1
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Holt GT, Gorman J, Wang S, Lowegard AU, Zhang B, Liu T, Lin BC, Louder MK, Frenkel MS, McKee K, O'Dell S, Rawi R, Shen CH, Doria-Rose NA, Kwong PD, Donald BR. Improved HIV-1 neutralization breadth and potency of V2-apex antibodies by in silico design. Cell Rep 2023; 42:112711. [PMID: 37436900 PMCID: PMC10528384 DOI: 10.1016/j.celrep.2023.112711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 05/05/2023] [Accepted: 06/12/2023] [Indexed: 07/14/2023] Open
Abstract
Broadly neutralizing antibodies (bNAbs) against HIV can reduce viral transmission in humans, but an effective therapeutic will require unusually high breadth and potency of neutralization. We employ the OSPREY computational protein design software to engineer variants of two apex-directed bNAbs, PGT145 and PG9RSH, resulting in increases in potency of over 100-fold against some viruses. The top designed variants improve neutralization breadth from 39% to 54% at clinically relevant concentrations (IC80 < 1 μg/mL) and improve median potency (IC80) by up to 4-fold over a cross-clade panel of 208 strains. To investigate the mechanisms of improvement, we determine cryoelectron microscopy structures of each variant in complex with the HIV envelope trimer. Surprisingly, we find the largest increases in breadth to be a result of optimizing side-chain interactions with highly variable epitope residues. These results provide insight into mechanisms of neutralization breadth and inform strategies for antibody design and improvement.
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Affiliation(s)
- Graham T Holt
- Department of Computer Science, Duke University, Durham, NC, USA; Program in Computational Biology & Bioinformatics, Duke University, Durham, NC, USA
| | - Jason Gorman
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Siyu Wang
- Program in Computational Biology & Bioinformatics, Duke University, Durham, NC, USA
| | - Anna U Lowegard
- Department of Computer Science, Duke University, Durham, NC, USA; Program in Computational Biology & Bioinformatics, Duke University, Durham, NC, USA
| | - Baoshan Zhang
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Tracy Liu
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Bob C Lin
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Mark K Louder
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | | | - Krisha McKee
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Sijy O'Dell
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Reda Rawi
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Chen-Hsiang Shen
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Nicole A Doria-Rose
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Peter D Kwong
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA.
| | - Bruce R Donald
- Department of Computer Science, Duke University, Durham, NC, USA; Department of Biochemistry, Duke University, Durham, NC, USA; Department of Mathematics, Duke University, Durham, NC, USA; Department of Chemistry, Duke University, Durham, NC, USA.
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2
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Wang S, Reeve SM, Holt GT, Ojewole AA, Frenkel MS, Gainza P, Keshipeddy S, Fowler VG, Wright DL, Donald BR. Chiral evasion and stereospecific antifolate resistance in Staphylococcus aureus. PLoS Comput Biol 2022; 18:e1009855. [PMID: 35143481 PMCID: PMC8865654 DOI: 10.1371/journal.pcbi.1009855] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 02/23/2022] [Accepted: 01/21/2022] [Indexed: 11/19/2022] Open
Abstract
Antimicrobial resistance presents a significant health care crisis. The mutation F98Y in Staphylococcus aureus dihydrofolate reductase (SaDHFR) confers resistance to the clinically important antifolate trimethoprim (TMP). Propargyl-linked antifolates (PLAs), next generation DHFR inhibitors, are much more resilient than TMP against this F98Y variant, yet this F98Y substitution still reduces efficacy of these agents. Surprisingly, differences in the enantiomeric configuration at the stereogenic center of PLAs influence the isomeric state of the NADPH cofactor. To understand the molecular basis of F98Y-mediated resistance and how PLAs' inhibition drives NADPH isomeric states, we used protein design algorithms in the osprey protein design software suite to analyze a comprehensive suite of structural, biophysical, biochemical, and computational data. Here, we present a model showing how F98Y SaDHFR exploits a different anomeric configuration of NADPH to evade certain PLAs' inhibition, while other PLAs remain unaffected by this resistance mechanism.
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Affiliation(s)
- Siyu Wang
- Department of Computer Science, Duke University, Durham, North Carolina, United States of America
- Program in Computational Biology and Bioinformatics, Duke University, Durham, North Carolina, United States of America
| | - Stephanie M. Reeve
- Department of Pharmaceutical Sciences, University of Connecticut, Storrs, Connecticut, United States of America
| | - Graham T. Holt
- Department of Computer Science, Duke University, Durham, North Carolina, United States of America
- Program in Computational Biology and Bioinformatics, Duke University, Durham, North Carolina, United States of America
| | - Adegoke A. Ojewole
- Department of Computer Science, Duke University, Durham, North Carolina, United States of America
- Program in Computational Biology and Bioinformatics, Duke University, Durham, North Carolina, United States of America
| | - Marcel S. Frenkel
- Department of Biochemistry, Duke University Medical Center, Durham, North Carolina, United States of America
| | - Pablo Gainza
- Department of Computer Science, Duke University, Durham, North Carolina, United States of America
| | - Santosh Keshipeddy
- Department of Pharmaceutical Sciences, University of Connecticut, Storrs, Connecticut, United States of America
| | - Vance G. Fowler
- Division of Infections Diseases, Department of Medicine, Duke University Medical Center, Durham, North Carolina, United States of America
| | - Dennis L. Wright
- Department of Pharmaceutical Sciences, University of Connecticut, Storrs, Connecticut, United States of America
- Department of Chemistry, University of Connecticut, Storrs, Connecticut, United States of America
| | - Bruce R. Donald
- Department of Computer Science, Duke University, Durham, North Carolina, United States of America
- Department of Biochemistry, Duke University Medical Center, Durham, North Carolina, United States of America
- Department of Mathematics, Duke University, Durham, North Carolina, United States of America
- Department of Chemistry, Duke University, Durham, North Carolina, United States of America
- * E-mail:
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3
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Lowegard AU, Frenkel MS, Holt GT, Jou JD, Ojewole AA, Donald BR. Novel, provable algorithms for efficient ensemble-based computational protein design and their application to the redesign of the c-Raf-RBD:KRas protein-protein interface. PLoS Comput Biol 2020; 16:e1007447. [PMID: 32511232 PMCID: PMC7329130 DOI: 10.1371/journal.pcbi.1007447] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 07/01/2020] [Accepted: 05/13/2020] [Indexed: 11/25/2022] Open
Abstract
The K* algorithm provably approximates partition functions for a set of states (e.g., protein, ligand, and protein-ligand complex) to a user-specified accuracy ε. Often, reaching an ε-approximation for a particular set of partition functions takes a prohibitive amount of time and space. To alleviate some of this cost, we introduce two new algorithms into the osprey suite for protein design: fries, a Fast Removal of Inadequately Energied Sequences, and EWAK*, an Energy Window Approximation to K*. fries pre-processes the sequence space to limit a design to only the most stable, energetically favorable sequence possibilities. EWAK* then takes this pruned sequence space as input and, using a user-specified energy window, calculates K* scores using the lowest energy conformations. We expect fries/EWAK* to be most useful in cases where there are many unstable sequences in the design sequence space and when users are satisfied with enumerating the low-energy ensemble of conformations. In combination, these algorithms provably retain calculational accuracy while limiting the input sequence space and the conformations included in each partition function calculation to only the most energetically favorable, effectively reducing runtime while still enriching for desirable sequences. This combined approach led to significant speed-ups compared to the previous state-of-the-art multi-sequence algorithm, BBK*, while maintaining its efficiency and accuracy, which we show across 40 different protein systems and a total of 2,826 protein design problems. Additionally, as a proof of concept, we used these new algorithms to redesign the protein-protein interface (PPI) of the c-Raf-RBD:KRas complex. The Ras-binding domain of the protein kinase c-Raf (c-Raf-RBD) is the tightest known binder of KRas, a protein implicated in difficult-to-treat cancers. fries/EWAK* accurately retrospectively predicted the effect of 41 different sets of mutations in the PPI of the c-Raf-RBD:KRas complex. Notably, these mutations include mutations whose effect had previously been incorrectly predicted using other computational methods. Next, we used fries/EWAK* for prospective design and discovered a novel point mutation that improves binding of c-Raf-RBD to KRas in its active, GTP-bound state (KRasGTP). We combined this new mutation with two previously reported mutations (which were highly-ranked by osprey) to create a new variant of c-Raf-RBD, c-Raf-RBD(RKY). fries/EWAK* in osprey computationally predicted that this new variant binds even more tightly than the previous best-binding variant, c-Raf-RBD(RK). We measured the binding affinity of c-Raf-RBD(RKY) using a bio-layer interferometry (BLI) assay, and found that this new variant exhibits single-digit nanomolar affinity for KRasGTP, confirming the computational predictions made with fries/EWAK*. This new variant binds roughly five times more tightly than the previous best known binder and roughly 36 times more tightly than the design starting point (wild-type c-Raf-RBD). This study steps through the advancement and development of computational protein design by presenting theory, new algorithms, accurate retrospective designs, new prospective designs, and biochemical validation. Computational structure-based protein design is an innovative tool for redesigning proteins to introduce a particular or novel function. One such function is improving the binding of one protein to another, which can increase our understanding of important protein systems. Herein we introduce two novel, provable algorithms, fries and EWAK*, for more efficient computational structure-based protein design as well as their application to the redesign of the c-Raf-RBD:KRas protein-protein interface. These new algorithms speed-up computational structure-based protein design while maintaining accurate calculations, allowing for larger, previously infeasible protein designs. Additionally, using fries and EWAK* within the osprey suite, we designed the tightest known binder of KRas, a heavily studied cancer target that interacts with a number of different proteins. This previously undiscovered variant of a KRas-binding domain, c-Raf-RBD, has potential to serve as a tool to further probe the protein-protein interface of KRas with its effectors and its discovery alone emphasizes the potential for more successful applications of computational structure-based protein design.
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Affiliation(s)
- Anna U. Lowegard
- Program in Computational Biology and Bioinformatics, Duke University Medical Center, Durham, North Carolina, United States of America
- Department of Computer Science, Duke University, Durham, North Carolina, United States of America
| | - Marcel S. Frenkel
- Department of Biochemistry, Duke University Medical Center, Durham, North Carolina, United States of America
| | - Graham T. Holt
- Program in Computational Biology and Bioinformatics, Duke University Medical Center, Durham, North Carolina, United States of America
- Department of Computer Science, Duke University, Durham, North Carolina, United States of America
| | - Jonathan D. Jou
- Department of Computer Science, Duke University, Durham, North Carolina, United States of America
| | - Adegoke A. Ojewole
- Program in Computational Biology and Bioinformatics, Duke University Medical Center, Durham, North Carolina, United States of America
- Department of Computer Science, Duke University, Durham, North Carolina, United States of America
| | - Bruce R. Donald
- Department of Computer Science, Duke University, Durham, North Carolina, United States of America
- Department of Biochemistry, Duke University Medical Center, Durham, North Carolina, United States of America
- * E-mail:
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4
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Jou JD, Holt GT, Lowegard AU, Donald BR. Minimization-Aware Recursive K*: A Novel, Provable Algorithm that Accelerates Ensemble-Based Protein Design and Provably Approximates the Energy Landscape. J Comput Biol 2019; 27:550-564. [PMID: 31855059 DOI: 10.1089/cmb.2019.0315] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Protein design algorithms that model continuous sidechain flexibility and conformational ensembles better approximate the in vitro and in vivo behavior of proteins. The previous state of the art, iMinDEE-A*-K*, computes provable ɛ-approximations to partition functions of protein states (e.g., bound vs. unbound) by computing provable, admissible pairwise-minimized energy lower bounds on protein conformations, and using the A* enumeration algorithm to return a gap-free list of lowest-energy conformations. iMinDEE-A*-K* runs in time sublinear in the number of conformations, but can be trapped in loosely-bounded, low-energy conformational wells containing many conformations with highly similar energies. That is, iMinDEE-A*-K* is unable to exploit the correlation between protein conformation and energy: similar conformations often have similar energy. We introduce two new concepts that exploit this correlation: Minimization-Aware Enumeration and Recursive K*. We combine these two insights into a novel algorithm, Minimization-Aware Recursive K* (MARK*), which tightens bounds not on single conformations, but instead on distinct regions of the conformation space. We compare the performance of iMinDEE-A*-K* versus MARK* by running the Branch and Bound over K* (BBK*) algorithm, which provably returns sequences in order of decreasing K* score, using either iMinDEE-A*-K* or MARK* to approximate partition functions. We show on 200 design problems that MARK* not only enumerates and minimizes vastly fewer conformations than the previous state of the art, but also runs up to 2 orders of magnitude faster. Finally, we show that MARK* not only efficiently approximates the partition function, but also provably approximates the energy landscape. To our knowledge, MARK* is the first algorithm to do so. We use MARK* to analyze the change in energy landscape of the bound and unbound states of an HIV-1 capsid protein C-terminal domain in complex with a camelid VHH, and measure the change in conformational entropy induced by binding. Thus, MARK* both accelerates existing designs and offers new capabilities not possible with previous algorithms.
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Affiliation(s)
- Jonathan D Jou
- Department of Computer Science, Duke University, Durham, North Carolina
| | - Graham T Holt
- Department of Computer Science, Duke University, Durham, North Carolina.,Computational Biology and Bioinformatics Program, Duke University, Durham, North Carolina
| | - Anna U Lowegard
- Department of Computer Science, Duke University, Durham, North Carolina.,Computational Biology and Bioinformatics Program, Duke University, Durham, North Carolina
| | - Bruce R Donald
- Department of Computer Science, Duke University, Durham, North Carolina.,Department of Biochemistry, Duke University Medical Center, Durham, North Carolina.,Department of Chemistry, Duke University, Durham, North Carolina
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5
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Holt GT, Jou JD, Gill NP, Lowegard AU, Martin JW, Madden DR, Donald BR. Computational Analysis of Energy Landscapes Reveals Dynamic Features That Contribute to Binding of Inhibitors to CFTR-Associated Ligand. J Phys Chem B 2019; 123:10441-10455. [PMID: 31697075 DOI: 10.1021/acs.jpcb.9b07278] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
The CFTR-associated ligand PDZ domain (CALP) binds to the cystic fibrosis transmembrane conductance regulator (CFTR) and mediates lysosomal degradation of mature CFTR. Inhibition of this interaction has been explored as a therapeutic avenue for cystic fibrosis. Previously, we reported the ensemble-based computational design of a novel peptide inhibitor of CALP, which resulted in the most binding-efficient inhibitor to date. This inhibitor, kCAL01, was designed using osprey and evinced significant biological activity in in vitro cell-based assays. Here, we report a crystal structure of kCAL01 bound to CALP and compare structural features against iCAL36, a previously developed inhibitor of CALP. We compute side-chain energy landscapes for each structure to not only enable approximation of binding thermodynamics but also reveal ensemble features that contribute to the comparatively efficient binding of kCAL01. Finally, we compare the previously reported design ensemble for kCAL01 vs the new crystal structure and show that, despite small differences between the design model and crystal structure, significant biophysical features that enhance inhibitor binding are captured in the design ensemble. This suggests not only that ensemble-based design captured thermodynamically significant features observed in vitro, but also that a design eschewing ensembles would miss the kCAL01 sequence entirely.
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Affiliation(s)
- Graham T Holt
- Department of Computer Science , Duke University , Durham , North Carolina 27708 , United States.,Program in Computational Biology and Bioinformatics , Duke University , Durham , North Carolina 27708 , United States
| | - Jonathan D Jou
- Department of Computer Science , Duke University , Durham , North Carolina 27708 , United States
| | - Nicholas P Gill
- Department of Biochemistry & Cell Biology , Geisel School of Medicine at Dartmouth , Hanover , New Hampshire 03755 , United States
| | - Anna U Lowegard
- Department of Computer Science , Duke University , Durham , North Carolina 27708 , United States.,Program in Computational Biology and Bioinformatics , Duke University , Durham , North Carolina 27708 , United States
| | - Jeffrey W Martin
- Department of Computer Science , Duke University , Durham , North Carolina 27708 , United States
| | - Dean R Madden
- Department of Biochemistry & Cell Biology , Geisel School of Medicine at Dartmouth , Hanover , New Hampshire 03755 , United States
| | - Bruce R Donald
- Department of Computer Science , Duke University , Durham , North Carolina 27708 , United States.,Department of Biochemistry , Duke University , Durham , North Carolina 27710 , United States.,Department of Chemistry , Duke University , Durham , North Carolina 27710 , United States
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6
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Reeve SM, Si D, Krucinska J, Yan Y, Viswanathan K, Wang S, Holt GT, Frenkel MS, Ojewole AA, Estrada A, Agabiti SS, Alverson JB, Gibson ND, Priestley ND, Wiemer AJ, Donald BR, Wright DL. Toward Broad Spectrum Dihydrofolate Reductase Inhibitors Targeting Trimethoprim Resistant Enzymes Identified in Clinical Isolates of Methicillin Resistant Staphylococcus aureus. ACS Infect Dis 2019; 5:1896-1906. [PMID: 31565920 DOI: 10.1021/acsinfecdis.9b00222] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The spread of plasmid borne resistance enzymes in clinical Staphylococcus aureus isolates is rendering trimethoprim and iclaprim, both inhibitors of dihydrofolate reductase (DHFR), ineffective. Continued exploitation of these targets will require compounds that can broadly inhibit these resistance-conferring isoforms. Using a structure-based approach, we have developed a novel class of ionized nonclassical antifolates (INCAs) that capture the molecular interactions that have been exclusive to classical antifolates. These modifications allow for a greatly expanded spectrum of activity across these pathogenic DHFR isoforms, while maintaining the ability to penetrate the bacterial cell wall. Using biochemical, structural, and computational methods, we are able to optimize these inhibitors to the conserved active sites of the endogenous and trimethoprim resistant DHFR enzymes. Here, we report a series of INCA compounds that exhibit low nanomolar enzymatic activity and potent cellular activity with human selectivity against a panel of clinically relevant TMP resistant (TMPR) and methicillin resistant Staphylococcus aureus (MRSA) isolates.
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Affiliation(s)
- Stephanie M. Reeve
- Department of Pharmaceutical Sciences, University of Connecticut, 69 N. Eagleville Road, Storrs, Connecticut 06269, United States
| | - Debjani Si
- Department of Pharmaceutical Sciences, University of Connecticut, 69 N. Eagleville Road, Storrs, Connecticut 06269, United States
| | - Jolanta Krucinska
- Department of Pharmaceutical Sciences, University of Connecticut, 69 N. Eagleville Road, Storrs, Connecticut 06269, United States
| | - Yongzhao Yan
- Department of Pharmaceutical Sciences, University of Connecticut, 69 N. Eagleville Road, Storrs, Connecticut 06269, United States
| | - Kishore Viswanathan
- Department of Pharmaceutical Sciences, University of Connecticut, 69 N. Eagleville Road, Storrs, Connecticut 06269, United States
| | - Siyu Wang
- Department of Computer Science, Duke University, 308 Research Drive, Durham, North Carolina 27708, United States
- Program in Computational Biology and Bioinformatics, Duke University, 101 Science Drive, Durham, North Carolina 27708, United States
| | - Graham T. Holt
- Department of Computer Science, Duke University, 308 Research Drive, Durham, North Carolina 27708, United States
- Program in Computational Biology and Bioinformatics, Duke University, 101 Science Drive, Durham, North Carolina 27708, United States
| | - Marcel S. Frenkel
- Department of Biochemistry, Duke University Medical Center, 255 Nanaline H. Duke, Durham, North Carolina 27710, United States
| | - Adegoke A. Ojewole
- Department of Computer Science, Duke University, 308 Research Drive, Durham, North Carolina 27708, United States
- Program in Computational Biology and Bioinformatics, Duke University, 101 Science Drive, Durham, North Carolina 27708, United States
| | - Alexavier Estrada
- Department of Pharmaceutical Sciences, University of Connecticut, 69 N. Eagleville Road, Storrs, Connecticut 06269, United States
| | - Sherry S. Agabiti
- Department of Pharmaceutical Sciences, University of Connecticut, 69 N. Eagleville Road, Storrs, Connecticut 06269, United States
| | - Jeremy B. Alverson
- Department of Chemistry, University of Montana, 32 Campus Drive, Missoula, Montana 59812, United States
| | - Nathan D. Gibson
- Department of Chemistry, University of Montana, 32 Campus Drive, Missoula, Montana 59812, United States
| | - Nigel D. Priestley
- Department of Chemistry, University of Montana, 32 Campus Drive, Missoula, Montana 59812, United States
| | - Andrew J. Wiemer
- Department of Pharmaceutical Sciences, University of Connecticut, 69 N. Eagleville Road, Storrs, Connecticut 06269, United States
| | - Bruce R. Donald
- Department of Computer Science, Duke University, 308 Research Drive, Durham, North Carolina 27708, United States
- Department of Biochemistry, Duke University Medical Center, 255 Nanaline H. Duke, Durham, North Carolina 27710, United States
- Department of Chemistry, Duke University, 124 Science Drive, Durham, North Carolina 27708, United States
| | - Dennis L. Wright
- Department of Pharmaceutical Sciences, University of Connecticut, 69 N. Eagleville Road, Storrs, Connecticut 06269, United States
- Department of Chemistry, University of Connecticut, 55 N. Eagleville Road, Storrs, Connecticut 06269, United States
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7
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Hallen MA, Martin JW, Ojewole A, Jou JD, Lowegard AU, Frenkel MS, Gainza P, Nisonoff HM, Mukund A, Wang S, Holt GT, Zhou D, Dowd E, Donald BR. OSPREY 3.0: Open-source protein redesign for you, with powerful new features. J Comput Chem 2018; 39:2494-2507. [PMID: 30368845 PMCID: PMC6391056 DOI: 10.1002/jcc.25522] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Accepted: 06/14/2018] [Indexed: 12/14/2022]
Abstract
We present osprey 3.0, a new and greatly improved release of the osprey protein design software. Osprey 3.0 features a convenient new Python interface, which greatly improves its ease of use. It is over two orders of magnitude faster than previous versions of osprey when running the same algorithms on the same hardware. Moreover, osprey 3.0 includes several new algorithms, which introduce substantial speedups as well as improved biophysical modeling. It also includes GPU support, which provides an additional speedup of over an order of magnitude. Like previous versions of osprey, osprey 3.0 offers a unique package of advantages over other design software, including provable design algorithms that account for continuous flexibility during design and model conformational entropy. Finally, we show here empirically that osprey 3.0 accurately predicts the effect of mutations on protein-protein binding. Osprey 3.0 is available at http://www.cs.duke.edu/donaldlab/osprey.php as free and open-source software. © 2018 Wiley Periodicals, Inc.
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Affiliation(s)
- Mark A. Hallen
- Department of Computer Science, Duke University, Durham, NC
27708
- Toyota Technological Institute at Chicago, Chicago, IL
60637
| | | | - Adegoke Ojewole
- Program in Computational Biology and Bioinformatics, Duke
University Medical Center, Durham, NC 27710
| | - Jonathan D. Jou
- Department of Computer Science, Duke University, Durham, NC
27708
| | - Anna U. Lowegard
- Program in Computational Biology and Bioinformatics, Duke
University Medical Center, Durham, NC 27710
| | - Marcel S. Frenkel
- Department of Biochemistry, Duke University Medical Center,
Durham, NC 27710
| | - Pablo Gainza
- Department of Computer Science, Duke University, Durham, NC
27708
| | | | - Aditya Mukund
- Department of Computer Science, Duke University, Durham, NC
27708
| | - Siyu Wang
- Program in Computational Biology and Bioinformatics, Duke
University Medical Center, Durham, NC 27710
| | - Graham T. Holt
- Program in Computational Biology and Bioinformatics, Duke
University Medical Center, Durham, NC 27710
| | - David Zhou
- Department of Computer Science, Duke University, Durham, NC
27708
| | - Elizabeth Dowd
- Department of Computer Science, Duke University, Durham, NC
27708
| | - Bruce R. Donald
- Department of Computer Science, Duke University, Durham, NC
27708
- Department of Chemistry, Duke University, Durham, NC
27708
- Department of Biochemistry, Duke University Medical Center,
Durham, NC 27710
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8
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de Juan-Sanz J, Holt GT, Schreiter ER, de Juan F, Kim DS, Ryan TA. Axonal Endoplasmic Reticulum Ca 2+ Content Controls Release Probability in CNS Nerve Terminals. Neuron 2017; 93:867-881.e6. [PMID: 28162809 DOI: 10.1016/j.neuron.2017.01.010] [Citation(s) in RCA: 170] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2016] [Revised: 11/23/2016] [Accepted: 01/13/2017] [Indexed: 12/14/2022]
Abstract
Although the endoplasmic reticulum (ER) extends throughout axons and axonal ER dysfunction is implicated in numerous neurological diseases, its role at nerve terminals is poorly understood. We developed novel genetically encoded ER-targeted low-affinity Ca2+ indicators optimized for examining axonal ER Ca2+. Our experiments revealed that presynaptic function is tightly controlled by ER Ca2+ content. We found that neuronal activity drives net Ca2+ uptake into presynaptic ER although this activity does not contribute significantly to shaping cytosolic Ca2+ except during prolonged repetitive firing. In contrast, we found that axonal ER acts as an actuator of plasma membrane (PM) function: [Ca2+]ER controls STIM1 activation in presynaptic terminals, which results in the local modulation of presynaptic function, impacting activity-driven Ca2+ entry and release probability. These experiments reveal a critical role of presynaptic ER in the control of neurotransmitter release and will help frame future investigations into the molecular basis of ER-driven neuronal disease states.
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Affiliation(s)
- Jaime de Juan-Sanz
- Department of Biochemistry, Weill Cornell Medicine, New York, NY 10065, USA
| | - Graham T Holt
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Eric R Schreiter
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Fernando de Juan
- Department of Physics, University of Oxford, Oxford, OX1 3NP, UK
| | - Douglas S Kim
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Timothy A Ryan
- Department of Biochemistry, Weill Cornell Medicine, New York, NY 10065, USA.
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9
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Dana H, Mohar B, Sun Y, Narayan S, Gordus A, Hasseman JP, Tsegaye G, Holt GT, Hu A, Walpita D, Patel R, Macklin JJ, Bargmann CI, Ahrens MB, Schreiter ER, Jayaraman V, Looger LL, Svoboda K, Kim DS. Sensitive red protein calcium indicators for imaging neural activity. eLife 2016; 5:e12727. [PMID: 27011354 PMCID: PMC4846379 DOI: 10.7554/elife.12727] [Citation(s) in RCA: 579] [Impact Index Per Article: 72.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2015] [Accepted: 03/24/2016] [Indexed: 12/18/2022] Open
Abstract
Genetically encoded calcium indicators (GECIs) allow measurement of activity in large populations of neurons and in small neuronal compartments, over times of milliseconds to months. Although GFP-based GECIs are widely used for in vivo neurophysiology, GECIs with red-shifted excitation and emission spectra have advantages for in vivo imaging because of reduced scattering and absorption in tissue, and a consequent reduction in phototoxicity. However, current red GECIs are inferior to the state-of-the-art GFP-based GCaMP6 indicators for detecting and quantifying neural activity. Here we present improved red GECIs based on mRuby (jRCaMP1a, b) and mApple (jRGECO1a), with sensitivity comparable to GCaMP6. We characterized the performance of the new red GECIs in cultured neurons and in mouse, Drosophila, zebrafish and C. elegans in vivo. Red GECIs facilitate deep-tissue imaging, dual-color imaging together with GFP-based reporters, and the use of optogenetics in combination with calcium imaging.
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Affiliation(s)
- Hod Dana
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Boaz Mohar
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
- Weizmann Institute of Science, Rehovot, Israel
| | - Yi Sun
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Sujatha Narayan
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Andrew Gordus
- Howard Hughes Medical Institute, The Rockefeller University, New York, United States
| | - Jeremy P Hasseman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Getahun Tsegaye
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Graham T Holt
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Amy Hu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Deepika Walpita
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Ronak Patel
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - John J Macklin
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Cornelia I Bargmann
- Howard Hughes Medical Institute, The Rockefeller University, New York, United States
| | - Misha B Ahrens
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Eric R Schreiter
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Vivek Jayaraman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Loren L Looger
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Karel Svoboda
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Douglas S Kim
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
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10
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Dana H, Mohar B, Sun Y, Narayan S, Gordus A, Hasseman JP, Tsegaye G, Holt GT, Hu A, Walpita D, Patel R, Macklin JJ, Bargmann CI, Ahrens MB, Schreiter ER, Jayaraman V, Looger LL, Svoboda K, Kim DS. Sensitive red protein calcium indicators for imaging neural activity. eLife 2016; 5:e12727. [PMID: 27011354 DOI: 10.7554/elife.1272] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2015] [Accepted: 03/24/2016] [Indexed: 05/27/2023] Open
Abstract
Genetically encoded calcium indicators (GECIs) allow measurement of activity in large populations of neurons and in small neuronal compartments, over times of milliseconds to months. Although GFP-based GECIs are widely used for in vivo neurophysiology, GECIs with red-shifted excitation and emission spectra have advantages for in vivo imaging because of reduced scattering and absorption in tissue, and a consequent reduction in phototoxicity. However, current red GECIs are inferior to the state-of-the-art GFP-based GCaMP6 indicators for detecting and quantifying neural activity. Here we present improved red GECIs based on mRuby (jRCaMP1a, b) and mApple (jRGECO1a), with sensitivity comparable to GCaMP6. We characterized the performance of the new red GECIs in cultured neurons and in mouse, Drosophila, zebrafish and C. elegans in vivo. Red GECIs facilitate deep-tissue imaging, dual-color imaging together with GFP-based reporters, and the use of optogenetics in combination with calcium imaging.
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Affiliation(s)
- Hod Dana
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Boaz Mohar
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
- Weizmann Institute of Science, Rehovot, Israel
| | - Yi Sun
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Sujatha Narayan
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Andrew Gordus
- Howard Hughes Medical Institute, The Rockefeller University, New York, United States
| | - Jeremy P Hasseman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Getahun Tsegaye
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Graham T Holt
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Amy Hu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Deepika Walpita
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Ronak Patel
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - John J Macklin
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Cornelia I Bargmann
- Howard Hughes Medical Institute, The Rockefeller University, New York, United States
| | - Misha B Ahrens
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Eric R Schreiter
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Vivek Jayaraman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Loren L Looger
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Karel Svoboda
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Douglas S Kim
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
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11
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Dana H, Mohar B, Sun Y, Narayan S, Gordus A, Hasseman JP, Tsegaye G, Holt GT, Hu A, Walpita D, Patel R, Macklin JJ, Bargmann CI, Ahrens MB, Schreiter ER, Jayaraman V, Looger LL, Svoboda K, Kim DS. Sensitive red protein calcium indicators for imaging neural activity. eLife 2016; 5. [PMID: 27011354 DOI: 10.7554/elife.12727.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2015] [Accepted: 03/24/2016] [Indexed: 05/20/2023] Open
Abstract
Genetically encoded calcium indicators (GECIs) allow measurement of activity in large populations of neurons and in small neuronal compartments, over times of milliseconds to months. Although GFP-based GECIs are widely used for in vivo neurophysiology, GECIs with red-shifted excitation and emission spectra have advantages for in vivo imaging because of reduced scattering and absorption in tissue, and a consequent reduction in phototoxicity. However, current red GECIs are inferior to the state-of-the-art GFP-based GCaMP6 indicators for detecting and quantifying neural activity. Here we present improved red GECIs based on mRuby (jRCaMP1a, b) and mApple (jRGECO1a), with sensitivity comparable to GCaMP6. We characterized the performance of the new red GECIs in cultured neurons and in mouse, Drosophila, zebrafish and C. elegans in vivo. Red GECIs facilitate deep-tissue imaging, dual-color imaging together with GFP-based reporters, and the use of optogenetics in combination with calcium imaging.
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Affiliation(s)
- Hod Dana
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Boaz Mohar
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
- Weizmann Institute of Science, Rehovot, Israel
| | - Yi Sun
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Sujatha Narayan
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Andrew Gordus
- Howard Hughes Medical Institute, The Rockefeller University, New York, United States
| | - Jeremy P Hasseman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Getahun Tsegaye
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Graham T Holt
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Amy Hu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Deepika Walpita
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Ronak Patel
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - John J Macklin
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Cornelia I Bargmann
- Howard Hughes Medical Institute, The Rockefeller University, New York, United States
| | - Misha B Ahrens
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Eric R Schreiter
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Vivek Jayaraman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Loren L Looger
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Karel Svoboda
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Douglas S Kim
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
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12
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Henderson MJ, Baldwin HA, Werley CA, Boccardo S, Whitaker LR, Yan X, Holt GT, Schreiter ER, Looger LL, Cohen AE, Kim DS, Harvey BK. A Low Affinity GCaMP3 Variant (GCaMPer) for Imaging the Endoplasmic Reticulum Calcium Store. PLoS One 2015; 10:e0139273. [PMID: 26451944 PMCID: PMC4599735 DOI: 10.1371/journal.pone.0139273] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2015] [Accepted: 09/09/2015] [Indexed: 12/22/2022] Open
Abstract
Endoplasmic reticulum calcium homeostasis is critical for cellular functions and is disrupted in diverse pathologies including neurodegeneration and cardiovascular disease. Owing to the high concentration of calcium within the ER, studying this subcellular compartment requires tools that are optimized for these conditions. To develop a single-fluorophore genetically encoded calcium indicator for this organelle, we targeted a low affinity variant of GCaMP3 to the ER lumen (GCaMPer (10.19)). A set of viral vectors was constructed to express GCaMPer in human neuroblastoma cells, rat primary cortical neurons, and human induced pluripotent stem cell-derived cardiomyocytes. We observed dynamic changes in GCaMPer (10.19) fluorescence in response to pharmacologic manipulations of the ER calcium store. Additionally, periodic calcium efflux from the ER was observed during spontaneous beating of cardiomyocytes. GCaMPer (10.19) has utility in imaging ER calcium in living cells and providing insight into luminal calcium dynamics under physiologic and pathologic states.
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Affiliation(s)
- Mark J. Henderson
- National Institute on Drug Abuse, National Institutes of Health, 251 Bayview Blvd, Baltimore, Maryland, 21224, United States of America
- * E-mail: (MJH); (BKH)
| | - Heather A. Baldwin
- National Institute on Drug Abuse, National Institutes of Health, 251 Bayview Blvd, Baltimore, Maryland, 21224, United States of America
| | - Christopher A. Werley
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, 02138, United States of America
| | - Stefano Boccardo
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, 02138, United States of America
| | - Leslie R. Whitaker
- National Institute on Drug Abuse, National Institutes of Health, 251 Bayview Blvd, Baltimore, Maryland, 21224, United States of America
| | - Xiaokang Yan
- National Institute on Drug Abuse, National Institutes of Health, 251 Bayview Blvd, Baltimore, Maryland, 21224, United States of America
| | - Graham T. Holt
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, Virginia, 20147, United States of America
| | - Eric R. Schreiter
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, Virginia, 20147, United States of America
| | - Loren L. Looger
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, Virginia, 20147, United States of America
| | - Adam E. Cohen
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, 02138, United States of America
- Department of Physics, Harvard University, Cambridge, Massachusetts, 02138, United States of America
- Harvard Stem Cell Institute, Harvard University, Cambridge, Massachusetts, 02138, United States of America
- Howard Hughes Medical Institute, Harvard University, Cambridge, Massachusetts, 02138, United States of America
| | - Douglas S. Kim
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, Virginia, 20147, United States of America
| | - Brandon K. Harvey
- National Institute on Drug Abuse, National Institutes of Health, 251 Bayview Blvd, Baltimore, Maryland, 21224, United States of America
- * E-mail: (MJH); (BKH)
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