1
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Rojas-Prats E, Martinez-Gonzalez L, Gil C, Ramírez D, Martinez A. Druggable cavities and allosteric modulators of the cell division cycle 7 (CDC7) kinase. J Enzyme Inhib Med Chem 2024; 39:2301767. [PMID: 38205514 PMCID: PMC10786434 DOI: 10.1080/14756366.2024.2301767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 12/18/2023] [Indexed: 01/12/2024] Open
Abstract
Cell division cycle 7 kinase (CDC7) has been found overexpressed in many cancer cell lines being also one of the kinases involved in the nuclear protein TDP-43 phosphorylation in vivo. Thus, inhibitors of CDC7 are emerging drug candidates for the treatment of oncological and neurodegenerative unmet diseases. All the known CDC7 inhibitors are ATP-competitives, lacking of selectivity enough for success in clinical trials. As allosteric sites are less conserved among kinase proteins, discovery of allosteric modulators of CDC7 is a great challenge and opportunity in this field.Using different computational approaches, we have here identified new druggable cavities on the human CDC7 structure and subsequently selective CDC7 inhibitors with allosteric modulation mainly targeting the pockets where the interaction between this kinase and its activator DBF4 takes place.
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Affiliation(s)
- Elisa Rojas-Prats
- Centro de Investigaciones Biológicas -Margarita Salas-CSIC, Madrid, Spain
| | - Loreto Martinez-Gonzalez
- Centro de Investigaciones Biológicas -Margarita Salas-CSIC, Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de 13 Salud Carlos III, Madrid, Spain
| | - Carmen Gil
- Centro de Investigaciones Biológicas -Margarita Salas-CSIC, Madrid, Spain
| | - David Ramírez
- Departamento de Farmacología, Facultad de Ciencias Biológicas, Universidad de Concepción, Concepción, Chile
| | - Ana Martinez
- Centro de Investigaciones Biológicas -Margarita Salas-CSIC, Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de 13 Salud Carlos III, Madrid, Spain
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2
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Nerín-Fonz F, Caprai C, Morales-Pastor A, Lopez-Balastegui M, Aranda-García D, Giorgino T, Selent J. AlloViz: A tool for the calculation and visualisation of protein allosteric communication networks. Comput Struct Biotechnol J 2024; 23:1938-1944. [PMID: 38736696 PMCID: PMC11087696 DOI: 10.1016/j.csbj.2024.04.047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 04/18/2024] [Accepted: 04/18/2024] [Indexed: 05/14/2024] Open
Abstract
Allostery, the presence of functional interactions between distant parts of proteins, is a critical concept in the field of biochemistry and molecular biology, particularly in the context of protein function and regulation. Understanding the principles of allosteric regulation is essential for advancing our knowledge of biology and developing new therapeutic strategies. This paper presents AlloViz, an open-source Python package designed to quantitatively determine, analyse, and visually represent allosteric communication networks on the basis of molecular dynamics (MD) simulation data. The software integrates well-known techniques for understanding allosteric properties simplifying the process of accessing, rationalising, and representing protein allostery and communication routes. It overcomes the inefficiency of having multiple methods with heterogeneous implementations and showcases the advantages of using MD simulations and multiple replicas to obtain statistically sound information on protein dynamics; it also enables the calculation of "consensus-like" scores aggregating methods that consider multiple structural aspects of allosteric networks. We demonstrate the features of AlloViz on two proteins: β-arrestin 1, a key player for regulating G protein-coupled receptor (GPCR) signalling, and the protein tyrosine phosphatase 1B, an important pharmaceutical target for allosteric inhibitors. The software includes comprehensive documentation and examples, tutorials, and a user-friendly graphical interface.
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Affiliation(s)
- Francho Nerín-Fonz
- Hospital del Mar Research Institute & Universitat Pompeu Fabra, C/ Dr. Aiguader 88, Barcelona, 08003, Spain
| | - Camilla Caprai
- Department of Biosciences, Università degli Studi di Milano, Via Celoria 26, Milan, 20133, Italy
- National Research Council of Italy, Biophysics Institute (CNR-IBF), Via Celoria 26, Milan, 20133, Italy
| | - Adrián Morales-Pastor
- Hospital del Mar Research Institute & Universitat Pompeu Fabra, C/ Dr. Aiguader 88, Barcelona, 08003, Spain
| | - Marta Lopez-Balastegui
- Hospital del Mar Research Institute & Universitat Pompeu Fabra, C/ Dr. Aiguader 88, Barcelona, 08003, Spain
| | - David Aranda-García
- Hospital del Mar Research Institute & Universitat Pompeu Fabra, C/ Dr. Aiguader 88, Barcelona, 08003, Spain
| | - Toni Giorgino
- National Research Council of Italy, Biophysics Institute (CNR-IBF), Via Celoria 26, Milan, 20133, Italy
| | - Jana Selent
- Hospital del Mar Research Institute & Universitat Pompeu Fabra, C/ Dr. Aiguader 88, Barcelona, 08003, Spain
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3
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Liu Z, Gillis TG, Raman S, Cui Q. A parameterized two-domain thermodynamic model explains diverse mutational effects on protein allostery. eLife 2024; 12:RP92262. [PMID: 38836839 PMCID: PMC11152574 DOI: 10.7554/elife.92262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2024] Open
Abstract
New experimental findings continue to challenge our understanding of protein allostery. Recent deep mutational scanning study showed that allosteric hotspots in the tetracycline repressor (TetR) and its homologous transcriptional factors are broadly distributed rather than spanning well-defined structural pathways as often assumed. Moreover, hotspot mutation-induced allostery loss was rescued by distributed additional mutations in a degenerate fashion. Here, we develop a two-domain thermodynamic model for TetR, which readily rationalizes these intriguing observations. The model accurately captures the in vivo activities of various mutants with changes in physically transparent parameters, allowing the data-based quantification of mutational effects using statistical inference. Our analysis reveals the intrinsic connection of intra- and inter-domain properties for allosteric regulation and illustrate epistatic interactions that are consistent with structural features of the protein. The insights gained from this study into the nature of two-domain allostery are expected to have broader implications for other multi-domain allosteric proteins.
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Affiliation(s)
- Zhuang Liu
- Department of Physics, Boston UniversityBostonUnited States
| | - Thomas G Gillis
- Department of Biochemistry, University of WisconsinMadisonUnited States
| | - Srivatsan Raman
- Department of Biochemistry, University of WisconsinMadisonUnited States
- Department of Chemistry, University of WisconsinMadisonUnited States
- Department of Bacteriology, University of WisconsinMadisonUnited States
| | - Qiang Cui
- Department of Physics, Boston UniversityBostonUnited States
- Department of Chemistry, Boston UniversityBostonUnited States
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4
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Gampp O, Kadavath H, Riek R. NMR tools to detect protein allostery. Curr Opin Struct Biol 2024; 86:102792. [PMID: 38428364 DOI: 10.1016/j.sbi.2024.102792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 02/06/2024] [Accepted: 02/14/2024] [Indexed: 03/03/2024]
Abstract
Allostery is a fundamental mechanism of cellular homeostasis by intra-protein communication between distinct functional sites. It is an internal process of proteins to steer interactions not only with each other but also with other biomolecules such as ligands, lipids, and nucleic acids. In addition, allosteric regulation is particularly important in enzymatic activities. A major challenge in structural and molecular biology today is unraveling allosteric sites in proteins, to elucidate the detailed mechanism of allostery and the development of allosteric drugs. Here we summarize the recently developed tools and approaches which enable the elucidation of regulatory hotspots and correlated motion in biomolecules, focusing primarily on solution-state nuclear magnetic resonance spectroscopy (NMR). These tools open an avenue towards a rational understanding of the mechanism of allostery and provide essential information for the design of allosteric drugs.
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Affiliation(s)
- Olivia Gampp
- Laboratory of Physical Chemistry, ETH Zurich, Switzerland
| | - Harindranath Kadavath
- Laboratory of Physical Chemistry, ETH Zurich, Switzerland; St. Jude Children's Research Hospital, 262 Danny Thomas Place, 38105 Memphis, Tennessee, USA. https://twitter.com/harijik
| | - Roland Riek
- Laboratory of Physical Chemistry, ETH Zurich, Switzerland.
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5
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Lefèbre J, Falk T, Ning Y, Rademacher C. Secondary Sites of the C-type Lectin-Like Fold. Chemistry 2024; 30:e202400660. [PMID: 38527187 DOI: 10.1002/chem.202400660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Revised: 03/23/2024] [Accepted: 03/25/2024] [Indexed: 03/27/2024]
Abstract
C-type lectins are a large superfamily of proteins involved in a multitude of biological processes. In particular, their involvement in immunity and homeostasis has rendered them attractive targets for diverse therapeutic interventions. They share a characteristic C-type lectin-like domain whose adaptability enables them to bind a broad spectrum of ligands beyond the originally defined canonical Ca2+-dependent carbohydrate binding. Together with variable domain architecture and high-level conformational plasticity, this enables C-type lectins to meet diverse functional demands. Secondary sites provide another layer of regulation and are often intricately linked to functional diversity. Located remote from the canonical primary binding site, secondary sites can accommodate ligands with other physicochemical properties and alter protein dynamics, thus enhancing selectivity and enabling fine-tuning of the biological response. In this review, we outline the structural determinants allowing C-type lectins to perform a large variety of tasks and to accommodate the ligands associated with it. Using the six well-characterized Ca2+-dependent and Ca2+-independent C-type lectin receptors DC-SIGN, langerin, MGL, dectin-1, CLEC-2 and NKG2D as examples, we focus on the characteristics of non-canonical interactions and secondary sites and their potential use in drug discovery endeavors.
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Affiliation(s)
- Jonathan Lefèbre
- Department of Pharmaceutical Sciences, University of Vienna, Vienna, Austria
- Vienna Doctoral School of Pharmaceutical, Nutritional and Sport, Sciences, University of Vienna, Vienna, Austria
- Department of Microbiology, Immunology and Genetics, University of Vienna, Max F. Perutz Labs, Vienna, Austria
| | - Torben Falk
- Department of Pharmaceutical Sciences, University of Vienna, Vienna, Austria
- Vienna Doctoral School of Pharmaceutical, Nutritional and Sport, Sciences, University of Vienna, Vienna, Austria
- Department of Microbiology, Immunology and Genetics, University of Vienna, Max F. Perutz Labs, Vienna, Austria
| | - Yunzhan Ning
- Department of Pharmaceutical Sciences, University of Vienna, Vienna, Austria
- Vienna Doctoral School of Pharmaceutical, Nutritional and Sport, Sciences, University of Vienna, Vienna, Austria
- Department of Microbiology, Immunology and Genetics, University of Vienna, Max F. Perutz Labs, Vienna, Austria
| | - Christoph Rademacher
- Department of Pharmaceutical Sciences, University of Vienna, Vienna, Austria
- Department of Microbiology, Immunology and Genetics, University of Vienna, Max F. Perutz Labs, Vienna, Austria
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6
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Evans D, Sheraz S, Lau A. SARS-CoV-2 3CLPro Dihedral Angles Reveal Allosteric Signaling. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.22.595309. [PMID: 38826232 PMCID: PMC11142162 DOI: 10.1101/2024.05.22.595309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
In allosteric proteins, identifying the pathways that signals take from allosteric ligand-binding sites to enzyme active sites or binding pockets and interfaces remains challenging. This avenue of research is motivated by the goals of understanding particular macromolecular systems of interest and creating general methods for their study. An especially important protein that is the subject of many investigations in allostery is the SARS-CoV-2 main protease (Mpro), which is necessary for coronaviral replication. It is both an attractive drug target and, due to intense interest in it for the development of pharmaceutical compounds, a gauge of the state-of-the-art approaches in studying protein inhibition. Here we develop a computational method for characterizing protein allostery and use it to study Mpro. We propose a role of the protein's C-terminal tail in allosteric modulation and warn of unintuitive traps that can plague studies of the role of protein dihedrals angles in transmitting allosteric signals.
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Affiliation(s)
- Daniel Evans
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, United States
| | - Samreen Sheraz
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, United States
| | - Albert Lau
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, United States
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7
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Scrima S, Lambrughi M, Tiberti M, Fadda E, Papaleo E. ASM variants in the spotlight: A structure-based atlas for unraveling pathogenic mechanisms in lysosomal acid sphingomyelinase. Biochim Biophys Acta Mol Basis Dis 2024:167260. [PMID: 38782304 DOI: 10.1016/j.bbadis.2024.167260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 04/30/2024] [Accepted: 05/18/2024] [Indexed: 05/25/2024]
Abstract
Lysosomal acid sphingomyelinase (ASM), a critical enzyme in lipid metabolism encoded by the SMPD1 gene, plays a crucial role in sphingomyelin hydrolysis in lysosomes. ASM deficiency leads to acid sphingomyelinase deficiency, a rare genetic disorder with diverse clinical manifestations, and the protein can be found mutated in other diseases. We employed a structure-based framework to comprehensively understand the functional implications of ASM variants, integrating pathogenicity predictions with molecular insights derived from a molecular dynamics simulation in a lysosomal membrane environment. Our analysis, encompassing over 400 variants, establishes a structural atlas of missense variants of lysosomal ASM, associating mechanistic indicators with pathogenic potential. Our study highlights variants that influence structural stability or exert local and long-range effects at functional sites. To validate our predictions, we compared them to available experimental data on residual catalytic activity in 135 ASM variants. Notably, our findings also suggest applications of the resulting data for identifying cases suited for enzyme replacement therapy. This comprehensive approach enhances the understanding of ASM variants and provides valuable insights for potential therapeutic interventions.
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Affiliation(s)
- Simone Scrima
- Cancer Structural Biology, Danish Cancer Institute, 2100 Copenhagen, Denmark; Cancer Systems Biology, Section for Bioinformatics, Department of Health and Technology, Technical University of Denmark, 2800 Lyngby, Denmark
| | - Matteo Lambrughi
- Cancer Structural Biology, Danish Cancer Institute, 2100 Copenhagen, Denmark
| | - Matteo Tiberti
- Cancer Structural Biology, Danish Cancer Institute, 2100 Copenhagen, Denmark
| | - Elisa Fadda
- Department of Chemistry and Hamilton Institute, Maynooth University, Maynooth, co. Kildare, Ireland
| | - Elena Papaleo
- Cancer Structural Biology, Danish Cancer Institute, 2100 Copenhagen, Denmark; Cancer Systems Biology, Section for Bioinformatics, Department of Health and Technology, Technical University of Denmark, 2800 Lyngby, Denmark.
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8
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Muzquiz R, Jamshidi C, Conroy DW, Jaroniec CP, Foster MP. Insights into Ligand-Mediated Activation of an Oligomeric Ring-Shaped Gene-Regulatory Protein from Solution- and Solid-State NMR. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.10.593404. [PMID: 38798368 PMCID: PMC11118279 DOI: 10.1101/2024.05.10.593404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
The 91 kDa oligomeric ring-shaped ligand binding protein TRAP (trp RNA binding attenuation protein) regulates the expression of a series of genes involved in tryptophan (Trp) biosynthesis in bacilli. When cellular Trp levels rise, the free amino acid binds to sites buried in the interfaces between each of the 11 (or 12, depending on the species) protomers in the ring. Crystal structures of Trp-bound TRAP show the Trp ligands are sequestered from solvent by a pair of loops from adjacent protomers that bury the bound ligand via polar contacts to several threonine residues. Binding of the Trp ligands occurs cooperatively, such that successive binding events occur with higher apparent affinity but the structural basis for this cooperativity is poorly understood. We used solution methyl-TROSY NMR relaxation experiments focused on threonine and isoleucine sidechains, as well as magic angle spinning solid-state NMR 13C-13C and 15N-13C chemical shift correlation spectra on uniformly labeled samples recorded at 800 and 1200 MHz, to characterize the structure and dynamics of the protein. Methyl 13C relaxation dispersion experiments on ligand-free apo TRAP revealed concerted exchange dynamics on the μs-ms time scale, consistent with transient sampling of conformations that could allow ligand binding. Cross-correlated relaxation experiments revealed widespread disorder on fast timescales. Chemical shifts for methyl-bearing side chains in apo- and Trp-bound TRAP revealed subtle changes in the distribution of sampled sidechain rotameric states. These observations reveal a pathway and mechanism for induced conformational changes to generate homotropic Trp-Trp binding cooperativity.
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Affiliation(s)
- Rodrigo Muzquiz
- Ohio State Biochemistry Graduate Program, The Ohio State University, 484 West 12 Avenue, Columbus, OH 43210, USA
- Department of Chemistry and Biochemistry, The Ohio State University, 100 West 18 Avenue, Columbus, OH 43210, USA
| | - Cameron Jamshidi
- Ohio State Biochemistry Graduate Program, The Ohio State University, 484 West 12 Avenue, Columbus, OH 43210, USA
- Department of Chemistry and Biochemistry, The Ohio State University, 100 West 18 Avenue, Columbus, OH 43210, USA
| | - Daniel W. Conroy
- Department of Chemistry and Biochemistry, The Ohio State University, 100 West 18 Avenue, Columbus, OH 43210, USA
| | - Christopher P. Jaroniec
- Ohio State Biochemistry Graduate Program, The Ohio State University, 484 West 12 Avenue, Columbus, OH 43210, USA
- Department of Chemistry and Biochemistry, The Ohio State University, 100 West 18 Avenue, Columbus, OH 43210, USA
| | - Mark P. Foster
- Ohio State Biochemistry Graduate Program, The Ohio State University, 484 West 12 Avenue, Columbus, OH 43210, USA
- Department of Chemistry and Biochemistry, The Ohio State University, 100 West 18 Avenue, Columbus, OH 43210, USA
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9
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Csizi KS, Reiher M. Automated preparation of nanoscopic structures: Graph-based sequence analysis, mismatch detection, and pH-consistent protonation with uncertainty estimates. J Comput Chem 2024; 45:761-776. [PMID: 38124290 DOI: 10.1002/jcc.27276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Accepted: 11/14/2023] [Indexed: 12/23/2023]
Abstract
Structure and function in nanoscale atomistic assemblies are tightly coupled, and every atom with its specific position and even every electron will have a decisive effect on the electronic structure, and hence, on the molecular properties. Molecular simulations of nanoscopic atomistic structures therefore require accurately resolved three-dimensional input structures. If extracted from experiment, these structures often suffer from severe uncertainties, of which the lack of information on hydrogen atoms is a prominent example. Hence, experimental structures require careful review and curation, which is a time-consuming and error-prone process. Here, we present a fast and robust protocol for the automated structure analysis and pH-consistent protonation, in short, ASAP. For biomolecules as a target, the ASAP protocol integrates sequence analysis and error assessment of a given input structure. ASAP allows for pK a prediction from reference data through Gaussian process regression including uncertainty estimation and connects to system-focused atomistic modeling described in Brunken and Reiher (J. Chem. Theory Comput. 16, 2020, 1646). Although focused on biomolecules, ASAP can be extended to other nanoscopic objects, because most of its design elements rely on a general graph-based foundation guaranteeing transferability. The modular character of the underlying pipeline supports different degrees of automation, which allows for (i) efficient feedback loops for human-machine interaction with a low entrance barrier and for (ii) integration into autonomous procedures such as automated force field parametrizations. This facilitates fast switching of the pH-state through on-the-fly system-focused reparametrization during a molecular simulation at virtually no extra computational cost.
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Affiliation(s)
- Katja-Sophia Csizi
- Department of Chemistry and Applied Biosciences, ETH Zurich, Zurich, Switzerland
| | - Markus Reiher
- Department of Chemistry and Applied Biosciences, ETH Zurich, Zurich, Switzerland
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10
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Bian H, Shao X, Cai W, Fu H. Understanding the Reversible Binding of a Multichain Protein-Protein Complex through Free-Energy Calculations. J Phys Chem B 2024; 128:3598-3604. [PMID: 38574232 DOI: 10.1021/acs.jpcb.4c00519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/06/2024]
Abstract
We demonstrate that the binding affinity of a multichain protein-protein complex, insulin dimer, can be accurately predicted using a streamlined route of standard binding free-energy calculations. We find that chains A and C, which do not interact directly during binding, stabilize the insulin monomer structures and reduce the binding affinity of the two monomers, therefore enabling their reversible association. Notably, we confirm that although classical methods can estimate the binding affinity of the insulin dimer, conventional molecular dynamics, enhanced sampling algorithms, and classical geometrical routes of binding free-energy calculations may not fully capture certain aspects of the role played by the noninteracting chains in the binding dynamics. Therefore, this study not only elucidates the role of noninteracting chains in the reversible binding of the insulin dimer but also offers a methodological guide for investigating the reversible binding of multichain protein-protein complexes utilizing streamlined free-energy calculations.
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Affiliation(s)
- Hengwei Bian
- Research Center for Analytical Sciences, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, College of Chemistry, Nankai University, Tianjin 300071, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| | - Xueguang Shao
- Research Center for Analytical Sciences, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, College of Chemistry, Nankai University, Tianjin 300071, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
- School of Materials Science and Engineering, Smart Sensing Interdisciplinary Science Center, Nankai University, Tianjin 300350, China
| | - Wensheng Cai
- Research Center for Analytical Sciences, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, College of Chemistry, Nankai University, Tianjin 300071, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
- School of Materials Science and Engineering, Smart Sensing Interdisciplinary Science Center, Nankai University, Tianjin 300350, China
| | - Haohao Fu
- Research Center for Analytical Sciences, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, College of Chemistry, Nankai University, Tianjin 300071, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
- School of Materials Science and Engineering, Smart Sensing Interdisciplinary Science Center, Nankai University, Tianjin 300350, China
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11
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Giladi M, Fojtík L, Strauss T, Da'adoosh B, Hiller R, Man P, Khananshvili D. Structural dynamics of Na + and Ca 2+ interactions with full-size mammalian NCX. Commun Biol 2024; 7:463. [PMID: 38627576 PMCID: PMC11021524 DOI: 10.1038/s42003-024-06159-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2023] [Accepted: 04/05/2024] [Indexed: 04/19/2024] Open
Abstract
Cytosolic Ca2+ and Na+ allosterically regulate Na+/Ca2+ exchanger (NCX) proteins to vary the NCX-mediated Ca2+ entry/exit rates in diverse cell types. To resolve the structure-based dynamic mechanisms underlying the ion-dependent allosteric regulation in mammalian NCXs, we analyze the apo, Ca2+, and Na+-bound species of the brain NCX1.4 variant using hydrogen-deuterium exchange mass spectrometry (HDX-MS) and molecular dynamics (MD) simulations. Ca2+ binding to the cytosolic regulatory domains (CBD1 and CBD2) rigidifies the intracellular regulatory loop (5L6) and promotes its interaction with the membrane domains. Either Na+ or Ca2+ stabilizes the intracellular portions of transmembrane helices TM3, TM4, TM9, TM10, and their connecting loops (3L4 and 9L10), thereby exposing previously unappreciated regulatory sites. Ca2+ or Na+ also rigidifies the palmitoylation domain (TMH2), and neighboring TM1/TM6 bundle, thereby uncovering a structural entity for modulating the ion transport rates. The present analysis provides new structure-dynamic clues underlying the regulatory diversity among tissue-specific NCX variants.
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Affiliation(s)
- Moshe Giladi
- Department of Physiology and Pharmacology, Faculty of Medicine, Tel-Aviv University, Tel Aviv, 69978, Israel.
- Tel-Aviv Sourasky Medical Center, Tel Aviv, 6423906, Israel.
| | - Lukáš Fojtík
- Division BioCeV, Institute of Microbiology of the Czech Academy of Sciences, Prumyslova, 595, 252 50 Vestec, Prague, Czech Republic
- Department of Biochemistry, Faculty of Science, Charles University, 128 00, Prague, Czech Republic
| | - Tali Strauss
- Department of Physiology and Pharmacology, Faculty of Medicine, Tel-Aviv University, Tel Aviv, 69978, Israel
| | - Benny Da'adoosh
- Blavatnik Center for Drug Discovery, Tel Aviv University, Tel Aviv, 69978, Israel
| | - Reuben Hiller
- Department of Physiology and Pharmacology, Faculty of Medicine, Tel-Aviv University, Tel Aviv, 69978, Israel
| | - Petr Man
- Division BioCeV, Institute of Microbiology of the Czech Academy of Sciences, Prumyslova, 595, 252 50 Vestec, Prague, Czech Republic.
- Department of Biochemistry, Faculty of Science, Charles University, 128 00, Prague, Czech Republic.
| | - Daniel Khananshvili
- Department of Physiology and Pharmacology, Faculty of Medicine, Tel-Aviv University, Tel Aviv, 69978, Israel.
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12
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Nerín-Fonz F, Cournia Z. Machine learning approaches in predicting allosteric sites. Curr Opin Struct Biol 2024; 85:102774. [PMID: 38354652 DOI: 10.1016/j.sbi.2024.102774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Revised: 12/29/2023] [Accepted: 01/02/2024] [Indexed: 02/16/2024]
Abstract
Allosteric regulation is a fundamental biological mechanism that can control critical cellular processes via allosteric modulator binding to protein distal functional sites. The advantages of allosteric modulators over orthosteric ones have sparked the development of numerous computational approaches, such as the identification of allosteric binding sites, to facilitate allosteric drug discovery. Building on the success of machine learning (ML) models for solving complex problems in biology and chemistry, several ML models for predicting allosteric sites have been developed. In this review, we provide an overview of these models and discuss future perspectives powered by the field of artificial intelligence such as protein language models.
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Affiliation(s)
- Francho Nerín-Fonz
- Biomedical Research Foundation, Academy of Athens, 4 Soranou Ephesiou, Athens 11527, Greece; Vienna Doctoral School of Pharmaceutical, Nutritional and Sport Sciences, University of Vienna, Josef-Holaubek-Platz 2, 1090 Vienna, Austria.
| | - Zoe Cournia
- Biomedical Research Foundation, Academy of Athens, 4 Soranou Ephesiou, Athens 11527, Greece; Vienna Doctoral School of Pharmaceutical, Nutritional and Sport Sciences, University of Vienna, Josef-Holaubek-Platz 2, 1090 Vienna, Austria.
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13
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Skeens E, Sinha S, Ahsan M, D’Ordine AM, Jogl G, Palermo G, Lisi GP. High-fidelity, hyper-accurate, and evolved mutants rewire atomic-level communication in CRISPR-Cas9. SCIENCE ADVANCES 2024; 10:eadl1045. [PMID: 38446895 PMCID: PMC10917355 DOI: 10.1126/sciadv.adl1045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 01/29/2024] [Indexed: 03/08/2024]
Abstract
The high-fidelity (HF1), hyper-accurate (Hypa), and evolved (Evo) variants of the CRISPR-associated protein 9 (Cas9) endonuclease are critical tools to mitigate off-target effects in the application of CRISPR-Cas9 technology. The mechanisms by which mutations in recognition subdomain 3 (Rec3) mediate specificity in these variants are poorly understood. Here, solution nuclear magnetic resonance and molecular dynamics simulations establish the structural and dynamic effects of high-specificity mutations in Rec3, and how they propagate the allosteric signal of Cas9. We reveal conserved structural changes and dynamic differences at regions of Rec3 that interface with the RNA:DNA hybrid, transducing chemical signals from Rec3 to the catalytic His-Asn-His (HNH) domain. The variants remodel the communication sourcing from the Rec3 α helix 37, previously shown to sense target DNA complementarity, either directly or allosterically. This mechanism increases communication between the DNA mismatch recognition helix and the HNH active site, shedding light on the structure and dynamics underlying Cas9 specificity and providing insight for future engineering principles.
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Affiliation(s)
- Erin Skeens
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, USA
| | - Souvik Sinha
- Department of Bioengineering, University of California, Riverside, Riverside, CA, USA
| | - Mohd Ahsan
- Department of Bioengineering, University of California, Riverside, Riverside, CA, USA
| | - Alexandra M. D’Ordine
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, USA
| | - Gerwald Jogl
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, USA
| | - Giulia Palermo
- Department of Bioengineering, University of California, Riverside, Riverside, CA, USA
- Department of Chemistry, University of California, Riverside, Riverside, CA, USA
| | - George P. Lisi
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI, USA
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14
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Dorbath E, Gulzar A, Stock G. Log-periodic oscillations as real-time signatures of hierarchical dynamics in proteins. J Chem Phys 2024; 160:074103. [PMID: 38364004 DOI: 10.1063/5.0188220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 01/23/2024] [Indexed: 02/18/2024] Open
Abstract
The time-dependent relaxation of a dynamical system may exhibit a power-law behavior that is superimposed by log-periodic oscillations. D. Sornette [Phys. Rep. 297, 239 (1998)] showed that this behavior can be explained by a discrete scale invariance of the system, which is associated with discrete and equidistant timescales on a logarithmic scale. Examples include such diverse fields as financial crashes, random diffusion, and quantum topological materials. Recent time-resolved experiments and molecular dynamics simulations suggest that discrete scale invariance may also apply to hierarchical dynamics in proteins, where several fast local conformational changes are a prerequisite for a slow global transition to occur. Employing entropy-based timescale analysis and Markov state modeling to a simple one-dimensional hierarchical model and biomolecular simulation data, it is found that hierarchical systems quite generally give rise to logarithmically spaced discrete timescales. By introducing a one-dimensional reaction coordinate that collectively accounts for the hierarchically coupled degrees of freedom, the free energy landscape exhibits a characteristic staircase shape with two metastable end states, which causes the log-periodic time evolution of the system. The period of the log-oscillations reflects the effective roughness of the energy landscape and can, in simple cases, be interpreted in terms of the barriers of the staircase landscape.
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Affiliation(s)
- Emanuel Dorbath
- Biomolecular Dynamics, Institute of Physics, University of Freiburg, 79104 Freiburg, Germany
| | - Adnan Gulzar
- Biomolecular Dynamics, Institute of Physics, University of Freiburg, 79104 Freiburg, Germany
| | - Gerhard Stock
- Biomolecular Dynamics, Institute of Physics, University of Freiburg, 79104 Freiburg, Germany
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15
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Kannan A, Chaurasiya DK, Naganathan AN. Conflicting Interfacial Electrostatic Interactions as a Design Principle to Modulate Long-Range Interdomain Communication. ACS BIO & MED CHEM AU 2024; 4:53-67. [PMID: 38404745 PMCID: PMC10885104 DOI: 10.1021/acsbiomedchemau.3c00047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 10/19/2023] [Accepted: 10/23/2023] [Indexed: 02/27/2024]
Abstract
The extent and molecular basis of interdomain communication in multidomain proteins, central to understanding allostery and function, is an open question. One simple evolutionary strategy could involve the selection of either conflicting or favorable electrostatic interactions across the interface of two closely spaced domains to tune the magnitude of interdomain connectivity. Here, we study a bilobed domain FF34 from the eukaryotic p190A RhoGAP protein to explore one such design principle that mediates interdomain communication. We find that while the individual structural units in wild-type FF34 are marginally coupled, they exhibit distinct intrinsic stabilities and low cooperativity, manifesting as slow folding. The FF3-FF4 interface harbors a frustrated network of highly conserved electrostatic interactions-a charge troika-that promotes the population of multiple, decoupled, and non-native structural modes on a rugged native landscape. Perturbing this network via a charge-reversal mutation not only enhances stability and cooperativity but also dampens the fluctuations globally and speeds up the folding rate by at least an order of magnitude. Our work highlights how a conserved but nonoptimal network of interfacial electrostatic interactions shapes the native ensemble of a bilobed protein, a feature that could be exploited in designing molecular systems with long-range connectivity and enhanced cooperativity.
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Affiliation(s)
- Adithi Kannan
- Department of Biotechnology,
Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, India
| | - Dhruv Kumar Chaurasiya
- Department of Biotechnology,
Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, India
| | - Athi N. Naganathan
- Department of Biotechnology,
Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, India
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16
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Liu Z, Gillis T, Raman S, Cui Q. A parametrized two-domain thermodynamic model explains diverse mutational effects on protein allostery. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.08.06.552196. [PMID: 37662419 PMCID: PMC10473640 DOI: 10.1101/2023.08.06.552196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
New experimental findings continue to challenge our understanding of protein allostery. Recent deep mutational scanning study showed that allosteric hotspots in the tetracycline repressor (TetR) and its homologous transcriptional factors are broadly distributed rather than spanning well-defined structural pathways as often assumed. Moreover, hotspot mutation-induced allostery loss was rescued by distributed additional mutations in a degenerate fashion. Here, we develop a two-domain thermodynamic model for TetR, which readily rationalizes these intriguing observations. The model accurately captures the in vivo activities of various mutants with changes in physically transparent parameters, allowing the data-based quantification of mutational effects using statistical inference. Our analysis reveals the intrinsic connection of intra- and inter-domain properties for allosteric regulation and illustrate epistatic interactions that are consistent with structural features of the protein. The insights gained from this study into the nature of two-domain allostery are expected to have broader implications for other multidomain allosteric proteins.
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Affiliation(s)
- Zhuang Liu
- Department of Physics, Boston University, Boston, United States
| | - Thomas Gillis
- Department of Biochemistry, University of Wisconsin, Madison, United States
| | - Srivatsan Raman
- Department of Biochemistry, University of Wisconsin, Madison, United States
- Department of Chemistry, University of Wisconsin, Madison, United States
- Department of Bacteriology, University of Wisconsin, Madison, United States
| | - Qiang Cui
- Department of Physics, Boston University, Boston, United States
- Department of Chemistry, Boston University, Boston, United States
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17
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Acuto O. T-cell virtuosity in ''knowing thyself". Front Immunol 2024; 15:1343575. [PMID: 38415261 PMCID: PMC10896960 DOI: 10.3389/fimmu.2024.1343575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 01/17/2024] [Indexed: 02/29/2024] Open
Abstract
Major Histocompatibility Complex (MHC) I and II and the αβ T-cell antigen receptor (TCRαβ) govern fundamental traits of adaptive immunity. They form a membrane-borne ligand-receptor system weighing host proteome integrity to detect contamination by nonself proteins. MHC-I and -II exhibit the "MHC-fold", which is able to bind a large assortment of short peptides as proxies for self and nonself proteins. The ensuing varying surfaces are mandatory ligands for Ig-like TCRαβ highly mutable binding sites. Conserved molecular signatures guide TCRαβ ligand binding sites to focus on the MHC-fold (MHC-restriction) while leaving many opportunities for its most hypervariable determinants to contact the peptide. This riveting molecular strategy affords many options for binding energy compatible with specific recognition and signalling aimed to eradicated microbial pathogens and cancer cells. While the molecular foundations of αβ T-cell adaptive immunity are largely understood, uncertainty persists on how peptide-MHC binding induces the TCRαβ signals that instruct cell-fate decisions. Solving this mystery is another milestone for understanding αβ T-cells' self/nonself discrimination. Recent developments revealing the innermost links between TCRαβ structural dynamics and signalling modality should help dissipate this long-sought-after enigma.
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Affiliation(s)
- Oreste Acuto
- Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
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18
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Astore MA, Pradhan AS, Thiede EH, Hanson SM. Protein dynamics underlying allosteric regulation. Curr Opin Struct Biol 2024; 84:102768. [PMID: 38215528 DOI: 10.1016/j.sbi.2023.102768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 12/16/2023] [Accepted: 12/18/2023] [Indexed: 01/14/2024]
Abstract
Allostery is the mechanism by which information and control are propagated in biomolecules. It regulates ligand binding, chemical reactions, and conformational changes. An increasing level of experimental resolution and control over allosteric mechanisms promises a deeper understanding of the molecular basis for life and powerful new therapeutics. In this review, we survey the literature for an up-to-date biological and theoretical understanding of protein allostery. By delineating five ways in which the energy landscape or the kinetics of a system may change to give rise to allostery, we aim to help the reader grasp its physical origins. To illustrate this framework, we examine three systems that display these forms of allostery: allosteric inhibitors of beta-lactamases, thermosensation of TRP channels, and the role of kinetic allostery in the function of kinases. Finally, we summarize the growing power of computational tools available to investigate the different forms of allostery presented in this review.
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Affiliation(s)
- Miro A Astore
- Center for Computational Biology, Flatiron Institute, New York, NY, USA; Center for Computational Mathematics, Flatiron Institute, New York, NY, USA. https://twitter.com/@miroastore
| | - Akshada S Pradhan
- Center for Computational Biology, Flatiron Institute, New York, NY, USA
| | - Erik H Thiede
- Center for Computational Biology, Flatiron Institute, New York, NY, USA; Center for Computational Mathematics, Flatiron Institute, New York, NY, USA; Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, USA
| | - Sonya M Hanson
- Center for Computational Biology, Flatiron Institute, New York, NY, USA; Center for Computational Mathematics, Flatiron Institute, New York, NY, USA.
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19
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Stern M, Liu AJ, Balasubramanian V. Physical effects of learning. Phys Rev E 2024; 109:024311. [PMID: 38491658 DOI: 10.1103/physreve.109.024311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 01/31/2024] [Indexed: 03/18/2024]
Abstract
Interacting many-body physical systems ranging from neural networks in the brain to folding proteins to self-modifying electrical circuits can learn to perform diverse tasks. This learning, both in nature and in engineered systems, can occur through evolutionary selection or through dynamical rules that drive active learning from experience. Here, we show that learning in linear physical networks with weak input signals leaves architectural imprints on the Hessian of a physical system. Compared to a generic organization of the system components, (a) the effective physical dimension of the response to inputs decreases, (b) the response of physical degrees of freedom to random perturbations (or system "susceptibility") increases, and (c) the low-eigenvalue eigenvectors of the Hessian align with the task. Overall, these effects embody the typical scenario for learning processes in physical systems in the weak input regime, suggesting ways of discovering whether a physical network may have been trained.
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Affiliation(s)
- Menachem Stern
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Andrea J Liu
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, New York 10010, USA
| | - Vijay Balasubramanian
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
- Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, New Mexico 87501, USA
- Theoretische Natuurkunde, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium
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20
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Guner-Yılmaz OZ, Kurkcuoglu O, Akten ED. Tunnel-like region observed as a potential allosteric site in Staphylococcus aureus Glyceraldehyde-3-phosphate dehydrogenase. Arch Biochem Biophys 2024; 752:109875. [PMID: 38158117 DOI: 10.1016/j.abb.2023.109875] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 12/14/2023] [Accepted: 12/17/2023] [Indexed: 01/03/2024]
Abstract
Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) catalyzing the sixth step of glycolysis has been investigated for allosteric features that might be used as potential target for specific inhibition of Staphylococcus aureus (S.aureus). X-ray structure of bacterial enzyme for which a tunnel-like opening passing through the center previously proposed as an allosteric site has been subjected to six independent 500 ns long Molecular Dynamics simulations. Harmonic bond restraints were employed at key residues to underline the allosteric feature of this region. A noticeable reduction was observed in the mobility of NAD+ binding domains when restrictions were applied. Also, a substantial decrease in cross-correlations between distant Cα fluctuations was detected throughout the structure. Mutual information (MI) analysis revealed a similar decrease in the degree of correspondence in positional fluctuations in all directions everywhere in the receptor. MI between backbone and side-chain torsional variations changed its distribution profile and decreased considerably around the catalytic sites when restraints were employed. Principal component analysis clearly showed that the restrained state sampled a narrower range of conformations than apo state, especially in the first principal mode due to restriction in the conformational flexibility of NAD+ binding domain. Clustering the trajectory based on catalytic site residues displayed a smaller repertoire of conformations for restrained state compared to apo. Representative snapshots subjected to k-shortest pathway analysis revealed the impact of bond restraints on the allosteric communication which displayed distinct optimal and suboptimal pathways for two states, where observed frequencies of critical residues Gln51 and Val283 at the proposed site changed considerably.
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Affiliation(s)
| | - Ozge Kurkcuoglu
- Department of Chemical Engineering, Istanbul Technical University, Istanbul, Turkey
| | - Ebru Demet Akten
- Department of Molecular Biology and Genetics, Faculty of Engineering and Natural Sciences, Kadir Has University, Istanbul, Turkey.
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21
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Deng J, Yuan Y, Cui Q. Modulation of Allostery with Multiple Mechanisms by Hotspot Mutations in TetR. J Am Chem Soc 2024; 146:2757-2768. [PMID: 38231868 PMCID: PMC10843641 DOI: 10.1021/jacs.3c12494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Modulating allosteric coupling offers unique opportunities for biomedical applications. Such efforts can benefit from efficient prediction and evaluation of allostery hotspot residues that dictate the degree of cooperativity between distant sites. We demonstrate that effects of allostery hotspot mutations can be evaluated qualitatively and semiquantitatively by molecular dynamics simulations in a bacterial tetracycline repressor (TetR). The simulations recapitulate the effects of these mutations on abolishing the induction function of TetR and provide a rationale for the different rescuabilities observed to restore allosteric coupling of the hotspot mutations. We demonstrate that the same noninducible phenotype could be the result of perturbations in distinct structural and energetic properties of TetR. Our work underscores the value of explicitly computing the functional free energy landscapes to effectively evaluate and rank hotspot mutations despite the prevalence of compensatory interactions and therefore provides quantitative guidance to allostery modulation for therapeutic and engineering applications.
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Affiliation(s)
- Jiahua Deng
- Department of Chemistry, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
| | - Yuchen Yuan
- Department of Chemistry, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
| | - Qiang Cui
- Department of Chemistry, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
- Department of Physics, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, Massachusetts 02215, United States
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22
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Kish M, Ivory DP, Phillips JJ. Transient Structural Dynamics of Glycogen Phosphorylase from Nonequilibrium Hydrogen/Deuterium-Exchange Mass Spectrometry. J Am Chem Soc 2024; 146:298-307. [PMID: 38158228 PMCID: PMC10786028 DOI: 10.1021/jacs.3c08934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 12/12/2023] [Accepted: 12/13/2023] [Indexed: 01/03/2024]
Abstract
It remains a major challenge to ascertain the specific structurally dynamic changes that underpin protein functional switching. There is a growing need in molecular biology and drug discovery to complement structural models with the ability to determine the dynamic structural changes that occur as these proteins are regulated and function. The archetypal allosteric enzyme glycogen phosphorylase is a clinical target of great interest to treat type II diabetes and metastatic cancers. Here, we developed a time-resolved nonequilibrium millisecond hydrogen/deuterium-exchange mass spectrometry (HDX-MS) approach capable of precisely locating dynamic structural changes during allosteric activation and inhibition of glycogen phosphorylase. We resolved obligate transient changes in the localized structure that are absent when directly comparing active/inactive states of the enzyme and show that they are common to allosteric activation by AMP and inhibition by caffeine, operating at different sites. This indicates that opposing allosteric regulation by inhibitor and activator ligands is mediated by pathways that intersect with a common structurally dynamic motif. This mass spectrometry approach uniquely stands to discover local transient structural dynamics and could be used broadly to identify features that influence the structural transitions of proteins.
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Affiliation(s)
- Monika Kish
- Living
Systems Institute, Department of Biosciences, University of Exeter, Stocker Road, Exeter EX4
4QD, U.K.
| | - Dylan P. Ivory
- Living
Systems Institute, Department of Biosciences, University of Exeter, Stocker Road, Exeter EX4
4QD, U.K.
| | - Jonathan J. Phillips
- Living
Systems Institute, Department of Biosciences, University of Exeter, Stocker Road, Exeter EX4
4QD, U.K.
- Alan
Turing Institute, British Library, London NW1 2DB, U.K.
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23
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Hunt NT. Biomolecular infrared spectroscopy: making time for dynamics. Chem Sci 2024; 15:414-430. [PMID: 38179520 PMCID: PMC10763549 DOI: 10.1039/d3sc05223k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 11/24/2023] [Indexed: 01/06/2024] Open
Abstract
Time resolved infrared spectroscopy of biological molecules has provided a wealth of information relating to structural dynamics, conformational changes, solvation and intermolecular interactions. Challenges still exist however arising from the wide range of timescales over which biological processes occur, stretching from picoseconds to minutes or hours. Experimental methods are often limited by vibrational lifetimes of probe groups, which are typically on the order of picoseconds, while measuring an evolving system continuously over some 18 orders of magnitude in time presents a raft of technological hurdles. In this Perspective, a series of recent advances which allow biological molecules and processes to be studied over an increasing range of timescales, while maintaining ultrafast time resolution, will be reviewed, showing that the potential for real-time observation of biomolecular function draws ever closer, while offering a new set of challenges to be overcome.
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Affiliation(s)
- Neil T Hunt
- Department of Chemistry and York Biomedical Research Institute, University of York Heslington York YO10 5DD UK
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24
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Buda K, Miton CM, Tokuriki N. Pervasive epistasis exposes intramolecular networks in adaptive enzyme evolution. Nat Commun 2023; 14:8508. [PMID: 38129396 PMCID: PMC10739712 DOI: 10.1038/s41467-023-44333-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Accepted: 12/08/2023] [Indexed: 12/23/2023] Open
Abstract
Enzyme evolution is characterized by constant alterations of the intramolecular residue networks supporting their functions. The rewiring of these network interactions can give rise to epistasis. As mutations accumulate, the epistasis observed across diverse genotypes may appear idiosyncratic, that is, exhibit unique effects in different genetic backgrounds. Here, we unveil a quantitative picture of the prevalence and patterns of epistasis in enzyme evolution by analyzing 41 fitness landscapes generated from seven enzymes. We show that >94% of all mutational and epistatic effects appear highly idiosyncratic, which greatly distorted the functional prediction of the evolved enzymes. By examining seemingly idiosyncratic changes in epistasis along adaptive trajectories, we expose several instances of higher-order, intramolecular rewiring. Using complementary structural data, we outline putative molecular mechanisms explaining higher-order epistasis along two enzyme trajectories. Our work emphasizes the prevalence of epistasis and provides an approach to exploring this phenomenon through a molecular lens.
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Affiliation(s)
- Karol Buda
- Michael Smith Laboratories, University of British Columbia, Vancouver, Canada
| | - Charlotte M Miton
- Michael Smith Laboratories, University of British Columbia, Vancouver, Canada
| | - Nobuhiko Tokuriki
- Michael Smith Laboratories, University of British Columbia, Vancouver, Canada.
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25
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Ersoy A, Altintel B, Livnat Levanon N, Ben-Tal N, Haliloglu T, Lewinson O. Computational analysis of long-range allosteric communications in CFTR. eLife 2023; 12:RP88659. [PMID: 38109179 PMCID: PMC10727502 DOI: 10.7554/elife.88659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2023] Open
Abstract
Malfunction of the CFTR protein results in cystic fibrosis, one of the most common hereditary diseases. CFTR functions as an anion channel, the gating of which is controlled by long-range allosteric communications. Allostery also has direct bearings on CF treatment: the most effective CFTR drugs modulate its activity allosterically. Herein, we integrated Gaussian network model, transfer entropy, and anisotropic normal mode-Langevin dynamics and investigated the allosteric communications network of CFTR. The results are in remarkable agreement with experimental observations and mutational analysis and provide extensive novel insight. We identified residues that serve as pivotal allosteric sources and transducers, many of which correspond to disease-causing mutations. We find that in the ATP-free form, dynamic fluctuations of the residues that comprise the ATP-binding sites facilitate the initial binding of the nucleotide. Subsequent binding of ATP then brings to the fore and focuses on dynamic fluctuations that were present in a latent and diffuse form in the absence of ATP. We demonstrate that drugs that potentiate CFTR's conductance do so not by directly acting on the gating residues, but rather by mimicking the allosteric signal sent by the ATP-binding sites. We have also uncovered a previously undiscovered allosteric 'hotspot' located proximal to the docking site of the phosphorylated regulatory (R) domain, thereby establishing a molecular foundation for its phosphorylation-dependent excitatory role. This study unveils the molecular underpinnings of allosteric connectivity within CFTR and highlights a novel allosteric 'hotspot' that could serve as a promising target for the development of novel therapeutic interventions.
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Affiliation(s)
- Ayca Ersoy
- Department of Chemical Engineering, Bogazici UniversityIstanbulTurkey
- Polymer Research Center, Bogazici UniversityIstanbulTurkey
| | - Bengi Altintel
- Department of Chemical Engineering, Bogazici UniversityIstanbulTurkey
- Polymer Research Center, Bogazici UniversityIstanbulTurkey
| | - Nurit Livnat Levanon
- Department of Molecular Microbiology, Bruce and Ruth Rappaport Faculty of Medicine, Technion-Israel Institute of TechnologyTel AvivIsrael
| | - Nir Ben-Tal
- Department of Biochemistry and Molecular Biology, Faculty of Life Sciences, Tel-Aviv UniversityTel-AvivIsrael
| | - Turkan Haliloglu
- Department of Chemical Engineering, Bogazici UniversityIstanbulTurkey
- Polymer Research Center, Bogazici UniversityIstanbulTurkey
| | - Oded Lewinson
- Department of Molecular Microbiology, Bruce and Ruth Rappaport Faculty of Medicine, Technion-Israel Institute of TechnologyTel AvivIsrael
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26
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Deng J, Yuan Y, Cui Q. Modulation of Allostery with Multiple Mechanisms by Hotspot Mutations in TetR. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.29.555381. [PMID: 37905112 PMCID: PMC10614727 DOI: 10.1101/2023.08.29.555381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Modulating allosteric coupling offers unique opportunities for biomedical applications. Such efforts can benefit from efficient prediction and evaluation of allostery hotspot residues that dictate the degree of co-operativity between distant sites. We demonstrate that effects of allostery hotspot mutations can be evaluated qualitatively and semi-quantitatively by molecular dynamics simulations in a bacterial tetracycline repressor (TetR). The simulations recapitulate the effects of these mutations on abolishing the induction function of TetR and provide a rationale for the different degrees of rescuability observed to restore allosteric coupling of the hotspot mutations. We demonstrate that the same non-inducible phenotype could be the result of perturbations in distinct structural and energetic properties of TetR. Our work underscore the value of explicitly computing the functional free energy landscapes to effectively evaluate and rank hotspot mutations despite the prevalence of compensatory interactions, and therefore provide quantitative guidance to allostery modulation for therapeutic and engineering applications.
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Affiliation(s)
- Jiahua Deng
- Department of Chemistry, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
| | - Yuchen Yuan
- Department of Chemistry, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
| | - Qiang Cui
- Department of Chemistry, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
- Department of Physics, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, Massachusetts 02215, United States
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27
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Segers M, Voorspoels A, Sakaue T, Carlon E. Mechanisms of DNA-Mediated Allostery. PHYSICAL REVIEW LETTERS 2023; 131:238402. [PMID: 38134780 DOI: 10.1103/physrevlett.131.238402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 11/07/2023] [Indexed: 12/24/2023]
Abstract
Proteins often regulate their activities via allostery-or action at a distance-in which the binding of a ligand at one binding site influences the affinity for another ligand at a distal site. Although less studied than in proteins, allosteric effects have been observed in experiments with DNA as well. In these experiments two or more proteins bind at distinct DNA sites and interact indirectly with each other, via a mechanism mediated by the linker DNA molecule. We develop a mechanical model of DNA/protein interactions which predicts three distinct mechanisms of allostery. Two of these involve an enthalpy-mediated allostery, while a third mechanism is entropy driven. We analyze experiments of DNA allostery and highlight the distinctive signatures allowing one to identify which of the proposed mechanisms best fits the data.
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Affiliation(s)
- Midas Segers
- Soft Matter and Biophysics, KU Leuven, Celestijnenlaan 200D, 3001 Leuven, Belgium
| | - Aderik Voorspoels
- Soft Matter and Biophysics, KU Leuven, Celestijnenlaan 200D, 3001 Leuven, Belgium
| | - Takahiro Sakaue
- Department of Physical Sciences, Aoyama Gakuin University, 5-10-1 Fuchinobe, Chuo-ku, Sagamihara, Kanagawa 252-5258, Japan
| | - Enrico Carlon
- Soft Matter and Biophysics, KU Leuven, Celestijnenlaan 200D, 3001 Leuven, Belgium
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Sohmen B, Beck C, Frank V, Seydel T, Hoffmann I, Hermann B, Nüesch M, Grimaldo M, Schreiber F, Wolf S, Roosen‐Runge F, Hugel T. The Onset of Molecule-Spanning Dynamics in Heat Shock Protein Hsp90. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2304262. [PMID: 37984887 PMCID: PMC10754087 DOI: 10.1002/advs.202304262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 10/06/2023] [Indexed: 11/22/2023]
Abstract
Protein dynamics have been investigated on a wide range of time scales. Nano- and picosecond dynamics have been assigned to local fluctuations, while slower dynamics have been attributed to larger conformational changes. However, it is largely unknown how fast (local) fluctuations can lead to slow global (allosteric) changes. Here, fast molecule-spanning dynamics on the 100 to 200 ns time scale in the heat shock protein 90 (Hsp90) are shown. Global real-space movements are assigned to dynamic modes on this time scale, which is possible by a combination of single-molecule fluorescence, quasi-elastic neutron scattering and all-atom molecular dynamics (MD) simulations. The time scale of these dynamic modes depends on the conformational state of the Hsp90 dimer. In addition, the dynamic modes are affected to various degrees by Sba1, a co-chaperone of Hsp90, depending on the location within Hsp90, which is in very good agreement with MD simulations. Altogether, this data is best described by fast molecule-spanning dynamics, which precede larger conformational changes in Hsp90 and might be the molecular basis for allostery. This integrative approach provides comprehensive insights into molecule-spanning dynamics on the nanosecond time scale for a multi-domain protein.
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Affiliation(s)
- Benedikt Sohmen
- Institute of Physical ChemistryUniversity of FreiburgAlbertstrasse 2179104FreiburgGermany
| | - Christian Beck
- Institute of Applied PhysicsUniversity of TübingenAuf der Morgenstelle 1072076TübingenGermany
- Science DivisionInstitut Max von Laue ‐ Paul Langevin71 avenue des MartyrsGrenoble38042France
| | - Veronika Frank
- Institute of Physical ChemistryUniversity of FreiburgAlbertstrasse 2179104FreiburgGermany
| | - Tilo Seydel
- Science DivisionInstitut Max von Laue ‐ Paul Langevin71 avenue des MartyrsGrenoble38042France
| | - Ingo Hoffmann
- Science DivisionInstitut Max von Laue ‐ Paul Langevin71 avenue des MartyrsGrenoble38042France
| | - Bianca Hermann
- Institute of Physical ChemistryUniversity of FreiburgAlbertstrasse 2179104FreiburgGermany
| | - Mark Nüesch
- Department of BiochemistryUniversity of ZurichWinterthurerstrasse 190CH‐8057ZurichSwitzerland
| | - Marco Grimaldo
- Science DivisionInstitut Max von Laue ‐ Paul Langevin71 avenue des MartyrsGrenoble38042France
| | - Frank Schreiber
- Institute of Applied PhysicsUniversity of TübingenAuf der Morgenstelle 1072076TübingenGermany
| | - Steffen Wolf
- Biomolecular Dynamics, Institute of PhysicsUniversity of FreiburgHermann‐Herder‐Strasse 379104FreiburgGermany
| | - Felix Roosen‐Runge
- Department of Biomedical Sciences and Biofilms‐Research Center for Biointerfaces (BRCB)Malmö University20506MalmöSweden
- Division of Physical ChemistryLund UniversityNaturvetarvägen 1422100LundSweden
| | - Thorsten Hugel
- Institute of Physical ChemistryUniversity of FreiburgAlbertstrasse 2179104FreiburgGermany
- Signalling Research Centers BIOSS and CIBSSUniversity of FreiburgSchänzlestrasse 1879104FreiburgGermany
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Roy M, Horovitz A. Distinguishing between concerted, sequential and barrierless conformational changes: Folding versus allostery. Curr Opin Struct Biol 2023; 83:102721. [PMID: 37922762 DOI: 10.1016/j.sbi.2023.102721] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 09/26/2023] [Indexed: 11/07/2023]
Abstract
Characterization of transition and intermediate states of reactions provides insights into their mechanisms and is often achieved through analysis of linear free energy relationships. Such an approach has been used extensively in protein folding studies but less so for analyzing allosteric transitions. Here, we point out analogies in ways to characterize pathways and intermediates in folding and allosteric transitions. Achieving an understanding of the mechanisms by which proteins undergo allosteric switching is important in many cases for obtaining insights into how they function.
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Affiliation(s)
- Mousam Roy
- Department of Chemical and Structural Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Amnon Horovitz
- Department of Chemical and Structural Biology, Weizmann Institute of Science, Rehovot 7610001, Israel.
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30
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Raza SHA, Zhong R, Yu X, Zhao G, Wei X, Lei H. Advances of Predicting Allosteric Mechanisms Through Protein Contact in New Technologies and Their Application. Mol Biotechnol 2023:10.1007/s12033-023-00951-4. [PMID: 37957479 DOI: 10.1007/s12033-023-00951-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 10/12/2023] [Indexed: 11/15/2023]
Abstract
Allostery is an intriguing phenomenon wherein the binding activity of a biological macromolecule is modulated via non-canonical binding site, resulting in synchronized functional changes. The mechanics underlying allostery are relatively complex and this review is focused on common methodologies used to study allostery, such as X-ray crystallography, NMR spectroscopy, and HDXMS. Different methodological approaches are used to generate data in different scenarios. For example, X-ray crystallography provides high-resolution structural information, NMR spectroscopy offers dynamic insights into allosteric interactions in solution, and HDXMS provides information on protein dynamics. The residue transition state (RTS) approach has emerged as a critical tool in understanding the energetics and conformational changes associated with allosteric regulation. Allostery has significant implications in drug discovery, gene transcription, disease diagnosis, and enzyme catalysis. Enzymes' catalytic activity can be modulated by allosteric regulation, offering opportunities to develop novel therapeutic alternatives. Understanding allosteric mechanisms associated with infectious organisms like SARS-CoV and bacterial pathogens can aid in the development of new antiviral drugs and antibiotics. Allosteric mechanisms are crucial in the regulation of a variety of signal transduction and cell metabolism pathways, which in turn govern various cellular processes. Despite progress, challenges remain in identifying allosteric sites and characterizing their contribution to a variety of biological processes. Increased understanding of these mechanisms can help develop allosteric systems specifically designed to modulate key biological mechanisms, providing novel opportunities for the development of targeted therapeutics. Therefore, the current review aims to summarize common methodologies that are used to further our understanding of allosteric mechanisms. In conclusion, this review provides insights into the methodologies used for the study of allostery, its applications in in silico modeling, the mechanisms underlying antibody allostery, and the ongoing challenges and prospects in advancing our comprehension of this intriguing phenomenon.
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Affiliation(s)
- Sayed Haidar Abbas Raza
- Guangdong Provincial Key Laboratory of Food Quality and Safety/Nation-Local Joint Engineering Research Center for Machining and Safety of Livestock and Poultry Products, South China Agricultural University, Guangzhou, 510642, China
- Guangdong Provincial Key Laboratory of Utilization and Conservation of Food and Medicinal Resources in Northern Region, Shaoguan University, Shaoguan, 512005, China
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Ruimin Zhong
- Guangdong Provincial Key Laboratory of Utilization and Conservation of Food and Medicinal Resources in Northern Region, Shaoguan University, Shaoguan, 512005, China
| | - Xiaoting Yu
- Guangdong Provincial Key Laboratory of Food Quality and Safety/Nation-Local Joint Engineering Research Center for Machining and Safety of Livestock and Poultry Products, South China Agricultural University, Guangzhou, 510642, China
| | - Gang Zhao
- Guangdong Provincial Key Laboratory of Food Quality and Safety/Nation-Local Joint Engineering Research Center for Machining and Safety of Livestock and Poultry Products, South China Agricultural University, Guangzhou, 510642, China
| | - Xiaoqun Wei
- Guangdong Provincial Key Laboratory of Food Quality and Safety/Nation-Local Joint Engineering Research Center for Machining and Safety of Livestock and Poultry Products, South China Agricultural University, Guangzhou, 510642, China
| | - Hongtao Lei
- Guangdong Provincial Key Laboratory of Food Quality and Safety/Nation-Local Joint Engineering Research Center for Machining and Safety of Livestock and Poultry Products, South China Agricultural University, Guangzhou, 510642, China.
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, China.
- Licheng Detection and Certification Group Co., Ltd., Zhongshan, 528403, Guangdong, China.
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31
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Aureli S, Cardenas VB, Raniolo S, Limongelli V. Conformational plasticity and allosteric communication networks explain Shelterin protein TPP1 binding to human telomerase. Commun Chem 2023; 6:242. [PMID: 37935941 PMCID: PMC10630336 DOI: 10.1038/s42004-023-01040-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 10/24/2023] [Indexed: 11/09/2023] Open
Abstract
The Shelterin complex protein TPP1 interacts with human telomerase (TERT) by means of the TEL-patch region, controlling telomere homeostasis. Aberrations in the TPP1-TERT heterodimer formation might lead to short telomeres and severe diseases like dyskeratosis congenita and Hoyeraal-Hreidarsson syndrome. In the present study, we provide a thorough characterization of the structural properties of the TPP1's OB-domain by combining data coming from microsecond-long molecular dynamics calculations, time-series analyses, and graph-based networks. Our results show that the TEL-patch conformational freedom is influenced by a network of long-range amino acid communications that together determine the proper TPP1-TERT binding. Furthermore, we reveal that in TPP1 pathological variants Glu169Δ, Lys170Δ and Leu95Gln, the TEL-patch plasticity is reduced, affecting the correct binding to TERT and, in turn, telomere processivity, which eventually leads to accelerated aging of affected cells. Our study provides a structural basis for the design of TPP1-targeting ligands with therapeutic potential against cancer and telomeropathies.
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Affiliation(s)
- Simone Aureli
- Faculty of Biomedical Sciences, Euler Institute, Università della Svizzera italiana (USI), via G. Buffi 13, Lugano, CH-6900, Switzerland
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneve, Rue Michel-Servet 1, Geneva, CH-1211, Switzerland
- Swiss Institute of Bioinformatics, University of Geneve, Geneva, CH-1206, Switzerland
| | - Vince Bart Cardenas
- Faculty of Biomedical Sciences, Euler Institute, Università della Svizzera italiana (USI), via G. Buffi 13, Lugano, CH-6900, Switzerland
| | - Stefano Raniolo
- Faculty of Biomedical Sciences, Euler Institute, Università della Svizzera italiana (USI), via G. Buffi 13, Lugano, CH-6900, Switzerland
| | - Vittorio Limongelli
- Faculty of Biomedical Sciences, Euler Institute, Università della Svizzera italiana (USI), via G. Buffi 13, Lugano, CH-6900, Switzerland.
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32
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Guo Z, Smutok O, Ayva CE, Walden P, Parker J, Whitfield J, Vickers CE, Ungerer JPJ, Katz E, Alexandrov K. Development of epistatic YES and AND protein logic gates and their assembly into signalling cascades. NATURE NANOTECHNOLOGY 2023; 18:1327-1334. [PMID: 37500780 DOI: 10.1038/s41565-023-01450-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Accepted: 06/09/2023] [Indexed: 07/29/2023]
Abstract
The construction and assembly of artificial allosteric protein switches into information and energy processing networks connected to both biological and non-biological systems is a central goal of synthetic biology and bionanotechnology. However, designing protein switches with the desired input, output and performance parameters is challenging. Here we use a range of reporter proteins to demonstrate that their chimeras with duplicated receptor domains produce YES gate protein switches with large (up to 9,000-fold) dynamic ranges and fast (minutes) response rates. In such switches, the epistatic interactions between largely independent synthetic allosteric sites result in an OFF state with minimal background noise. We used YES gate protein switches based on β-lactamase to develop quantitative biosensors of therapeutic drugs and protein biomarkers. Furthermore, we demonstrated the reconfiguration of YES gate switches into AND gate switches controlled by two different inputs, and their assembly into signalling networks regulated at multiple nodes.
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Affiliation(s)
- Zhong Guo
- ARC Centre of Excellence in Synthetic Biology, Brisbane, Queensland, Australia
- Centre for Agriculture and the Bioeconomy, Queensland University of Technology, Brisbane, Queensland, Australia
- School of Biology and Environmental Science, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Oleh Smutok
- Department of Chemistry and Biomolecular Science, Clarkson University, Potsdam, NY, USA
| | - Cagla Ergun Ayva
- Centre for Agriculture and the Bioeconomy, Queensland University of Technology, Brisbane, Queensland, Australia
- School of Biology and Environmental Science, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Patricia Walden
- Centre for Agriculture and the Bioeconomy, Queensland University of Technology, Brisbane, Queensland, Australia
- School of Biology and Environmental Science, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Jake Parker
- Yakka Bio, Canberra, New South Wales, Australia
| | - Jason Whitfield
- UNSW Founders, University of New South Wales, Sydney, New South Wales, Australia
| | - Claudia E Vickers
- ARC Centre of Excellence in Synthetic Biology, Brisbane, Queensland, Australia
- Centre for Agriculture and the Bioeconomy, Queensland University of Technology, Brisbane, Queensland, Australia
- School of Biology and Environmental Science, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Jacobus P J Ungerer
- Department of Chemical Pathology, Pathology Queensland, Brisbane, Queensland, Australia
- Faculty of Health and Behavioural Sciences, University of Queensland, Brisbane, Queensland, Australia
| | - Evgeny Katz
- Department of Chemistry and Biomolecular Science, Clarkson University, Potsdam, NY, USA
| | - Kirill Alexandrov
- ARC Centre of Excellence in Synthetic Biology, Brisbane, Queensland, Australia.
- Centre for Agriculture and the Bioeconomy, Queensland University of Technology, Brisbane, Queensland, Australia.
- School of Biology and Environmental Science, Queensland University of Technology, Brisbane, Queensland, Australia.
- CSIRO-QUT Synthetic Biology Alliance, Brisbane, Queensland, Australia.
- Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, Queensland, Australia.
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33
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Nussinov R, Liu Y, Zhang W, Jang H. Protein conformational ensembles in function: roles and mechanisms. RSC Chem Biol 2023; 4:850-864. [PMID: 37920394 PMCID: PMC10619138 DOI: 10.1039/d3cb00114h] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 09/02/2023] [Indexed: 11/04/2023] Open
Abstract
The sequence-structure-function paradigm has dominated twentieth century molecular biology. The paradigm tacitly stipulated that for each sequence there exists a single, well-organized protein structure. Yet, to sustain cell life, function requires (i) that there be more than a single structure, (ii) that there be switching between the structures, and (iii) that the structures be incompletely organized. These fundamental tenets called for an updated sequence-conformational ensemble-function paradigm. The powerful energy landscape idea, which is the foundation of modernized molecular biology, imported the conformational ensemble framework from physics and chemistry. This framework embraces the recognition that proteins are dynamic and are always interconverting between conformational states with varying energies. The more stable the conformation the more populated it is. The changes in the populations of the states are required for cell life. As an example, in vivo, under physiological conditions, wild type kinases commonly populate their more stable "closed", inactive, conformations. However, there are minor populations of the "open", ligand-free states. Upon their stabilization, e.g., by high affinity interactions or mutations, their ensembles shift to occupy the active states. Here we discuss the role of conformational propensities in function. We provide multiple examples of diverse systems, including protein kinases, lipid kinases, and Ras GTPases, discuss diverse conformational mechanisms, and provide a broad outlook on protein ensembles in the cell. We propose that the number of molecules in the active state (inactive for repressors), determine protein function, and that the dynamic, relative conformational propensities, rather than the rigid structures, are the hallmark of cell life.
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Affiliation(s)
- Ruth Nussinov
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research Frederick MD 21702 USA
- Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University Tel Aviv 69978 Israel
- Cancer Innovation Laboratory, National Cancer Institute Frederick MD 21702 USA
| | - Yonglan Liu
- Cancer Innovation Laboratory, National Cancer Institute Frederick MD 21702 USA
| | - Wengang Zhang
- Cancer Innovation Laboratory, National Cancer Institute Frederick MD 21702 USA
| | - Hyunbum Jang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research Frederick MD 21702 USA
- Cancer Innovation Laboratory, National Cancer Institute Frederick MD 21702 USA
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34
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Tian H, Xiao S, Jiang X, Tao P. PASSerRank: Prediction of allosteric sites with learning to rank. J Comput Chem 2023; 44:2223-2229. [PMID: 37561047 PMCID: PMC11127606 DOI: 10.1002/jcc.27193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 06/19/2023] [Accepted: 07/10/2023] [Indexed: 08/11/2023]
Abstract
Allostery plays a crucial role in regulating protein activity, making it a highly sought-after target in drug development. One of the major challenges in allosteric drug research is the identification of allosteric sites. In recent years, many computational models have been developed for accurate allosteric site prediction. Most of these models focus on designing a general rule that can be applied to pockets of proteins from various families. In this study, we present a new approach using the concept of Learning to Rank (LTR). The LTR model ranks pockets based on their relevance to allosteric sites, that is, how well a pocket meets the characteristics of known allosteric sites. After the training and validation on two datasets, the Allosteric Database (ASD) and CASBench, the LTR model was able to rank an allosteric pocket in the top three positions for 83.6% and 80.5% of test proteins, respectively. The model outperforms other common machine learning models with higher F1 scores (0.662 in ASD and 0.608 in CASBench) and Matthews correlation coefficients (0.645 in ASD and 0.589 in CASBench). The trained model is available on the PASSer platform (https://passer.smu.edu) to aid in drug discovery research.
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Affiliation(s)
- Hao Tian
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas, USA
| | - Sian Xiao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas, USA
| | - Xi Jiang
- Department of Statistics, Southern Methodist University, Dallas, Texas, USA
| | - Peng Tao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas, USA
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35
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Panecka-Hofman J, Poehner I. Structure and dynamics of pteridine reductase 1: the key phenomena relevant to enzyme function and drug design. EUROPEAN BIOPHYSICS JOURNAL : EBJ 2023; 52:521-532. [PMID: 37608196 PMCID: PMC10618315 DOI: 10.1007/s00249-023-01677-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Revised: 07/08/2023] [Accepted: 07/24/2023] [Indexed: 08/24/2023]
Abstract
Pteridine reductase 1 (PTR1) is a folate and pterin pathway enzyme unique for pathogenic trypanosomatids. As a validated drug target, PTR1 has been the focus of recent research efforts aimed at finding more effective treatments against human parasitic diseases such as leishmaniasis or sleeping sickness. Previous PTR1-centered structural studies highlighted the enzyme characteristics, such as flexible regions around the active site, highly conserved structural waters, and species-specific differences in pocket properties and dynamics, which likely impacts the binding of natural substrates and inhibitors. Furthermore, several aspects of the PTR1 function, such as the substrate inhibition phenomenon and the level of ligand binding cooperativity in the enzyme homotetramer, likely related to the global enzyme dynamics, are poorly known at the molecular level. We postulate that future drug design efforts could greatly benefit from a better understanding of these phenomena through studying both the local and global PTR1 dynamics. This review highlights the key aspects of the PTR1 structure and dynamics relevant to structure-based drug design that could be effectively investigated by modeling approaches. Particular emphasis is given to the perspective of molecular dynamics, what has been accomplished in this area to date, and how modeling could impact the PTR1-targeted drug design in the future.
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Affiliation(s)
- Joanna Panecka-Hofman
- Division of Biophysics, Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Pasteura 5, 02-093, Warsaw, Poland.
| | - Ina Poehner
- School of Pharmacy, University of Eastern Finland, Yliopistonranta 1 C, 70211, Kuopio, Finland
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36
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Maria-Solano MA, Choi S. Dynamic allosteric networks drive adenosine A 1 receptor activation and G-protein coupling. eLife 2023; 12:RP90773. [PMID: 37656635 PMCID: PMC10473838 DOI: 10.7554/elife.90773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/03/2023] Open
Abstract
G-protein coupled receptors (GPCRs) present specific activation pathways and signaling among receptor subtypes. Hence, an extensive knowledge of the structural dynamics of the receptor is critical for the development of therapeutics. Here, we target the adenosine A1 receptor (A1R), for which a negligible number of drugs have been approved. We combine molecular dynamics simulations, enhanced sampling techniques, network theory and pocket detection to decipher the activation pathway of A1R, decode the allosteric networks and identify transient pockets. The A1R activation pathway reveal hidden intermediate and pre-active states together with the inactive and fully-active states observed experimentally. The protein energy networks computed throughout these conformational states successfully unravel the extra and intracellular allosteric centers and the communication pathways that couples them. We observe that the allosteric networks are dynamic, being increased along activation and fine-tuned in presence of the trimeric G-proteins. Overlap of transient pockets and energy networks uncover how the allosteric coupling between pockets and distinct functional regions of the receptor is altered along activation. By an in-depth analysis of the bridge between activation pathway, energy networks and transient pockets, we provide a further understanding of A1R. This information can be useful to ease the design of allosteric modulators for A1R.
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Affiliation(s)
- Miguel A Maria-Solano
- Global AI Drug Discovery Center, College of Pharmacy and Graduate School of Pharmaceutical Science, Ewha Womans UniversitySeoulRepublic of Korea
| | - Sun Choi
- Global AI Drug Discovery Center, College of Pharmacy and Graduate School of Pharmaceutical Science, Ewha Womans UniversitySeoulRepublic of Korea
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37
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Lauzon D, Vallée-Bélisle A. Programing Chemical Communication: Allostery vs Multivalent Mechanism. J Am Chem Soc 2023; 145:18846-18854. [PMID: 37581934 DOI: 10.1021/jacs.3c04045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/17/2023]
Abstract
The emergence of life has relied on chemical communication and the ability to integrate multiple chemical inputs into a specific output. Two mechanisms are typically employed by nature to do so: allostery and multivalent activation. Although a better understanding of allostery has recently provided a variety of strategies to optimize the binding affinity, sensitivity, and specificity of molecular switches, mechanisms relying on multivalent activation remain poorly understood. As a proof of concept to compare the thermodynamic basis and design principles of both mechanisms, we have engineered a highly programmable DNA-based switch that can be triggered by either a multivalent or an allosteric DNA activator. By precisely designing the binding interface of the multivalent activator, we show that the affinity, dynamic range, and activated half-life of the molecular switch can be programed with even more versatility than when using an allosteric activator. The simplicity by which the activation properties of molecular switches can be rationally tuned using multivalent assembly suggests that it may find many applications in biosensing, drug delivery, synthetic biology, and molecular computation fields, where precise control over the transduction of binding events into a specific output is key.
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Affiliation(s)
- Dominic Lauzon
- Département de Chimie, Laboratoire de Biosenseurs et Nanomachines, Université de Montréal, Montréal QC H2V 0B3, Canada
| | - Alexis Vallée-Bélisle
- Département de Chimie, Laboratoire de Biosenseurs et Nanomachines, Université de Montréal, Montréal QC H2V 0B3, Canada
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38
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Skeens E, Sinha S, Ahsan M, D'Ordine AM, Jogl G, Palermo G, Lisi GP. High-Fidelity, Hyper-Accurate, and Evolved Mutants Rewire Atomic Level Communication in CRISPR-Cas9. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.25.554853. [PMID: 37662375 PMCID: PMC10473742 DOI: 10.1101/2023.08.25.554853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
The Cas9-HF1, HypaCas9, and evoCas9 variants of the Cas9 endonuclease are critical tools to mitigate off-target effects in the application of CRISPR-Cas9 technology. The mechanisms by which mutations in the Rec3 domain mediate specificity in these variants are poorly understood. Here, solution NMR and molecular dynamics simulations establish the structural and dynamic effects of high-specificity mutations in Rec3, and how they propagate the allosteric signal of Cas9. We reveal conserved structural changes and peculiar dynamic differences at regions of Rec3 that interface with the RNA:DNA hybrid, transducing chemical signals from Rec3 to the catalytic HNH domain. The variants remodel the communication sourcing from the Rec3 α-helix 37, previously shown to sense target DNA complementarity, either directly or allosterically. This mechanism increases communication between the DNA mismatch recognition helix and the HNH active site, shedding light on the structure and dynamics underlying Cas9 specificity and providing insight for future engineering principles.
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39
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Yu Y, O'Neill RT, Boulatov R, Widenhoefer RA, Craig SL. Allosteric control of olefin isomerization kinetics via remote metal binding and its mechanochemical analysis. Nat Commun 2023; 14:5074. [PMID: 37604905 PMCID: PMC10442431 DOI: 10.1038/s41467-023-40842-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 08/14/2023] [Indexed: 08/23/2023] Open
Abstract
Allosteric control of reaction thermodynamics is well understood, but the mechanisms by which changes in local geometries of receptor sites lower activation reaction barriers in electronically uncoupled, remote reaction moieties remain relatively unexplored. Here we report a molecular scaffold in which the rate of thermal E-to-Z isomerization of an alkene increases by a factor of as much as 104 in response to fast binding of a metal ion to a remote receptor site. A mechanochemical model of the olefin coupled to a compressive harmonic spring reproduces the observed acceleration quantitatively, adding the studied isomerization to the very few reactions demonstrated to be sensitive to extrinsic compressive force. The work validates experimentally the generalization of mechanochemical kinetics to compressive loads and demonstrates that the formalism of force-coupled reactivity offers a productive framework for the quantitative analysis of the molecular basis of allosteric control of reaction kinetics. Important differences in the effects of compressive vs. tensile force on the kinetic stabilities of molecules are discussed.
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Affiliation(s)
- Yichen Yu
- Department of Chemistry, Duke University, Durham, NC, 27708, USA
| | - Robert T O'Neill
- Department of Chemistry, University of Liverpool, Crown Street, Liverpool, L69 7ZD, UK
| | - Roman Boulatov
- Department of Chemistry, University of Liverpool, Crown Street, Liverpool, L69 7ZD, UK.
| | | | - Stephen L Craig
- Department of Chemistry, Duke University, Durham, NC, 27708, USA.
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40
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Buigues P, Gehrke S, Badaoui M, Dudas B, Mandana G, Qi T, Bottegoni G, Rosta E. Investigating the Unbinding of Muscarinic Antagonists from the Muscarinic 3 Receptor. J Chem Theory Comput 2023; 19:5260-5272. [PMID: 37458730 PMCID: PMC10413856 DOI: 10.1021/acs.jctc.3c00023] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Indexed: 08/09/2023]
Abstract
Patient symptom relief is often heavily influenced by the residence time of the inhibitor-target complex. For the human muscarinic receptor 3 (hMR3), tiotropium is a long-acting bronchodilator used in conditions such as asthma or chronic obstructive pulmonary disease (COPD). The mechanistic insights into this inhibitor remain unclear; specifically, the elucidation of the main factors determining the unbinding rates could help develop the next generation of antimuscarinic agents. Using our novel unbinding algorithm, we were able to investigate ligand dissociation from hMR3. The unbinding paths of tiotropium and two of its analogues, N-methylscopolamin and homatropine methylbromide, show a consistent qualitative mechanism and allow us to identify the structural bottleneck of the process. Furthermore, our machine learning-based analysis identified key roles of the ECL2/TM5 junction involved in the transition state. Additionally, our results point to relevant changes at the intracellular end of the TM6 helix leading to the ICL3 kinase domain, highlighting the closest residue L482. This residue is located right between two main protein binding sites involved in signal transduction for hMR3's activation and regulation. We also highlight key pharmacophores of tiotropium that play determining roles in the unbinding kinetics and could aid toward drug design and lead optimization.
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Affiliation(s)
- Pedro
J. Buigues
- Department
of Physics and Astronomy, University College
London, London WC1E 6BT, United
Kingdom
| | - Sascha Gehrke
- Department
of Physics and Astronomy, University College
London, London WC1E 6BT, United
Kingdom
| | - Magd Badaoui
- Department
of Physics and Astronomy, University College
London, London WC1E 6BT, United
Kingdom
| | - Balint Dudas
- Department
of Physics and Astronomy, University College
London, London WC1E 6BT, United
Kingdom
| | - Gaurav Mandana
- Department
of Physics and Astronomy, University College
London, London WC1E 6BT, United
Kingdom
| | - Tianyun Qi
- Department
of Physics and Astronomy, University College
London, London WC1E 6BT, United
Kingdom
| | - Giovanni Bottegoni
- Dipartimento
di Scienze Biomolecolari (DISB), University
of Urbino, Urbino Piazza Rinascimento, 6, Urbino 61029, Italy
- Institute
of Clinical Sciences, University of Birmingham, Edgbaston, B15 2TT Birmingham, United Kingdom
| | - Edina Rosta
- Department
of Physics and Astronomy, University College
London, London WC1E 6BT, United
Kingdom
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41
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Castelli M, Yan P, Rodina A, Digwal CS, Panchal P, Chiosis G, Moroni E, Colombo G. How aberrant N-glycosylation can alter protein functionality and ligand binding: An atomistic view. Structure 2023; 31:987-1004.e8. [PMID: 37343552 PMCID: PMC10526633 DOI: 10.1016/j.str.2023.05.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 04/21/2023] [Accepted: 05/25/2023] [Indexed: 06/23/2023]
Abstract
Protein-assembly defects due to an enrichment of aberrant conformational protein variants are emerging as a new frontier in therapeutics design. Understanding the structural elements that rewire the conformational dynamics of proteins and pathologically perturb functionally oriented ensembles is important for inhibitor development. Chaperones are hub proteins for the assembly of multiprotein complexes and an enrichment of aberrant conformers can affect the cellular proteome, and in turn, phenotypes. Here, we integrate computational and experimental tools to investigte how N-glycosylation of specific residues in glucose-regulated protein 94 (GRP94) modulates internal dynamics and alters the conformational fitness of regions fundamental for the interaction with ATP and synthetic ligands and impacts substructures important for the recognition of interacting proteins. N-glycosylation plays an active role in modulating the energy landscape of GRP94, and we provide support for leveraging the knowledge on distinct glycosylation variants to design molecules targeting GRP94 disease-associated conformational states and assemblies.
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Affiliation(s)
- Matteo Castelli
- Department of Chemistry, University of Pavia, via Taramelli 12, 27100 Pavia, Italy
| | - Pengrong Yan
- Chemical Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Anna Rodina
- Chemical Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Chander S Digwal
- Chemical Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Palak Panchal
- Chemical Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Gabriela Chiosis
- Chemical Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
| | | | - Giorgio Colombo
- Department of Chemistry, University of Pavia, via Taramelli 12, 27100 Pavia, Italy.
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42
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Alao JP, Obaseki I, Amankwah YS, Nguyen Q, Sugoor M, Unruh E, Popoola HO, Tehver R, Kravats AN. Insight into the Nucleotide Based Modulation of the Grp94 Molecular Chaperone Using Multiscale Dynamics. J Phys Chem B 2023; 127:5389-5409. [PMID: 37294929 PMCID: PMC10292203 DOI: 10.1021/acs.jpcb.3c00260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 05/17/2023] [Indexed: 06/11/2023]
Abstract
Grp94, an ER-localized molecular chaperone, is required for the folding and activation of many membrane and secretory proteins. Client activation by Grp94 is mediated by nucleotide and conformational changes. In this work, we aim to understand how microscopic changes from nucleotide hydrolysis can potentiate large-scale conformational changes of Grp94. We performed all-atom molecular dynamics simulations on the ATP-hydrolysis competent state of the Grp94 dimer in four different nucleotide bound states. We found that Grp94 was the most rigid when ATP was bound. ATP hydrolysis or nucleotide removal enhanced mobility of the N-terminal domain and ATP lid, resulting in suppression of interdomain communication. In an asymmetric conformation with one hydrolyzed nucleotide, we identified a more compact state, similar to experimental observations. We also identified a potential regulatory role of the flexible linker, as it formed electrostatic interactions with the Grp94 M-domain helix near the region where BiP is known to bind. These studies were complemented with normal-mode analysis of an elastic network model to investigate Grp94's large-scale conformational changes. SPM analysis identified residues that are important in signaling conformational change, many of which have known functional relevance in ATP coordination and catalysis, client binding, and BiP binding. Our findings suggest that ATP hydrolysis in Grp94 alters allosteric wiring and facilitates conformational changes.
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Affiliation(s)
- John Paul Alao
- Department
of Chemistry & Biochemistry, Miami University, Oxford, Ohio 45056, United States
| | - Ikponwmosa Obaseki
- Department
of Chemistry & Biochemistry, Miami University, Oxford, Ohio 45056, United States
| | - Yaa Sarfowah Amankwah
- Department
of Chemistry & Biochemistry, Miami University, Oxford, Ohio 45056, United States
| | - Quinn Nguyen
- Department
of Chemistry & Biochemistry, Miami University, Oxford, Ohio 45056, United States
- Department
of Chemistry, University of California,
Irvine, Irvine, California 92697, United States
| | - Meghana Sugoor
- Department
of Chemistry & Biochemistry, Miami University, Oxford, Ohio 45056, United States
| | - Erin Unruh
- Department
of Chemistry & Biochemistry, Miami University, Oxford, Ohio 45056, United States
- Cell,
Molecular, and Structural Biology Program, Department of Chemistry
& Biochemistry, Miami University, Oxford, Ohio 45056, United States
| | | | - Riina Tehver
- Department
of Physics, Denison University, Granville, Ohio 43023, United States
| | - Andrea N. Kravats
- Department
of Chemistry & Biochemistry, Miami University, Oxford, Ohio 45056, United States
- Cell,
Molecular, and Structural Biology Program, Department of Chemistry
& Biochemistry, Miami University, Oxford, Ohio 45056, United States
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43
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Mendels D, Byléhn F, Sirk TW, de Pablo JJ. Systematic modification of functionality in disordered elastic networks through free energy surface tailoring. SCIENCE ADVANCES 2023; 9:eadf7541. [PMID: 37285442 DOI: 10.1126/sciadv.adf7541] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 05/01/2023] [Indexed: 06/09/2023]
Abstract
A combined machine learning-physics-based approach is explored for molecular and materials engineering. Specifically, collective variables, akin to those used in enhanced sampled simulations, are constructed using a machine learning model trained on data gathered from a single system. Through the constructed collective variables, it becomes possible to identify critical molecular interactions in the considered system, the modulation of which enables a systematic tailoring of the system's free energy landscape. To explore the efficacy of the proposed approach, we use it to engineer allosteric regulation and uniaxial strain fluctuations in a complex disordered elastic network. Its successful application in these two cases provides insights regarding how functionality is governed in systems characterized by extensive connectivity and points to its potential for design of complex molecular systems.
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Affiliation(s)
- Dan Mendels
- Pritzker School of Molecular Engineering, University of Chicago, 5640 S. Ellis Avenue, Chicago, IL 60637 USA
| | - Fabian Byléhn
- Pritzker School of Molecular Engineering, University of Chicago, 5640 S. Ellis Avenue, Chicago, IL 60637 USA
| | - Timothy W Sirk
- Polymers Branch, U.S. CCDC Army Research Laboratory, Aberdeen Proving Ground, MD 21005, USA
| | - Juan J de Pablo
- Pritzker School of Molecular Engineering, University of Chicago, 5640 S. Ellis Avenue, Chicago, IL 60637 USA
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44
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Maschietto F, Allen B, Kyro GW, Batista VS. MDiGest: A Python package for describing allostery from molecular dynamics simulations. J Chem Phys 2023; 158:215103. [PMID: 37272574 PMCID: PMC10769569 DOI: 10.1063/5.0140453] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 04/04/2023] [Indexed: 06/06/2023] Open
Abstract
Many biological processes are regulated by allosteric mechanisms that communicate with distant sites in the protein responsible for functionality. The binding of a small molecule at an allosteric site typically induces conformational changes that propagate through the protein along allosteric pathways regulating enzymatic activity. Elucidating those communication pathways from allosteric sites to orthosteric sites is, therefore, essential to gain insights into biochemical processes. Targeting the allosteric pathways by mutagenesis can allow the engineering of proteins with desired functions. Furthermore, binding small molecule modulators along the allosteric pathways is a viable approach to target reactions using allosteric inhibitors/activators with temporal and spatial selectivity. Methods based on network theory can elucidate protein communication networks through the analysis of pairwise correlations observed in molecular dynamics (MD) simulations using molecular descriptors that serve as proxies for allosteric information. Typically, single atomic descriptors such as α-carbon displacements are used as proxies for allosteric information. Therefore, allosteric networks are based on correlations revealed by that descriptor. Here, we introduce a Python software package that provides a comprehensive toolkit for studying allostery from MD simulations of biochemical systems. MDiGest offers the ability to describe protein dynamics by combining different approaches, such as correlations of atomic displacements or dihedral angles, as well as a novel approach based on the correlation of Kabsch-Sander electrostatic couplings. MDiGest allows for comparisons of networks and community structures that capture physical information relevant to allostery. Multiple complementary tools for studying essential dynamics include principal component analysis, root mean square fluctuation, as well as secondary structure-based analyses.
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Affiliation(s)
- Federica Maschietto
- Department of Chemistry, Yale University, 225 Prospect Street, New Haven, Connecticut 06520, USA
| | - Brandon Allen
- Department of Chemistry, Yale University, 225 Prospect Street, New Haven, Connecticut 06520, USA
| | - Gregory W. Kyro
- Department of Chemistry, Yale University, 225 Prospect Street, New Haven, Connecticut 06520, USA
| | - Victor S. Batista
- Department of Chemistry, Yale University, 225 Prospect Street, New Haven, Connecticut 06520, USA
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45
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Konovalov KA, Wu CG, Qiu Y, Balakrishnan VK, Parihar PS, O’Connor MS, Xing Y, Huang X. Disease mutations and phosphorylation alter the allosteric pathways involved in autoinhibition of protein phosphatase 2A. J Chem Phys 2023; 158:215101. [PMID: 37260014 PMCID: PMC10238128 DOI: 10.1063/5.0150272] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 05/16/2023] [Indexed: 06/02/2023] Open
Abstract
Mutations in protein phosphatase 2A (PP2A) are connected to intellectual disability and cancer. It has been hypothesized that these mutations might disrupt the autoinhibition and phosphorylation-induced activation of PP2A. Since they are located far from both the active and substrate binding sites, it is unclear how they exert their effect. We performed allosteric pathway analysis based on molecular dynamics simulations and combined it with biochemical experiments to investigate the autoinhibition of PP2A. In the wild type (WT), the C-arm of the regulatory subunit B56δ obstructs the active and substrate binding sites exerting a dual autoinhibition effect. We find that the disease mutant, E198K, severely weakens the allosteric pathways that stabilize the C-arm in the WT. Instead, the strongest allosteric pathways in E198K take a different route that promotes exposure of the substrate binding site. To facilitate the allosteric pathway analysis, we introduce a path clustering algorithm for lumping pathways into channels. We reveal remarkable similarities between the allosteric channels of E198K and those in phosphorylation-activated WT, suggesting that the autoinhibition can be alleviated through a conserved mechanism. In contrast, we find that another disease mutant, E200K, which is in spatial proximity of E198, does not repartition the allosteric pathways leading to the substrate binding site; however, it may still induce exposure of the active site. This finding agrees with our biochemical data, allowing us to predict the activity of PP2A with the phosphorylated B56δ and provide insight into how disease mutations in spatial proximity alter the enzymatic activity in surprisingly different mechanisms.
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Affiliation(s)
- Kirill A. Konovalov
- Department of Chemistry, Theoretical Chemistry Institute, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
| | | | - Yunrui Qiu
- Department of Chemistry, Theoretical Chemistry Institute, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
| | - Vijaya Kumar Balakrishnan
- McArdle Laboratory for Cancer Research, Department of Oncology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA
| | - Pankaj Singh Parihar
- McArdle Laboratory for Cancer Research, Department of Oncology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA
| | - Michael S. O’Connor
- Biophysics Graduate Program, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
| | - Yongna Xing
- Authors to whom correspondence should be addressed: and
| | - Xuhui Huang
- Authors to whom correspondence should be addressed: and
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46
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Kim M, Jo H, Jung GY, Oh SS. Molecular Complementarity of Proteomimetic Materials for Target-Specific Recognition and Recognition-Mediated Complex Functions. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2208309. [PMID: 36525617 DOI: 10.1002/adma.202208309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 11/29/2022] [Indexed: 06/02/2023]
Abstract
As biomolecules essential for sustaining life, proteins are generated from long chains of 20 different α-amino acids that are folded into unique 3D structures. In particular, many proteins have molecular recognition functions owing to their binding pockets, which have complementary shapes, charges, and polarities for specific targets, making these biopolymers unique and highly valuable for biomedical and biocatalytic applications. Based on the understanding of protein structures and microenvironments, molecular complementarity can be exhibited by synthesizable and modifiable materials. This has prompted researchers to explore the proteomimetic potentials of a diverse range of materials, including biologically available peptides and oligonucleotides, synthetic supramolecules, inorganic molecules, and related coordination networks. To fully resemble a protein, proteomimetic materials perform the molecular recognition to mediate complex molecular functions, such as allosteric regulation, signal transduction, enzymatic reactions, and stimuli-responsive motions; this can also expand the landscape of their potential bio-applications. This review focuses on the recognitive aspects of proteomimetic designs derived for individual materials and their conformations. Recent progress provides insights to help guide the development of advanced protein mimicry with material heterogeneity, design modularity, and tailored functionality. The perspectives and challenges of current proteomimetic designs and tools are also discussed in relation to future applications.
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Affiliation(s)
- Minsun Kim
- School of Interdisciplinary Bioscience and Bioengineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea
| | - Hyesung Jo
- Department of Materials Science and Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, South Korea
| | - Gyoo Yeol Jung
- School of Interdisciplinary Bioscience and Bioengineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea
- Department of Chemical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, South Korea
| | - Seung Soo Oh
- School of Interdisciplinary Bioscience and Bioengineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea
- Department of Materials Science and Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, South Korea
- Department of Chemical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, South Korea
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47
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Wodak SJ, Vajda S, Lensink MF, Kozakov D, Bates PA. Critical Assessment of Methods for Predicting the 3D Structure of Proteins and Protein Complexes. Annu Rev Biophys 2023; 52:183-206. [PMID: 36626764 PMCID: PMC10885158 DOI: 10.1146/annurev-biophys-102622-084607] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Advances in a scientific discipline are often measured by small, incremental steps. In this review, we report on two intertwined disciplines in the protein structure prediction field, modeling of single chains and modeling of complexes, that have over decades emulated this pattern, as monitored by the community-wide blind prediction experiments CASP and CAPRI. However, over the past few years, dramatic advances were observed for the accurate prediction of single protein chains, driven by a surge of deep learning methodologies entering the prediction field. We review the mainscientific developments that enabled these recent breakthroughs and feature the important role of blind prediction experiments in building up and nurturing the structure prediction field. We discuss how the new wave of artificial intelligence-based methods is impacting the fields of computational and experimental structural biology and highlight areas in which deep learning methods are likely to lead to future developments, provided that major challenges are overcome.
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Affiliation(s)
- Shoshana J Wodak
- VIB-VUB Center for Structural Biology, Vrije Universiteit Brussel, Brussels, Belgium;
| | - Sandor Vajda
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA;
- Department of Chemistry, Boston University, Boston, Massachusetts, USA
| | - Marc F Lensink
- Univ. Lille, CNRS, UMR 8576-UGSF-Unité de Glycobiologie Structurale et Fonctionnelle, Lille, France;
| | - Dima Kozakov
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA;
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York, USA
| | - Paul A Bates
- Biomolecular Modelling Laboratory, The Francis Crick Institute, London, United Kingdom;
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48
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Tian H, Xiao S, Jiang X, Tao P. PASSerRank: Prediction of Allosteric Sites with Learning to Rank. ARXIV 2023:arXiv:2302.01117v2. [PMID: 36776818 PMCID: PMC9915737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/14/2023]
Abstract
Allostery plays a crucial role in regulating protein activity, making it a highly sought-after target in drug development. One of the major challenges in allosteric drug research is the identification of allosteric sites. In recent years, many computational models have been developed for accurate allosteric site prediction. Most of these models focus on designing a general rule that can be applied to pockets of proteins from various families. In this study, we present a new approach using the concept of Learning to Rank (LTR). The LTR model ranks pockets based on their relevance to allosteric sites, i.e., how well a pocket meets the characteristics of known allosteric sites. The model outperforms other common machine learning models with higher F1 score and Matthews correlation coefficient. After the training and validation on two datasets, the Allosteric Database (ASD) and CASBench, the LTR model was able to rank an allosteric pocket in the top 3 positions for 83.6% and 80.5% of test proteins, respectively. The trained model is available on the PASSer platform (https://passer.smu.edu) to aid in drug discovery research.
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Affiliation(s)
- Hao Tian
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas, United States of America
| | - Sian Xiao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas, United States of America
| | - Xi Jiang
- Department of Statistics, Southern Methodist University, Dallas, Texas, United States of America
| | - Peng Tao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas, United States of America
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49
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Verkhivker G, Alshahrani M, Gupta G, Xiao S, Tao P. From Deep Mutational Mapping of Allosteric Protein Landscapes to Deep Learning of Allostery and Hidden Allosteric Sites: Zooming in on "Allosteric Intersection" of Biochemical and Big Data Approaches. Int J Mol Sci 2023; 24:7747. [PMID: 37175454 PMCID: PMC10178073 DOI: 10.3390/ijms24097747] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 04/22/2023] [Accepted: 04/23/2023] [Indexed: 05/15/2023] Open
Abstract
The recent advances in artificial intelligence (AI) and machine learning have driven the design of new expert systems and automated workflows that are able to model complex chemical and biological phenomena. In recent years, machine learning approaches have been developed and actively deployed to facilitate computational and experimental studies of protein dynamics and allosteric mechanisms. In this review, we discuss in detail new developments along two major directions of allosteric research through the lens of data-intensive biochemical approaches and AI-based computational methods. Despite considerable progress in applications of AI methods for protein structure and dynamics studies, the intersection between allosteric regulation, the emerging structural biology technologies and AI approaches remains largely unexplored, calling for the development of AI-augmented integrative structural biology. In this review, we focus on the latest remarkable progress in deep high-throughput mining and comprehensive mapping of allosteric protein landscapes and allosteric regulatory mechanisms as well as on the new developments in AI methods for prediction and characterization of allosteric binding sites on the proteome level. We also discuss new AI-augmented structural biology approaches that expand our knowledge of the universe of protein dynamics and allostery. We conclude with an outlook and highlight the importance of developing an open science infrastructure for machine learning studies of allosteric regulation and validation of computational approaches using integrative studies of allosteric mechanisms. The development of community-accessible tools that uniquely leverage the existing experimental and simulation knowledgebase to enable interrogation of the allosteric functions can provide a much-needed boost to further innovation and integration of experimental and computational technologies empowered by booming AI field.
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Affiliation(s)
- Gennady Verkhivker
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; (M.A.); (G.G.)
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA 92618, USA
| | - Mohammed Alshahrani
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; (M.A.); (G.G.)
| | - Grace Gupta
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; (M.A.); (G.G.)
| | - Sian Xiao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, TX 75275, USA; (S.X.); (P.T.)
| | - Peng Tao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, TX 75275, USA; (S.X.); (P.T.)
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50
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Maschietto F, Morzan UN, Tofoleanu F, Gheeraert A, Chaudhuri A, Kyro GW, Nekrasov P, Brooks B, Loria JP, Rivalta I, Batista VS. Turning up the heat mimics allosteric signaling in imidazole-glycerol phosphate synthase. Nat Commun 2023; 14:2239. [PMID: 37076500 PMCID: PMC10115891 DOI: 10.1038/s41467-023-37956-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 04/06/2023] [Indexed: 04/21/2023] Open
Abstract
Allosteric drugs have the potential to revolutionize biomedicine due to their enhanced selectivity and protection against overdosage. However, we need to better understand allosteric mechanisms in order to fully harness their potential in drug discovery. In this study, molecular dynamics simulations and nuclear magnetic resonance spectroscopy are used to investigate how increases in temperature affect allostery in imidazole glycerol phosphate synthase. Results demonstrate that temperature increase triggers a cascade of local amino acid-to-amino acid dynamics that remarkably resembles the allosteric activation that takes place upon effector binding. The differences in the allosteric response elicited by temperature increase as opposed to effector binding are conditional to the alterations of collective motions induced by either mode of activation. This work provides an atomistic picture of temperature-dependent allostery, which could be harnessed to more precisely control enzyme function.
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Affiliation(s)
- Federica Maschietto
- Department of Chemistry, Yale University, P.O. Box 208107, New Haven, CT, 06520-8107, USA.
| | - Uriel N Morzan
- International Center for Theoretical Physics, Strada Costiera 11, 34151, Trieste, Italy.
| | - Florentina Tofoleanu
- Department of Chemistry, Yale University, P.O. Box 208107, New Haven, CT, 06520-8107, USA
- Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20852, USA
- Treeline Biosciences, 500 Arsenal Street, Watertown, MA, 02472, USA
| | - Aria Gheeraert
- ENSL, CNRS, Laboratoire de Chimie UMR 5182, 46 allée d'Italie, 69364, Lyon, France
- Dipartimento di Chimica Industriale "Toso Montanari", Alma Mater Studiorum, Università di Bologna, Bologna, Italy
| | - Apala Chaudhuri
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Gregory W Kyro
- Department of Chemistry, Yale University, P.O. Box 208107, New Haven, CT, 06520-8107, USA
| | - Peter Nekrasov
- Department of Chemistry, Yale University, P.O. Box 208107, New Haven, CT, 06520-8107, USA
| | - Bernard Brooks
- Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20852, USA
| | - J Patrick Loria
- Department of Chemistry, Yale University, P.O. Box 208107, New Haven, CT, 06520-8107, USA.
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA.
| | - Ivan Rivalta
- ENSL, CNRS, Laboratoire de Chimie UMR 5182, 46 allée d'Italie, 69364, Lyon, France.
- Dipartimento di Chimica Industriale "Toso Montanari", Alma Mater Studiorum, Università di Bologna, Bologna, Italy.
| | - Victor S Batista
- Department of Chemistry, Yale University, P.O. Box 208107, New Haven, CT, 06520-8107, USA.
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