, University of Minnesota, Minneapolis, Minnesota, USA.
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30
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Velazhahan V, Ma N, Pándy-Szekeres G, Kooistra AJ, Lee Y, Gloriam DE, Vaidehi N, Tate CG. Structure of the class D GPCR Ste2 dimer coupled to two G proteins. Nature 2020; 589:148-153. [PMID: 33268889 PMCID: PMC7116888 DOI: 10.1038/s41586-020-2994-1] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Accepted: 09/25/2020] [Indexed: 01/08/2023]
Abstract
G-protein-coupled receptors (GPCRs) are divided phylogenetically into six classes1,2, denoted A to F. More than 370 structures of vertebrate GPCRs (belonging to classes A, B, C and F) have been determined, leading to a substantial understanding of their function3. By contrast, there are no structures of class D GPCRs, which are found exclusively in fungi where they regulate survival and reproduction. Here we determine the structure of a class D GPCR, the Saccharomyces cerevisiae pheromone receptor Ste2, in an active state coupled to the heterotrimeric G protein Gpa1-Ste4-Ste18. Ste2 was purified as a homodimer coupled to two G proteins. The dimer interface of Ste2 is formed by the N terminus, the transmembrane helices H1, H2 and H7, and the first extracellular loop ECL1. We establish a class D1 generic residue numbering system (CD1) to enable comparisons with orthologues and with other GPCR classes. The structure of Ste2 bears similarities in overall topology to class A GPCRs, but the transmembrane helix H4 is shifted by more than 20 Å and the G-protein-binding site is a shallow groove rather than a cleft. The structure provides a template for the design of novel drugs to target fungal GPCRs, which could be used to treat numerous intractable fungal diseases4.
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Affiliation(s)
| | - Ning Ma
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - Gáspár Pándy-Szekeres
- Department of Drug Design and Pharmacology, Universitetsparken 2, Copenhagen, Denmark.,Medicinal Chemistry Research Group, Research Center for Natural Sciences, Budapest, Hungary
| | - Albert J Kooistra
- Department of Drug Design and Pharmacology, Universitetsparken 2, Copenhagen, Denmark
| | - Yang Lee
- MRC Laboratory of Molecular Biology, Cambridge, UK
| | - David E Gloriam
- Department of Drug Design and Pharmacology, Universitetsparken 2, Copenhagen, Denmark
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA, USA
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31
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Lee J, Robinson ME, Ma N, Artadji D, Ahmed MA, Xiao G, Sadras T, Deb G, Winchester J, Cosgun KN, Geng H, Chan LN, Kume K, Miettinen TP, Zhang Y, Nix MA, Klemm L, Chen CW, Chen J, Khairnar V, Wiita AP, Thomas-Tikhonenko A, Farzan M, Jung JU, Weinstock DM, Manalis SR, Diamond MS, Vaidehi N, Müschen M. IFITM3 functions as a PIP3 scaffold to amplify PI3K signalling in B cells. Nature 2020; 588:491-497. [PMID: 33149299 PMCID: PMC8087162 DOI: 10.1038/s41586-020-2884-6] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2019] [Accepted: 08/13/2020] [Indexed: 12/25/2022]
Abstract
Interferon-induced transmembrane protein 3 (IFITM3) has previously been identified as an endosomal protein that blocks viral infection1-3. Here we studied clinical cohorts of patients with B cell leukaemia and lymphoma, and identified IFITM3 as a strong predictor of poor outcome. In normal resting B cells, IFITM3 was minimally expressed and mainly localized in endosomes. However, engagement of the B cell receptor (BCR) induced both expression of IFITM3 and phosphorylation of this protein at Tyr20, which resulted in the accumulation of IFITM3 at the cell surface. In B cell leukaemia, oncogenic kinases phosphorylate IFITM3 at Tyr20, which causes constitutive localization of this protein at the plasma membrane. In a mouse model, Ifitm3-/- naive B cells developed in normal numbers; however, the formation of germinal centres and the production of antigen-specific antibodies were compromised. Oncogenes that induce the development of leukaemia and lymphoma did not transform Ifitm3-/- B cells. Conversely, the phosphomimetic IFITM3(Y20E) mutant induced oncogenic PI3K signalling and initiated the transformation of premalignant B cells. Mechanistic experiments revealed that IFITM3 functions as a PIP3 scaffold and central amplifier of PI3K signalling. The amplification of PI3K signals depends on IFITM3 using two lysine residues (Lys83 and Lys104) in its conserved intracellular loop as a scaffold for the accumulation of PIP3. In Ifitm3-/- B cells, lipid rafts were depleted of PIP3, which resulted in the defective expression of over 60 lipid-raft-associated surface receptors, and impaired BCR signalling and cellular adhesion. We conclude that the phosphorylation of IFITM3 that occurs after B cells encounter antigen induces a dynamic switch from antiviral effector functions in endosomes to a PI3K amplification loop at the cell surface. IFITM3-dependent amplification of PI3K signalling, which in part acts downstream of the BCR, is critical for the rapid expansion of B cells with high affinity to antigen. In addition, multiple oncogenes depend on IFITM3 to assemble PIP3-dependent signalling complexes and amplify PI3K signalling for malignant transformation.
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Affiliation(s)
- Jaewoong Lee
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Mark E Robinson
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Ning Ma
- Department of Computational and Quantitative Medicine, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Dewan Artadji
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Mohamed A Ahmed
- Department of Systems Biology, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Gang Xiao
- Department of Systems Biology, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Teresa Sadras
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Gauri Deb
- Department of Systems Biology, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Janet Winchester
- Department of Systems Biology, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Kadriye Nehir Cosgun
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Huimin Geng
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Lai N Chan
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Kohei Kume
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Teemu P Miettinen
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.,Medical Research Council Laboratory for Molecular Cell Biology, University College London, London, UK
| | - Ye Zhang
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Matthew A Nix
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Lars Klemm
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Chun Wei Chen
- Department of Systems Biology, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Jianjun Chen
- Department of Systems Biology, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Vishal Khairnar
- Department of Systems Biology, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Arun P Wiita
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Andrei Thomas-Tikhonenko
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michael Farzan
- Department of Immunology and Microbiology, The Scripps Research Institute, Jupiter, FL, USA
| | - Jae U Jung
- Department of Cancer Biology, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - David M Weinstock
- Dana Farber Cancer Institute, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Scott R Manalis
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.,Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Michael S Diamond
- Department of Medicine, Washington University School of Medicine in St Louis, St Louis, MO, USA.,Department of Molecular Microbiology, Washington University School of Medicine in St Louis, St Louis, MO, USA.,Department of Pathology and Immunology, Washington University School of Medicine in St Louis, St Louis, MO, USA
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Markus Müschen
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA. .,Department of Immunobiology, Yale University, New Haven, CT, USA.
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32
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Abstract
Although multiple components of the cell membrane modulate the stability and activation of G protein-coupled receptors (GPCRs), insights into the dynamics of GPCR structures come from biophysical studies conducted in detergents. This is because of the challenges of studying activation in a multicomponent lipid bilayer. To understand the role of cellular membrane lipids and cations in GPCR activation, we performed multiscale molecular dynamics simulations (56 μs) on three different conformational states of adenosine receptor A2AR, in both the cell membrane-like lipid bilayer and in detergent micelles. Molecular dynamics (MD) simulations show that the phosphatidylinositol bisphosphate (PIP2) interacts with the basic residues in the intracellular regions of A2AR, thereby reducing the flexibility of the receptor in the inactive state and limiting the transition to the active-intermediate state. In the G protein-coupled fully active state, PIP2 stabilizes the GPCR:G protein complex. Such stiffening effects are absent in non-ionic detergent micelles, and therefore, more transitions have been observed in detergents. The inter-residue distances that change significantly upon GPCR activation are known as activation microswitches. The activation microswitches show different levels of activation in the cell membrane, in the pure POPC bilayer, and in detergents. Thus, the temporal heat map of different activation microswitches calculated from the MD simulations suggests a rheostat model of GPCR activation microswitches rather than the binary switch model. These simulation results connect the chemistry of cell membrane lipids to receptor activity, which is useful for the design of detergents mimicking the cell membrane.
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Affiliation(s)
- Ning Ma
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, 1500 E Duarte Road, Duarte, CA-91010
| | - Sangbae Lee
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, 1500 E Duarte Road, Duarte, CA-91010
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, 1500 E Duarte Road, Duarte, CA-91010
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33
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Hu W, Bhattacharya S, Hong T, Wong P, Li L, Vaidehi N, Kalkum M, Shively JE. Structural characterization of a dimeric complex between the short cytoplasmic domain of CEACAM1 and the pseudo tetramer of S100A10-Annexin A2 using NMR and molecular dynamics. Biochim Biophys Acta Biomembr 2020; 1863:183451. [PMID: 32835655 DOI: 10.1016/j.bbamem.2020.183451] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 08/09/2020] [Accepted: 08/19/2020] [Indexed: 12/14/2022]
Abstract
AIIt, a heterotetramer of S100A10 (P11) and Annexin A2, plays a key role in calcium dependent, membrane associations with a variety of proteins. We previously showed that AIIt interacts with the short cytoplasmic domain (12 amino acids) of CEACAM1 (CEACAM1-SF). Since the cytoplasmic domains of CEACAM1 help regulate the formation of cis- or trans-dimers at the cell membrane, we investigated the possible role of their association with AIIt in this process. Using NMR and molecular dynamics, we show that AIIt and its pseudoheterodimer interacts with two molecules of short cytoplasmic domain isoform peptides, and that interaction depends on the binding motif 454-Phe-Gly-Lys-Thr-457 where Phe-454 binds in a hydrophobic pocket of AIIt, the null mutation Phe454Ala reduces binding by 2.5 fold, and the pseudophosphorylation mutant Thr457Glu reduces binding by three fold. Since these two residues in CEACAM1-SF were also found to play a role in the binding of calmodulin and G-actin at the membrane, we hypothesize a sequential set of three interactions are responsible for regulation of cis- to trans-dimerization of CEACAM1. The hydrophobic binding pocket in AIIt corresponds to a previously identified binding pocket for a peptide found in SMARCA3 and AHNAK, suggesting a conserved functional motif in AIIt allowing multiple proteins to reversibly interact with integral membrane proteins in a calcium dependent manner.
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Affiliation(s)
- Weidong Hu
- Department of Molecular Imaging and Therapy, , Beckman Research Institute of City of Hope, 1450 East Duarte Road, Duarte, CA 91010, United States of America
| | - Supriyo Bhattacharya
- Department of Computational and Quantitative Medicine, Beckman Research Institute of City of Hope, 1450 East Duarte Road, Duarte, CA 91010, United States of America
| | - Teresa Hong
- Department of Molecular Imaging and Therapy, , Beckman Research Institute of City of Hope, 1450 East Duarte Road, Duarte, CA 91010, United States of America
| | - Patty Wong
- Department of Molecular Imaging and Therapy, , Beckman Research Institute of City of Hope, 1450 East Duarte Road, Duarte, CA 91010, United States of America
| | - Lin Li
- Department of Molecular Imaging and Therapy, , Beckman Research Institute of City of Hope, 1450 East Duarte Road, Duarte, CA 91010, United States of America
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of City of Hope, 1450 East Duarte Road, Duarte, CA 91010, United States of America
| | - Markus Kalkum
- Department of Molecular Imaging and Therapy, , Beckman Research Institute of City of Hope, 1450 East Duarte Road, Duarte, CA 91010, United States of America
| | - John E Shively
- Department of Molecular Imaging and Therapy, , Beckman Research Institute of City of Hope, 1450 East Duarte Road, Duarte, CA 91010, United States of America.
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34
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Abstract
![]()
The
structural and functional properties of G protein-coupled receptors
(GPCRs) are often studied in a detergent micellar environment, but
many GPCRs tend to denature or aggregate in short alkyl chain detergents.
In our previous work [Lee, S., et al. (2016) J. Am. Chem.
Soc.138, 15425–15433], we showed
that GPCRs in alkyl glucosides were highly dynamic, resulting in the
penetration of detergent molecules between transmembrane α-helices,
which is the initial step in receptor denaturation. Although this
was not observed for GPCRs in dodecyl maltoside (DDM, also known as
lauryl maltoside), even this detergent is not mild enough to preserve
the integrity of many GPCRs during purification. Lauryl maltose neopentylglycol
(LMNG) detergents have been found to have significant advantages for
purifying GPCRs in a native state as they impart more stability to
the receptor than DDM. To gain insights into how they stabilize GPCRs,
we used atomistic molecular dynamics simulations of wild type adenosine
A2A receptor (WT-A2AR), thermostabilized A2AR (tA2AR), and wild type β2-adrenoceptor
(β2AR) in a variety of detergents (LMNG, DMNG, OGNG,
and DDM). Analysis of molecular dynamics simulations of tA2AR in LMNG, DMNG, and OGNG showed that this series of detergents exhibited
behavior very similar to that of an analogous series of detergents
DDM, DM, and OG in our previous study. However, there was a striking
difference upon comparison of the behavior of LMNG to that of DDM.
LMNG showed considerably less motion than DDM, which resulted in the
enhanced density of the aliphatic chains around the hydrophobic regions
of the receptor and considerably more hydrogen bond formation between
the head groups. This contributed to enhanced interaction energies
between both detergent molecules and between the receptor and detergent,
explaining the enhanced stability of GPCRs purified in this detergent.
Branched detergents occlude between transmembrane helices and reduce
their flexibility. Our results provide a rational foundation to develop
detergent variants for stabilizing membrane proteins.
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Affiliation(s)
- Sangbae Lee
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, 1500 East Duarte Road, Duarte, California 91010, United States
| | - Soumadwip Ghosh
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, 1500 East Duarte Road, Duarte, California 91010, United States
| | - Suvamay Jana
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, 1500 East Duarte Road, Duarte, California 91010, United States
| | - Nathan Robertson
- Heptares Therapeutics Ltd., BioPark, Broadwater Road, Welwyn Garden City, AL7 3AX, U.K
| | - Christopher G Tate
- MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Francis Crick Avenue, Cambridge CB2 0QH, U.K
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, 1500 East Duarte Road, Duarte, California 91010, United States
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35
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Ikegami K, de March CA, Nagai MH, Ghosh S, Do M, Sharma R, Bruguera ES, Lu YE, Fukutani Y, Vaidehi N, Yohda M, Matsunami H. Structural instability and divergence from conserved residues underlie intracellular retention of mammalian odorant receptors. Proc Natl Acad Sci U S A 2020; 117:2957-2967. [PMID: 31974307 PMCID: PMC7022149 DOI: 10.1073/pnas.1915520117] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
Mammalian odorant receptors are a diverse and rapidly evolving set of G protein-coupled receptors expressed in olfactory cilia membranes. Most odorant receptors show little to no cell surface expression in nonolfactory cells due to endoplasmic reticulum retention, which has slowed down biochemical studies. Here we provide evidence that structural instability and divergence from conserved residues of individual odorant receptors underlie intracellular retention using a combination of large-scale screening of odorant receptors cell surface expression in heterologous cells, point mutations, structural modeling, and machine learning techniques. We demonstrate the importance of conserved residues by synthesizing consensus odorant receptors that show high levels of cell surface expression similar to conventional G protein-coupled receptors. Furthermore, we associate in silico structural instability with poor cell surface expression using molecular dynamics simulations. We propose an enhanced evolutionary capacitance of olfactory sensory neurons that enable the functional expression of odorant receptors with cryptic mutations.
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Affiliation(s)
- Kentaro Ikegami
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710
- Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, Tokyo 184-8588, Japan
| | - Claire A de March
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710
| | - Maira H Nagai
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710
- Department of Biochemistry, Universidade de Sao Paulo, Sao Paulo, 05508-000, Brazil
| | - Soumadwip Ghosh
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
| | - Matthew Do
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710
| | - Ruchira Sharma
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710
| | - Elise S Bruguera
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710
| | - Yueyang Eric Lu
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710
| | - Yosuke Fukutani
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710
- Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, Tokyo 184-8588, Japan
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
| | - Masafumi Yohda
- Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, Tokyo 184-8588, Japan
| | - Hiroaki Matsunami
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710;
- Department of Neurobiology, Duke Institute for Brain Sciences, Duke University, Durham, NC 27710
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36
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Muk S, Ghosh S, Achuthan S, Chen X, Yao X, Sandhu M, Griffor MC, Fennell KF, Che Y, Shanmugasundaram V, Qiu X, Tate CG, Vaidehi N. Machine Learning for Prioritization of Thermostabilizing Mutations for G-Protein Coupled Receptors. Biophys J 2019; 117:2228-2239. [PMID: 31703801 DOI: 10.1016/j.bpj.2019.10.023] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 10/11/2019] [Accepted: 10/17/2019] [Indexed: 01/01/2023] Open
Abstract
Although the three-dimensional structures of G-protein coupled receptors (GPCRs), the largest superfamily of drug targets, have enabled structure-based drug design, there are no structures available for 87% of GPCRs. This is due to the stiff challenge in purifying the inherently flexible GPCRs. Identifying thermostabilized mutant GPCRs via systematic alanine scanning mutations has been a successful strategy in stabilizing GPCRs, but it remains a daunting task for each GPCR. We developed a computational method that combines sequence-, structure-, and dynamics-based molecular properties of GPCRs that recapitulate GPCR stability, with four different machine learning methods to predict thermostable mutations ahead of experiments. This method has been trained on thermostability data for 1231 mutants, the largest publicly available data set. A blind prediction for thermostable mutations of the complement factor C5a receptor 1 retrieved 36% of the thermostable mutants in the top 50 prioritized mutants compared to 3% in the first 50 attempts using systematic alanine scanning.
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Affiliation(s)
- Sanychen Muk
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California
| | - Soumadwip Ghosh
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California
| | - Srisairam Achuthan
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California
| | | | - XiaoJie Yao
- Discovery Sciences, Pfizer, Groton, Connecticut
| | - Manbir Sandhu
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California
| | | | | | - Ye Che
- Discovery Sciences, Pfizer, Groton, Connecticut
| | | | - Xiayang Qiu
- Discovery Sciences, Pfizer, Groton, Connecticut
| | | | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California.
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Jana S, Ghosh S, Muk S, Levy B, Vaidehi N. Prediction of Conformation Specific Thermostabilizing Mutations for Class A G Protein-Coupled Receptors. J Chem Inf Model 2019; 59:3744-3754. [PMID: 31408606 DOI: 10.1021/acs.jcim.9b00175] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
G protein-coupled receptors (GPCRs) are highly flexible and prone to denaturation during protein extraction in detergents and purification. This poses a huge challenge to purify a conformationally homogeneous solution of GPCRs. Thermostabilizing mutations have been used widely to purify and obtain crystal structures of several GPCRs. However, identifying thermostabilizing mutations for GPCRs remains a tedious and expensive task as they are not transferable even among closely related GPCRs. Additionally, the mutations stabilizing one conformational state of a GPCR do not always stabilize other conformational state(s) of the same GPCR. Previously we developed a computational method, LiticonDesign, for rapid prediction of thermostabilizing mutations for a specific GPCR conformation. In this study, we have used LiticonDesign to predict thermostabilizing mutations for the agonist bound active-intermediate state of the human adenosine receptor (A2AR) using the structure of the inactive state of the same GPCR and vice versa. Our study shows that the thermostable mutation predictions using LiticonDesign, for an active-intermediate state of a GPCR (A2AR in our case), requires a homology model that is derived from an active/active-intermediate state GPCR structure as a template. Similarly, the homology models derived from inactive state GPCR conformations are better in predicting the thermostable mutations for the inactive state of A2AR. Overall, LiticonDesign method is not only efficient in predicting thermostabilizing mutations for a given GPCR sequence but also can recover conformation specific mutations for a state of interest, if a suitable starting structure of desired conformation is chosen.
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Affiliation(s)
- Suvamay Jana
- Department of Computation and Quantitative Medicine , Beckman Research Institute of the City of Hope , 1500 E. Duarte Road , Duarte , California 91010 , United States
| | - Soumadwip Ghosh
- Department of Computation and Quantitative Medicine , Beckman Research Institute of the City of Hope , 1500 E. Duarte Road , Duarte , California 91010 , United States
| | - Sanychen Muk
- Department of Computation and Quantitative Medicine , Beckman Research Institute of the City of Hope , 1500 E. Duarte Road , Duarte , California 91010 , United States
| | - Benjamin Levy
- Department of Computation and Quantitative Medicine , Beckman Research Institute of the City of Hope , 1500 E. Duarte Road , Duarte , California 91010 , United States
| | - Nagarajan Vaidehi
- Department of Computation and Quantitative Medicine , Beckman Research Institute of the City of Hope , 1500 E. Duarte Road , Duarte , California 91010 , United States
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Kujawski M, Li L, Bhattacharya S, Wong P, Lee WH, Williams L, Li H, Chea J, Poku K, Bowles N, Vaidehi N, Yazaki P, Shively JE. Generation of dual specific bivalent BiTEs (dbBIspecific T-cell engaging antibodies) for cellular immunotherapy. BMC Cancer 2019; 19:882. [PMID: 31488104 PMCID: PMC6727398 DOI: 10.1186/s12885-019-6056-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Accepted: 08/19/2019] [Indexed: 01/12/2023] Open
Abstract
Background Bispecific T-cell engaging antibodies (BiTES), comprising dual anti-CD3 and anti-tumor antigen scFv fragments, are important therapeutic agents for the treatment of cancer. The dual scFv construct for BiTES requires proper protein folding while their small molecular size leads to rapid kidney clearance. Methods An intact (150 kDa) anti-tumor antigen antibody to CEA was joined in high yield (ca. 30%) to intact (150 kDa) anti-murine and anti-human CD3 antibodies using hinge region specific Click chemistry to form dual-specific, bivalent BiTES (dbBiTES, 300 kDa). dbBiTEs were tested in vitro by EM, flow cytometry and cell cytoxicity and in vivo by PET tumor imaging and redirected T-cell therapy. Results The interlocked hinge regions are compatible with a structural model that fits the electron micrographs of 300 kDa particles. Compared to intact anti-CEA antibody, dbBiTES exhibit high in vitro cytotoxicity, high in vivo tumor targeting as demonstrated by PET imaging, and redirected dbBiTE coated T-cells (1 microgram/10 million cells) that kill CEA+ target cells in vivo in CEA transgenic mice. Conclusion dbBiTE redirected T-cell therapy is a promising, efficient approach for targeting and killing cancer cells. Electronic supplementary material The online version of this article (10.1186/s12885-019-6056-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Maciej Kujawski
- Department of Molecular Imaging and Therapy, Beckman Research Institute City of Hope, Duarte, CA, 91010, USA
| | - Lin Li
- Department of Molecular Imaging and Therapy, Beckman Research Institute City of Hope, Duarte, CA, 91010, USA
| | - Supriyo Bhattacharya
- Department of Computational and Quantitative Medicine, Beckman Research Institute City of Hope, Duarte, CA, 91010, USA
| | - Patty Wong
- Department of Molecular Imaging and Therapy, Beckman Research Institute City of Hope, Duarte, CA, 91010, USA
| | - Wen-Hui Lee
- Department of Molecular Imaging and Therapy, Beckman Research Institute City of Hope, Duarte, CA, 91010, USA
| | - Lindsay Williams
- Department of Molecular Imaging and Therapy, Beckman Research Institute City of Hope, Duarte, CA, 91010, USA
| | - Harry Li
- Department of Molecular Imaging and Therapy, Beckman Research Institute City of Hope, Duarte, CA, 91010, USA
| | - Junie Chea
- Radiopharmacy, Beckman Research Institute City of Hope, Duarte, CA, 91010, USA
| | - Kofi Poku
- Radiopharmacy, Beckman Research Institute City of Hope, Duarte, CA, 91010, USA
| | - Nicole Bowles
- Radiopharmacy, Beckman Research Institute City of Hope, Duarte, CA, 91010, USA
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute City of Hope, Duarte, CA, 91010, USA
| | - Paul Yazaki
- Department of Molecular Imaging and Therapy, Beckman Research Institute City of Hope, Duarte, CA, 91010, USA
| | - John E Shively
- Department of Molecular Imaging and Therapy, Beckman Research Institute City of Hope, Duarte, CA, 91010, USA.
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Sandhu M, Touma AM, Dysthe M, Sadler F, Sivaramakrishnan S, Vaidehi N. Conformational plasticity of the intracellular cavity of GPCR-G-protein complexes leads to G-protein promiscuity and selectivity. Proc Natl Acad Sci U S A 2019; 116:11956-11965. [PMID: 31138704 PMCID: PMC6575595 DOI: 10.1073/pnas.1820944116] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
While the dynamics of the intracellular surface in agonist-stimulated GPCRs is well studied, the impact of GPCR dynamics on G-protein selectivity remains unclear. Here, we combine molecular dynamics simulations with live-cell FRET and secondary messenger measurements, for 21 GPCR-G-protein combinations, to advance a dynamic model of the GPCR-G-protein interface. Our data show C terminus peptides of Gαs, Gαi, and Gαq proteins assume a small ensemble of unique orientations when coupled to their cognate GPCRs, similar to the variations observed in 3D structures of GPCR-G-protein complexes. The noncognate G proteins interface with latent intracellular GPCR cavities but dissociate due to weak and unstable interactions. Three predicted mutations in β2-adrenergic receptor stabilize binding of noncognate Gαq protein in its latent cavity, allowing promiscuous signaling through both Gαs and Gαq in a dose-dependent manner. This demonstrates that latent GPCR cavities can be evolved, by design or nature, to tune G-protein selectivity, giving insights to pluridimensional GPCR signaling.
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Affiliation(s)
- Manbir Sandhu
- Irell & Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, CA 91010
- Department of Computational & Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
| | - Anja M Touma
- Department of Genetics, Cell Biology, and Development, University of Minnesota, Twin Cities, Minneapolis, MN 55455
| | - Matthew Dysthe
- Department of Genetics, Cell Biology, and Development, University of Minnesota, Twin Cities, Minneapolis, MN 55455
| | - Fredrik Sadler
- Department of Genetics, Cell Biology, and Development, University of Minnesota, Twin Cities, Minneapolis, MN 55455
| | - Sivaraj Sivaramakrishnan
- Department of Genetics, Cell Biology, and Development, University of Minnesota, Twin Cities, Minneapolis, MN 55455
| | - Nagarajan Vaidehi
- Irell & Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, CA 91010;
- Department of Computational & Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, CA 91010
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40
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Jayathilake BS, Bhattacharya S, Vaidehi N, Narayanan SR. Efficient and Selective Electrochemically Driven Enzyme-Catalyzed Reduction of Carbon Dioxide to Formate using Formate Dehydrogenase and an Artificial Cofactor. Acc Chem Res 2019; 52:676-685. [PMID: 30741524 DOI: 10.1021/acs.accounts.8b00551] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Increasing levels of carbon dioxide in the atmosphere and the growing need for energy necessitate a shift toward reliance on renewable energy sources and the utilization of carbon dioxide. Thus, producing carbonaceous fuel by the electrochemical reduction of carbon dioxide has been very appealing. We have focused on addressing the principal challenges of poor selectivity and poor energy efficiency in the electrochemical reduction of carbon dioxide. We have demonstrated here a viable pathway for the efficient and continuous electrochemical reduction of CO2 to formate using the metal-independent enzyme type of formate dehydrogenase (FDH) derived from C andida boidinii yeast. This type of FDH is attractive because it is commercially produced. In natural metabolic processes, this type of metal-independent FDH oxidizes formate to carbon dioxide using NAD+ as a cofactor. We show that FDH can catalyze the reverse process to generate formate when the natural cofactor NADH is replaced with an artificial cofactor, the methyl viologen radical cation. The methyl viologen radical cation is generated in situ, electrochemically. Our approach relies on the special properties of methyl viologen as a "unidirectional" redox cofactor for the conversion of CO2 to formate. Methyl viologen (in the oxidized form) does not catalyze formate oxidation, while the methyl viologen radical cation is an effective cofactor for the reduction of carbon dioxide. Thus, although the thermodynamic driving force is favorable for the oxidized form of methyl viologen to oxidize formate to carbon dioxide, the kinetic factors are not favorable. Only the reverse reaction of carbon dioxide reduction to formate is kinetically viable with the cofactor, methyl viologen radical cation. Binding free energy calculated from atomistic molecular dynamics (MD) simulations consolidate our understanding of these special binding properties of the methyl viologen radical cation and its ability to facilitate the two-electron reduction of carbon dioxide to formate in metal-independent FDH. By carrying out the reactions in a novel three-compartment cell, we have demonstrated the continuous production of formate at high energy efficiency and yield. This cell configuration uses judiciously selected ion-exchange membranes to separate the reaction compartments to preserve the yields of the methyl viologen radical cation and formate. By the electroregeneration of the methyl viologen radical cation at -0.44 V versus the normal hydrogen electrode, we could produce formate at 20 mV negative to the reversible electrode potential for carbon dioxide reduction to formate. Our results are in sharp contrast to the large overpotentials of -800 to -1000 mV required on metal catalysts, vindicating the selectivity and kinetic facility provided by FDH. Formate yields as high as 97% ± 1% could be realized by avoiding the adventitious reoxidation of the methyl viologen radical cation by molecular oxygen. We anticipate that the insights from the electrochemical studies and the MD simulations to be useful in redesigning the metal-independent FDH and alternate artificial cofactors to achieve even higher rates of conversion.
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Affiliation(s)
- Buddhinie S. Jayathilake
- Loker Hydrocarbon Research Institute, Department of Chemistry, University of Southern California, Los Angeles, California 90089, United States
| | - Supriyo Bhattacharya
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, 1500 E. Duarte Road, Duarte, California 91010, United States
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, 1500 E. Duarte Road, Duarte, California 91010, United States
| | - S. R. Narayanan
- Loker Hydrocarbon Research Institute, Department of Chemistry, University of Southern California, Los Angeles, California 90089, United States
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Lee S, Nivedha AK, Tate CG, Vaidehi N. Dynamic Role of the G Protein in Stabilizing the Active State of the Adenosine A 2A Receptor. Structure 2019; 27:703-712.e3. [PMID: 30713025 PMCID: PMC6531377 DOI: 10.1016/j.str.2018.12.007] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2018] [Revised: 07/28/2018] [Accepted: 12/09/2018] [Indexed: 11/20/2022]
Abstract
Agonist binding in the extracellular region of the G protein-coupled adenosine A2A receptor increases its affinity to the G proteins in the intracellular region, and vice versa. The structural basis for this effect is not evident from the crystal structures of A2AR in various conformational states since it stems from the receptor dynamics. Using atomistic molecular dynamics simulations on four different conformational states of the adenosine A2A receptor, we observed that the agonists show decreased ligand mobility, lower entropy of the extracellular loops in the active-intermediate state compared with the inactive state. In contrast, the entropy of the intracellular region increases to prime the receptor for coupling the G protein. Coupling of the G protein to A2AR shrinks the agonist binding site, making tighter receptor agonist contacts with an increase in the strength of allosteric communication compared with the active-intermediate state. These insights provide a strong basis for structure-based ligand design studies. GPCR conformation dynamics reveals the forward and backward allosteric mechanism Agonist binding increases the entropy in the intracellular region of the GPCR G protein binding shrinks the receptor-ligand contacts in the extracellular region Increased allostery between G protein and agonist in the GPCR-G protein complex
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Affiliation(s)
- Sangbae Lee
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, 1500 E. Duarte Road, Duarte, CA 91010, USA
| | - Anita K Nivedha
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, 1500 E. Duarte Road, Duarte, CA 91010, USA
| | - Christopher G Tate
- MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Francis Crick Avenue, Cambridge CB2 0QH, UK
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, 1500 E. Duarte Road, Duarte, CA 91010, USA.
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Ghazarian H, Hu W, Mao A, Nguyen T, Vaidehi N, Sligar S, Shively JE. NMR analysis of free and lipid nanodisc anchored CEACAM1 membrane proximal peptides with Ca 2+/CaM. Biochim Biophys Acta Biomembr 2019; 1861:787-797. [PMID: 30639287 DOI: 10.1016/j.bbamem.2019.01.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Revised: 12/16/2018] [Accepted: 01/08/2019] [Indexed: 11/28/2022]
Abstract
CEACAM1, a homotypic transmembrane receptor with 12 or 72 amino acid cytosolic domain isoforms, is converted from inactive cis-dimers to active trans-dimers by calcium-calmodulin (Ca2+/CaM). Previously, the weak binding of Ca2+/CaM to the human 12 AA cytosolic domain was studied using C-terminal anchored peptides. We now show the binding of 15N labeled Phe-454 cytosolic domain peptides in solution or membrane anchored using NMR demonstrates a significant role for the lipid bilayer. Although binding is increased by the mutation Phe454Ala, this mutation was previously shown to abrogate actin binding. On the other hand, Ca2+/CaM binding is abrogated by phosphorylation of nearby Thr-457, a post-translation modification required for actin binding and subsequent in vitro lumen formation. Binding of Ca2+/CaM to a membrane proximal peptide from the long 72 AA cytosolic domain anchored to lipid nanodiscs was very weak compared to lipid free conditions, suggesting membrane specific effects between the two isoforms. NMR analysis of 15N labeled Ca2+/CaM with unlabeled peptides showed the C-lobe of Ca2+/CaM is involved in peptide interactions, and hydrophobic residues such as Met-109, Val-142 and Met-144 play important roles in binding peptide. This information was incorporated into transmembrane models of CEACAM1 binding to Ca2+/CaM. The lack of Ca2+/CaM binding to phosphorylated Thr-457, a residue we have previously shown to be phosphorylated by CaMK2D, also dependent on Ca2+/CaM, suggests stepwise binding of the cytosolic domain first to Ca2+/CaM and then to actin.
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Affiliation(s)
- Haike Ghazarian
- Department of Molecular Imaging and Therapy, Diabetes, Metabolism and Research Institute of City of Hope, 1450 East Duarte Road, Duarte, CA 91010, United States of America; City of Hope Irell and Manella Graduate School of Biological Sciences, 1450 East Duarte road, Duarte, CA 91010, United States of America
| | - Weidong Hu
- Department of Molecular Imaging and Therapy, Diabetes, Metabolism and Research Institute of City of Hope, 1450 East Duarte Road, Duarte, CA 91010, United States of America
| | - Allen Mao
- Department of Molecular Imaging and Therapy, Diabetes, Metabolism and Research Institute of City of Hope, 1450 East Duarte Road, Duarte, CA 91010, United States of America
| | - Tung Nguyen
- Department of Molecular Imaging and Therapy, Diabetes, Metabolism and Research Institute of City of Hope, 1450 East Duarte Road, Duarte, CA 91010, United States of America
| | - Nagarajan Vaidehi
- Department of Molecular Imaging and Therapy, Diabetes, Metabolism and Research Institute of City of Hope, 1450 East Duarte Road, Duarte, CA 91010, United States of America
| | - Stephen Sligar
- Department of Biochemistry, University of Illinois, Urbana, IL 61801, United States of America
| | - John E Shively
- Department of Molecular Imaging and Therapy, Diabetes, Metabolism and Research Institute of City of Hope, 1450 East Duarte Road, Duarte, CA 91010, United States of America.
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Ghosh S, Bierig T, Lee S, Jana S, Löhle A, Schnapp G, Tautermann CS, Vaidehi N. Engineering Salt Bridge Networks between Transmembrane Helices Confers Thermostability in G-Protein-Coupled Receptors. J Chem Theory Comput 2018; 14:6574-6585. [PMID: 30359017 DOI: 10.1021/acs.jctc.8b00602] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Introduction of specific point mutations has been an effective strategy in enhancing the thermostability of G-protein-coupled receptors (GPCRs). Our previous work showed that a specific residue position on transmembrane helix 6 (TM6) in class A GPCRs consistently yields thermostable mutants. The crystal structure of human chemokine receptor CCR5 also showed increased thermostability upon mutation of two positions, A233D6.33 and K303E7.59. With the goal of testing the transferability of these two thermostabilizing mutations in other chemokine receptors, we tested the mutations A237D6.33 and R307E7.59 in human CCR3 for thermostability and aggregation properties in detergent solution. Interestingly, the double mutant exhibited a 6-10-fold decrease in the aggregation propensity of the wild-type protein. This is in stark contrast to the two single mutants whose aggregation properties resemble the wild type (WT). Moreover, unlike in CCR5, the two single mutants separately showed no increase in thermostability compared to the wild-type CCR3, while the double-mutant A237D6.33/R307E7.59 confers an increase of 2.6 °C in the melting temperature compared to the WT. Extensive all-atom molecular dynamics (MD) simulations in detergent micelles show that a salt bridge network between transmembrane helices TM3, TM6, and TM7 that is absent in the two single mutants confers stability in the double mutant. The free energy surface of the double mutant shows conformational homogeneity compared to the single mutants. An annular n-dodecyl maltoside detergent layer packs tighter to the hydrophobic surface of the double-mutant CCR3 compared to the single mutants providing additional stability. The purification of other C-C chemokine receptors lacking such stabilizing residues may benefit from the incorporation of these two point mutations.
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Affiliation(s)
- Soumadwip Ghosh
- Department of Molecular Imaging and Therapy , Beckman Research Institute of the City of Hope , 1500 East Duarte Road , Duarte , California 91010 , United States
| | - Tobias Bierig
- Department of Medicinal Chemistry , Boehringer Ingelheim Pharma GmbH & Company KG , Birkendorfer Strasse 65 , D-88397 Biberach an der Riss , Germany
| | | | | | | | - Gisela Schnapp
- Department of Medicinal Chemistry , Boehringer Ingelheim Pharma GmbH & Company KG , Birkendorfer Strasse 65 , D-88397 Biberach an der Riss , Germany
| | - Christofer S Tautermann
- Department of Medicinal Chemistry , Boehringer Ingelheim Pharma GmbH & Company KG , Birkendorfer Strasse 65 , D-88397 Biberach an der Riss , Germany
| | - Nagarajan Vaidehi
- Department of Molecular Imaging and Therapy , Beckman Research Institute of the City of Hope , 1500 East Duarte Road , Duarte , California 91010 , United States
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Ma N, Lippert LG, Devamani T, Levy B, Lee S, Sandhu M, Vaidehi N, Sivaramakrishnan S. Bitopic Inhibition of ATP and Substrate Binding in Ser/Thr Kinases through a Conserved Allosteric Mechanism. Biochemistry 2018; 57:6387-6390. [PMID: 30339352 DOI: 10.1021/acs.biochem.8b00729] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Protein kinases achieve substrate selective phosphorylation through their conformational flexibility and dynamic interaction with the substrate. Designing substrate selective or kinase selective small molecule inhibitors remains a challenge because of a lack of understanding of the dynamic mechanism by which substrates are selected by the kinase. Using a combination of all-atom molecular dynamics simulations and FRET sensors, we have delineated an allosteric mechanism that results in interaction among the DFG motif, G-loop, and activation loop and structurally links the nucleotide and substrate binding interfaces in protein kinase Cα and three other Ser/Thr kinases. ATP-competitive staurosporine analogues engage this allosteric switch region located just outside the ATP binding site to displace substrate binding to varying degrees. These inhibitors function as bitopic ligands by occupying the ATP binding site and interacting with the allosteric switch region. The conserved mechanism identified in this study can be exploited to select and design bitopic inhibitors for kinases.
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Affiliation(s)
- Ning Ma
- Department of Computational and Quantitative Medicine , Beckman Research Institute of the City of Hope , Duarte , California 91010 , United States
| | - Lisa G Lippert
- Department of Genetics, Cell Biology, and Development , University of Minnesota , Minneapolis , Minnesota 55455 , United States
| | - Titu Devamani
- Department of Genetics, Cell Biology, and Development , University of Minnesota , Minneapolis , Minnesota 55455 , United States
| | - Benjamin Levy
- Department of Computational and Quantitative Medicine , Beckman Research Institute of the City of Hope , Duarte , California 91010 , United States
| | - Sangbae Lee
- Department of Computational and Quantitative Medicine , Beckman Research Institute of the City of Hope , Duarte , California 91010 , United States
| | - Manbir Sandhu
- Department of Computational and Quantitative Medicine , Beckman Research Institute of the City of Hope , Duarte , California 91010 , United States
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine , Beckman Research Institute of the City of Hope , Duarte , California 91010 , United States
| | - Sivaraj Sivaramakrishnan
- Department of Genetics, Cell Biology, and Development , University of Minnesota , Minneapolis , Minnesota 55455 , United States
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Tautermann CS, Binder F, Büttner FH, Eickmeier C, Fiegen D, Gross U, Grundl MA, Heilker R, Hobson S, Hoerer S, Luippold A, Mack V, Montel F, Peters S, Bhattacharya S, Vaidehi N, Schnapp G, Thamm S, Zeeb M. Allosteric Activation of Striatal-Enriched Protein Tyrosine Phosphatase (STEP, PTPN5) by a Fragment-like Molecule. J Med Chem 2018; 62:306-316. [PMID: 30207464 DOI: 10.1021/acs.jmedchem.8b00857] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Protein tyrosine phosphatase non-receptor type 5 (PTPN5, STEP) is a brain specific phosphatase that regulates synaptic function and plasticity by modulation of N-methyl-d-aspartate receptor (NMDAR) and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) trafficking. Dysregulation of STEP has been linked to neurodegenerative and neuropsychiatric diseases, highlighting this enzyme as an attractive therapeutic target for drug discovery. Selective targeting of STEP with small molecules has been hampered by high conservation of the active site among protein tyrosine phosphatases. We report the discovery of the first small molecule allosteric activator for STEP that binds to the phosphatase domain. Allosteric binding is confirmed by both X-ray and 15N NMR experiments, and specificity has been demonstrated by an enzymatic test cascade. Molecular dynamics simulations indicate stimulation of enzymatic activity by a long-range allosteric mechanism. To allow the scientific community to make use of this tool, we offer to provide the compound in the course of an open innovation initiative.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | - Supriyo Bhattacharya
- Department of Molecular Immunology , Beckman Research Institute of the City of Hope , 1500, E. Duarte Road , Duarte , California 91010 , United States
| | - Nagarajan Vaidehi
- Department of Molecular Immunology , Beckman Research Institute of the City of Hope , 1500, E. Duarte Road , Duarte , California 91010 , United States
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Bhargava R, Sandhu M, Muk S, Lee G, Vaidehi N, Stark JM. C-NHEJ without indels is robust and requires synergistic function of distinct XLF domains. Nat Commun 2018; 9:2484. [PMID: 29950655 PMCID: PMC6021437 DOI: 10.1038/s41467-018-04867-5] [Citation(s) in RCA: 62] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Accepted: 05/25/2018] [Indexed: 01/17/2023] Open
Abstract
To investigate the fidelity of canonical non-homologous end joining (C-NHEJ), we developed an assay to detect EJ between distal ends of two Cas9-induced chromosomal breaks that are joined without causing insertion/deletion mutations (indels). Here we find that such EJ requires several core C-NHEJ factors, including XLF. Using variants of this assay, we find that C-NHEJ is required for EJ events that use 1-2, but not ≥3, nucleotides of terminal microhomology. We also investigated XLF residues required for EJ without indels, finding that one of two binding domains is essential (L115 or C-terminal lysines that bind XRCC4 and KU/DNA, respectively), and that disruption of one of these domains sensitizes XLF to mutations that affect its dimer interface, which we examined with molecular dynamic simulations. Thus, C-NHEJ, including synergistic function of distinct XLF domains, is required for EJ of chromosomal breaks without indels.
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Affiliation(s)
- Ragini Bhargava
- Department of Cancer Genetics and Epigenetics, Beckman Research Institute of the City of Hope, 1500 E Duarte Rd., Duarte, CA, 91010, USA
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, 1500 E Duarte Rd., Duarte, CA, 91010, USA
| | - Manbir Sandhu
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, 1500 E Duarte Rd., Duarte, CA, 91010, USA
- Department of Molecular Immunology, Beckman Research Institute of the City of Hope, 1500 E Duarte Rd., Duarte, CA, 91010, USA
| | - Sanychen Muk
- Department of Molecular Immunology, Beckman Research Institute of the City of Hope, 1500 E Duarte Rd., Duarte, CA, 91010, USA
| | - Gabriella Lee
- Department of Cancer Genetics and Epigenetics, Beckman Research Institute of the City of Hope, 1500 E Duarte Rd., Duarte, CA, 91010, USA
| | - Nagarajan Vaidehi
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, 1500 E Duarte Rd., Duarte, CA, 91010, USA
- Department of Molecular Immunology, Beckman Research Institute of the City of Hope, 1500 E Duarte Rd., Duarte, CA, 91010, USA
| | - Jeremy M Stark
- Department of Cancer Genetics and Epigenetics, Beckman Research Institute of the City of Hope, 1500 E Duarte Rd., Duarte, CA, 91010, USA.
- Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, 1500 E Duarte Rd., Duarte, CA, 91010, USA.
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Vaidehi N, Muk S, Sandhu M, Achuthan S, Jana S, Bhattacharya S, Tate CG, Grisshammer R. Machine Learning Methods for Rapid Prediction of Thermostabilizing Mutants of G‐protein‐coupled receptors in Detergents. FASEB J 2018. [DOI: 10.1096/fasebj.2018.32.1_supplement.555.17] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Nagarajan Vaidehi
- Molecular ImmunologyBeckman Research Institute of the City of HopeDuarteCA
| | - Sanychen Muk
- Beckman Research Institute of the City of HopeDuarteCA
| | - Manbir Sandhu
- Beckman Research Institute of the City of HopeDuarteCA
| | - Srisairam Achuthan
- Division of Research InformaticsBeckman Research Institute of the City of HopeDuarteCA
| | - Suvamay Jana
- Beckman Research Institute of the City of HopeDuarteCA
| | | | - Christopher G. Tate
- Medical Research Council Laboratory of Molecular BiologyCambridgeUnited Kingdom
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ma N, Lee S, Devamani T, Sandhu M, Sommese R, Sivaramakrishnan S, Vaidehi N. The PKC inhibitor BimI functions as a bi‐topic ligand that toggles a conserved allosteric switch to drive potent kinase inhibition. FASEB J 2018. [DOI: 10.1096/fasebj.2018.32.1_supplement.662.16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- ning ma
- City of hope Beckman research instituteDuarteCA
| | - Sangbae Lee
- City of hope Beckman research instituteDuarteCA
| | | | | | - Ruth Sommese
- University of Minnesota Twin CitiesMinneapolisMN
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Sandhu M, Dysthe M, Sivaramakrishnan S, Vaidehi N. Molecular GPS: Receptor and G‐protein dynamics that drive selectivity in GPCRs. FASEB J 2018. [DOI: 10.1096/fasebj.2018.32.1_supplement.557.14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Manbir Sandhu
- Molecular ImmunologyBeckman Research Institute at City of HopeDuarteCA
| | - Matthew Dysthe
- Genetics, Cell Biology, and DevelopmentUniversity of Minnesota ‐ Twin CitiesMinneapolisMN
| | | | - Nagarajan Vaidehi
- Molecular ImmunologyBeckman Research Institute at City of HopeDuarteCA
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Lee S, Nivedha AK, Song H, Vaidehi N. Distinct Dynamics of Biased Agonists Bound AT1R. Biophys J 2018. [DOI: 10.1016/j.bpj.2017.11.1331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
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