1
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Trifan A, Gorgun D, Salim M, Li Z, Brace A, Zvyagin M, Ma H, Clyde A, Clark D, Hardy DJ, Burnley T, Huang L, McCalpin J, Emani M, Yoo H, Yin J, Tsaris A, Subbiah V, Raza T, Liu J, Trebesch N, Wells G, Mysore V, Gibbs T, Phillips J, Chennubhotla SC, Foster I, Stevens R, Anandkumar A, Vishwanath V, Stone JE, Tajkhorshid E, A. Harris S, Ramanathan A. Intelligent resolution: Integrating Cryo-EM with AI-driven multi-resolution simulations to observe the severe acute respiratory syndrome coronavirus-2 replication-transcription machinery in action. THE INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2022; 36:603-623. [PMID: 38464362 PMCID: PMC10923581 DOI: 10.1177/10943420221113513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replication transcription complex (RTC) is a multi-domain protein responsible for replicating and transcribing the viral mRNA inside a human cell. Attacking RTC function with pharmaceutical compounds is a pathway to treating COVID-19. Conventional tools, e.g., cryo-electron microscopy and all-atom molecular dynamics (AAMD), do not provide sufficiently high resolution or timescale to capture important dynamics of this molecular machine. Consequently, we develop an innovative workflow that bridges the gap between these resolutions, using mesoscale fluctuating finite element analysis (FFEA) continuum simulations and a hierarchy of AI-methods that continually learn and infer features for maintaining consistency between AAMD and FFEA simulations. We leverage a multi-site distributed workflow manager to orchestrate AI, FFEA, and AAMD jobs, providing optimal resource utilization across HPC centers. Our study provides unprecedented access to study the SARS-CoV-2 RTC machinery, while providing general capability for AI-enabled multi-resolution simulations at scale.
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Affiliation(s)
- Anda Trifan
- Argonne National Laboratory
- University of Illinois Urbana-Champaign
| | - Defne Gorgun
- Argonne National Laboratory
- University of Illinois Urbana-Champaign
| | | | | | | | | | | | - Austin Clyde
- Argonne National Laboratory
- University of Chicago
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Ian Foster
- Argonne National Laboratory
- University of Chicago
| | - Rick Stevens
- Argonne National Laboratory
- University of Chicago
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2
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Vermaas JV, Mayne CG, Shinn E, Tajkhorshid E. Assembly and Analysis of Cell-Scale Membrane Envelopes. J Chem Inf Model 2022; 62:602-617. [PMID: 34910495 PMCID: PMC8903035 DOI: 10.1021/acs.jcim.1c01050] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
The march toward exascale computing will enable routine molecular simulation of larger and more complex systems, for example, simulation of entire viral particles, on the scale of approximately billions of atoms─a simulation size commensurate with a small bacterial cell. Anticipating the future hardware capabilities that will enable this type of research and paralleling advances in experimental structural biology, efforts are currently underway to develop software tools, procedures, and workflows for constructing cell-scale structures. Herein, we describe our efforts in developing and implementing an efficient and robust workflow for construction of cell-scale membrane envelopes and embedding membrane proteins into them. A new approach for construction of massive membrane structures that are stable during the simulations is built on implementing a subtractive assembly technique coupled with the development of a structure concatenation tool (fastmerge), which eliminates overlapping elements based on volumetric criteria rather than adding successive molecules to the simulation system. Using this approach, we have constructed two "protocells" consisting of MARTINI coarse-grained beads to represent cellular membranes, one the size of a cellular organelle and another the size of a small bacterial cell. The membrane envelopes constructed here remain whole during the molecular dynamics simulations performed and exhibit water flux only through specific proteins, demonstrating the success of our methodology in creating tight cell-like membrane compartments. Extended simulations of these cell-scale structures highlight the propensity for nonspecific interactions between adjacent membrane proteins leading to the formation of protein microclusters on the cell surface, an insight uniquely enabled by the scale of the simulations. We anticipate that the experiences and best practices presented here will form the basis for the next generation of cell-scale models, which will begin to address the addition of soluble proteins, nucleic acids, and small molecules essential to the function of a cell.
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Affiliation(s)
- Josh V. Vermaas
- Biosciences Center, National Renewable Energy Laboratory, Golden, CO 80401,;
| | - Christopher G. Mayne
- Theoretical and Computational Biophysics Group, NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute for Advanced Science and Technology, Department of Biochemistry, and Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801
| | - Eric Shinn
- Theoretical and Computational Biophysics Group, NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute for Advanced Science and Technology, Department of Biochemistry, and Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801
| | - Emad Tajkhorshid
- Theoretical and Computational Biophysics Group, NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute for Advanced Science and Technology, Department of Biochemistry, and Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801,;
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3
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Lanrezac A, Férey N, Baaden M. Wielding the power of interactive molecular simulations. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2021. [DOI: 10.1002/wcms.1594] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- André Lanrezac
- CNRS, Laboratoire de Biochimie Théorique Université de Paris Paris France
| | - Nicolas Férey
- CNRS, Laboratoire interdisciplinaire des sciences du numérique Université Paris‐Saclay Orsay France
| | - Marc Baaden
- CNRS, Laboratoire de Biochimie Théorique Université de Paris Paris France
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4
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Ni T, Zhu Y, Yang Z, Xu C, Chaban Y, Nesterova T, Ning J, Böcking T, Parker MW, Monnie C, Ahn J, Perilla JR, Zhang P. Structure of native HIV-1 cores and their interactions with IP6 and CypA. SCIENCE ADVANCES 2021; 7:eabj5715. [PMID: 34797722 PMCID: PMC8604400 DOI: 10.1126/sciadv.abj5715] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 10/01/2021] [Indexed: 05/24/2023]
Abstract
The viral capsid plays essential roles in HIV replication and is a major platform engaging host factors. To overcome challenges in study native capsid structure, we used the perfringolysin O to perforate the membrane of HIV-1 particles, thus allowing host proteins and small molecules to access the native capsid while improving cryo–electron microscopy image quality. Using cryo–electron tomography and subtomogram averaging, we determined the structures of native capsomers in the presence and absence of inositol hexakisphosphate (IP6) and cyclophilin A and constructed an all-atom model of a complete HIV-1 capsid. Our structures reveal two IP6 binding sites and modes of cyclophilin A interactions. Free energy calculations substantiate the two binding sites at R18 and K25 and further show a prohibitive energy barrier for IP6 to pass through the pentamer. Our results demonstrate that perfringolysin O perforation is a valuable tool for structural analyses of enveloped virus capsids and interactions with host cell factors.
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Affiliation(s)
- Tao Ni
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Yanan Zhu
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Zhengyi Yang
- Electron Bio-Imaging Centre, Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, UK
| | - Chaoyi Xu
- Department of Chemistry and Biochemistry, University of Delaware, Newark, DE, USA
| | - Yuriy Chaban
- Electron Bio-Imaging Centre, Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, UK
| | - Tanya Nesterova
- Department of Chemistry and Biochemistry, University of Delaware, Newark, DE, USA
| | - Jiying Ning
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Till Böcking
- EMBL Australia Node in Single Molecule Science and ARC Centre of Excellence in Advanced Molecular Imaging, School of Medical Sciences, UNSW, Sydney, Australia
| | - Michael W. Parker
- Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria 3010, Australia
- St. Vincent’s Institute of Medical Research, Fitzroy, Victoria 3065, Australia
| | - Christina Monnie
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jinwoo Ahn
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Juan R. Perilla
- Department of Chemistry and Biochemistry, University of Delaware, Newark, DE, USA
| | - Peijun Zhang
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
- Electron Bio-Imaging Centre, Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, UK
- Chinese Academy of Medical Sciences Oxford Institute, University of Oxford, Oxford OX3 7BN, UK
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5
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Hardy DJ, Isralewitz B, Stone JE, Tajkhorshid E. Lessons Learned from Responsive Molecular Dynamics Studies of the COVID-19 Virus. PROCEEDINGS OF URGENTHPC 2021 : THE THIRD INTERNATIONAL WORKSHOP ON HPC FOR URGENT DECISION MAKING 2021; 2021:1-10. [PMID: 36573923 PMCID: PMC9788906 DOI: 10.1109/urgenthpc54802.2021.00006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Over the past 18 months, the need to perform atomic detail molecular dynamics simulations of the SARS-CoV-2 virion, its spike protein, and other structures related to the viral infection cycle has led biomedical researchers worldwide to urgently seek out all available biomolecular structure information, appropriate molecular modeling and simulation software, and the necessary computing resources to conduct their work. We describe our experiences from several COVID-19 research collaborations and the challenges they presented in terms of our molecular modeling software development and support efforts, our laboratory's local computing environment, and our scientists' use of non-traditional HPC hardware platforms such as public clouds for large scale parallel molecular dynamics simulations.
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Affiliation(s)
- David J. Hardy
- Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign Urbana, Illinois, USA
| | - Barry Isralewitz
- Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign Urbana, Illinois, USA
| | - John E. Stone
- Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign Urbana, Illinois, USA
| | - Emad Tajkhorshid
- Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign Urbana, Illinois, USA
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6
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Roe DR, Brooks BR. Improving the speed of volumetric density map generation via cubic spline interpolation. J Mol Graph Model 2021; 104:107832. [PMID: 33444979 DOI: 10.1016/j.jmgm.2021.107832] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 12/29/2020] [Accepted: 12/29/2020] [Indexed: 10/22/2022]
Abstract
Visualizing data generated from molecular dynamics simulations can be difficult, particularly when there can be thousands to millions of trajectory frames. The creation of a 3D grid of atomic density (i.e. a volumetric map) is one way to easily view the long-time average behavior of a system. One way to generate volumetric maps is by approximating each atom with a Gaussian function centered on that atom and spread over neighboring grid cells. However the calculation of the Gaussian function requires evaluation of the exponential function, which is computationally costly. Here we report on speeding up the calculation of volumetric maps from molecular dynamics trajectory data by replacing the expensive exponential function evaluation with an approximation using interpolating cubic splines. We also discuss the errors involved in this approximation, and recommend settings for volumetric map creation based on this.
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Affiliation(s)
- Daniel R Roe
- Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
| | - Bernard R Brooks
- Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
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7
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Xu C, Fischer DK, Rankovic S, Li W, Dick RA, Runge B, Zadorozhnyi R, Ahn J, Aiken C, Polenova T, Engelman AN, Ambrose Z, Rousso I, Perilla JR. Permeability of the HIV-1 capsid to metabolites modulates viral DNA synthesis. PLoS Biol 2020; 18:e3001015. [PMID: 33332391 PMCID: PMC7775124 DOI: 10.1371/journal.pbio.3001015] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 12/31/2020] [Accepted: 11/26/2020] [Indexed: 02/07/2023] Open
Abstract
Reverse transcription, an essential event in the HIV-1 life cycle, requires deoxynucleotide triphosphates (dNTPs) to fuel DNA synthesis, thus requiring penetration of dNTPs into the viral capsid. The central cavity of the capsid protein (CA) hexamer reveals itself as a plausible channel that allows the passage of dNTPs into assembled capsids. Nevertheless, the molecular mechanism of nucleotide import into the capsid remains unknown. Employing all-atom molecular dynamics (MD) simulations, we established that cooperative binding between nucleotides inside a CA hexamer cavity results in energetically favorable conditions for passive translocation of dNTPs into the HIV-1 capsid. Furthermore, binding of the host cell metabolite inositol hexakisphosphate (IP6) enhances dNTP import, while binding of synthesized molecules like benzenehexacarboxylic acid (BHC) inhibits it. The enhancing effect on reverse transcription by IP6 and the consequences of interactions between CA and nucleotides were corroborated using atomic force microscopy, transmission electron microscopy, and virological assays. Collectively, our results provide an atomistic description of the permeability of the HIV-1 capsid to small molecules and reveal a novel mechanism for the involvement of metabolites in HIV-1 capsid stabilization, nucleotide import, and reverse transcription. This study shows that the HIV-1 capsid protein, in addition to its structural role, regulates reverse transcription, an essential metabolic process of the virus, by mediating the import of nucleotides. In addition, host cell metabolites such as inositol phosphates are recruited by the capsid to regulate viral DNA synthesis.
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Affiliation(s)
- Chaoyi Xu
- Department of Chemistry and Biochemistry, University of Delaware, Newark, Delaware, United States of America
- Pittsburgh Center for HIV Protein Interactions (PCHPI), University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
| | - Douglas K. Fischer
- Pittsburgh Center for HIV Protein Interactions (PCHPI), University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
| | - Sanela Rankovic
- Department of Physiology and Cell Biology, Ben-Gurion University of Negev, Beer Sheva, Israel
| | - Wen Li
- Pittsburgh Center for HIV Protein Interactions (PCHPI), University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
- Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Robert A. Dick
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York, United States of America
| | - Brent Runge
- Department of Chemistry and Biochemistry, University of Delaware, Newark, Delaware, United States of America
- Pittsburgh Center for HIV Protein Interactions (PCHPI), University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
| | - Roman Zadorozhnyi
- Department of Chemistry and Biochemistry, University of Delaware, Newark, Delaware, United States of America
- Pittsburgh Center for HIV Protein Interactions (PCHPI), University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
| | - Jinwoo Ahn
- Pittsburgh Center for HIV Protein Interactions (PCHPI), University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
| | - Christopher Aiken
- Pittsburgh Center for HIV Protein Interactions (PCHPI), University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Tatyana Polenova
- Department of Chemistry and Biochemistry, University of Delaware, Newark, Delaware, United States of America
- Pittsburgh Center for HIV Protein Interactions (PCHPI), University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
| | - Alan N. Engelman
- Pittsburgh Center for HIV Protein Interactions (PCHPI), University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
- Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Zandrea Ambrose
- Pittsburgh Center for HIV Protein Interactions (PCHPI), University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
- * E-mail: (ZA); (IR); (JRP)
| | - Itay Rousso
- Department of Physiology and Cell Biology, Ben-Gurion University of Negev, Beer Sheva, Israel
- * E-mail: (ZA); (IR); (JRP)
| | - Juan R. Perilla
- Department of Chemistry and Biochemistry, University of Delaware, Newark, Delaware, United States of America
- Pittsburgh Center for HIV Protein Interactions (PCHPI), University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
- * E-mail: (ZA); (IR); (JRP)
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8
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Decherchi S, Spitaleri A, Stone J, Rocchia W. NanoShaper-VMD interface: computing and visualizing surfaces, pockets and channels in molecular systems. Bioinformatics 2020; 35:1241-1243. [PMID: 30169777 DOI: 10.1093/bioinformatics/bty761] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2018] [Revised: 07/31/2018] [Accepted: 08/30/2018] [Indexed: 12/27/2022] Open
Abstract
SUMMARY NanoShaper is a program specifically aiming the construction and analysis of the molecular surface of nanoscopic systems. It uses ray-casting for parallelism and it performs analytical computations whenever possible to maximize robustness and accuracy of the approach. Among the other features, NanoShaper provides volume, surface area, including that of internal cavities, for any considered molecular system. It identifies pockets via a very intuitive definition based on the concept of probe radius, intrinsic to the definition of the solvent excluded surface. We show here that, with a suitable choice of the parameters, the same approach can also permit the visualisation of molecular channels. NanoShaper has now been interfaced with the widely used molecular visualization software VMD, further enriching its already well furnished toolset. AVAILABILITY AND IMPLEMENTATION VMD is available at http://www.ks.uiuc.edu/Research/vmd/. NanoShaper, its documentation, tutorials and supporting programs are available at http://concept.iit.it/downloads. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Sergio Decherchi
- CONCEPT Lab, Istituto Italiano di Tecnologia, Genoa, Italy.,BiKi Technologies s.r.l., Genova, Italy
| | | | - John Stone
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Walter Rocchia
- CONCEPT Lab, Istituto Italiano di Tecnologia, Genoa, Italy
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9
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Cassidy CK, Himes BA, Sun D, Ma J, Zhao G, Parkinson JS, Stansfeld PJ, Luthey-Schulten Z, Zhang P. Structure and dynamics of the E. coli chemotaxis core signaling complex by cryo-electron tomography and molecular simulations. Commun Biol 2020; 3:24. [PMID: 31925330 PMCID: PMC6954272 DOI: 10.1038/s42003-019-0748-0] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Accepted: 12/19/2019] [Indexed: 01/08/2023] Open
Abstract
To enable the processing of chemical gradients, chemotactic bacteria possess large arrays of transmembrane chemoreceptors, the histidine kinase CheA, and the adaptor protein CheW, organized as coupled core-signaling units (CSU). Despite decades of study, important questions surrounding the molecular mechanisms of sensory signal transduction remain unresolved, owing especially to the lack of a high-resolution CSU structure. Here, we use cryo-electron tomography and sub-tomogram averaging to determine a structure of the Escherichia coli CSU at sub-nanometer resolution. Based on our experimental data, we use molecular simulations to construct an atomistic model of the CSU, enabling a detailed characterization of CheA conformational dynamics in its native structural context. We identify multiple, distinct conformations of the critical P4 domain as well as asymmetries in the localization of the P3 bundle, offering several novel insights into the CheA signaling mechanism.
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Affiliation(s)
- C Keith Cassidy
- Department of Biochemistry, University of Oxford, Oxford, OX1 3QU, UK.
- Department of Physics and Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
| | - Benjamin A Himes
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA
| | - Dapeng Sun
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA
| | - Jun Ma
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA
| | - Gongpu Zhao
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA
| | - John S Parkinson
- School of Biological Sciences, University of Utah, Salt Lake City, UT, 84112, USA
| | - Phillip J Stansfeld
- Department of Biochemistry, University of Oxford, Oxford, OX1 3QU, UK
- School of Life Sciences & Department of Chemistry, University of Warwick, Coventry, CV4 7AL, UK
| | - Zaida Luthey-Schulten
- Department of Physics and Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Chemistry and Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Peijun Zhang
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA.
- Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK.
- Electron Bio-Imaging Centre, Diamond Light Sources, Harwell Science and Innovation Campus, Didcot, OX11 0DE, UK.
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10
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Kidmose RT, Juhl J, Nissen P, Boesen T, Karlsen JL, Pedersen BP. Namdinator - automatic molecular dynamics flexible fitting of structural models into cryo-EM and crystallography experimental maps. IUCRJ 2019; 6:526-531. [PMID: 31316797 PMCID: PMC6608625 DOI: 10.1107/s2052252519007619] [Citation(s) in RCA: 189] [Impact Index Per Article: 37.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2019] [Accepted: 05/25/2019] [Indexed: 05/20/2023]
Abstract
Model building into experimental maps is a key element of structural biology, but can be both time consuming and error prone for low-resolution maps. Here we present Namdinator, an easy-to-use tool that enables the user to run a molecular dynamics flexible fitting simulation followed by real-space refinement in an automated manner through a pipeline system. Namdinator will modify an atomic model to fit within cryo-EM or crystallography density maps, and can be used advantageously for both the initial fitting of models, and for a geometrical optimization step to correct outliers, clashes and other model problems. We have benchmarked Namdinator against 39 deposited cryo-EM models and maps, and observe model improvements in 34 of these cases (87%). Clashes between atoms were reduced, and the model-to-map fit and overall model geometry were improved, in several cases substantially. We show that Namdinator is able to model large-scale conformational changes compared to the starting model. Namdinator is a fast and easy tool for structural model builders at all skill levels. Namdinator is available as a web service (https://namdinator.au.dk), or it can be run locally as a command-line tool.
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Affiliation(s)
- Rune Thomas Kidmose
- Centre for Structural Biology, Department of Molecular Biology and Genetics, Aarhus University, Gustav Wieds Vej 10C, Aarhus, DK-8000, Denmark
| | - Jonathan Juhl
- Centre for Structural Biology, Department of Molecular Biology and Genetics, Aarhus University, Gustav Wieds Vej 10C, Aarhus, DK-8000, Denmark
| | - Poul Nissen
- Centre for Structural Biology, Department of Molecular Biology and Genetics, Aarhus University, Gustav Wieds Vej 10C, Aarhus, DK-8000, Denmark
| | - Thomas Boesen
- Centre for Structural Biology, Department of Molecular Biology and Genetics, Aarhus University, Gustav Wieds Vej 10C, Aarhus, DK-8000, Denmark
| | - Jesper Lykkegaard Karlsen
- Centre for Structural Biology, Department of Molecular Biology and Genetics, Aarhus University, Gustav Wieds Vej 10C, Aarhus, DK-8000, Denmark
- Correspondence e-mail: ,
| | - Bjørn Panyella Pedersen
- Centre for Structural Biology, Department of Molecular Biology and Genetics, Aarhus University, Gustav Wieds Vej 10C, Aarhus, DK-8000, Denmark
- Correspondence e-mail: ,
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11
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Mori T, Kulik M, Miyashita O, Jung J, Tama F, Sugita Y. Acceleration of cryo-EM Flexible Fitting for Large Biomolecular Systems by Efficient Space Partitioning. Structure 2018; 27:161-174.e3. [PMID: 30344106 DOI: 10.1016/j.str.2018.09.004] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Revised: 06/22/2018] [Accepted: 09/18/2018] [Indexed: 01/21/2023]
Abstract
Flexible fitting is a powerful technique to build the 3D structures of biomolecules from cryoelectron microscopy (cryo-EM) density maps. One popular method is a cross-correlation coefficient-based approach, where the molecular dynamics (MD) simulation is carried out with the biasing potential that includes the cross-correlation coefficient between the experimental and simulated density maps. Here, we propose efficient parallelization schemes for the calculation of the cross-correlation coefficient to accelerate flexible fitting. Our schemes are tested for small, medium, and large biomolecules using CPU and hybrid CPU + GPU architectures. The scheme for the atomic decomposition MD is suitable for small proteins such as Ca2+-ATPase with the all-atom Go model, while that for the domain decomposition MD is better for larger systems such as ribosome with the all-atom Go or the all-atom explicit solvent models. Our methods allow flexible fitting for various biomolecules with reasonable computational cost. This approach also connects high-resolution structure refinements with investigation of protein structure-function relationship.
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Affiliation(s)
- Takaharu Mori
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan
| | - Marta Kulik
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan
| | - Osamu Miyashita
- RIKEN Center for Computational Science, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Jaewoon Jung
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan; RIKEN Center for Computational Science, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Florence Tama
- RIKEN Center for Computational Science, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan; Department of Physics, Graduate School of Science, and Institute of Transformative Bio-Molecules, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8602, Japan
| | - Yuji Sugita
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan; RIKEN Center for Computational Science, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan; RIKEN Center for Biosystems Dynamics Research, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.
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12
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Cassidy CK, Himes BA, Luthey-Schulten Z, Zhang P. CryoEM-based hybrid modeling approaches for structure determination. Curr Opin Microbiol 2018; 43:14-23. [PMID: 29107896 PMCID: PMC5934336 DOI: 10.1016/j.mib.2017.10.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2017] [Revised: 10/04/2017] [Accepted: 10/09/2017] [Indexed: 12/21/2022]
Abstract
Recent advances in cryo-electron microscopy (cryoEM) have dramatically improved the resolutions at which vitrified biological specimens can be studied, revealing new structural and mechanistic insights over a broad range of spatial scales. Bolstered by these advances, much effort has been directed toward the development of hybrid modeling methodologies for the construction and refinement of high-fidelity atomistic models from cryoEM data. In this brief review, we will survey the key elements of cryoEM-based hybrid modeling, providing an overview of available computational tools and strategies as well as several recent applications.
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Affiliation(s)
- C Keith Cassidy
- Department of Physics, Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Benjamin A Himes
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Zaida Luthey-Schulten
- Department of Chemistry, Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Peijun Zhang
- Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK; Electron Bio-Imaging Centre, Diamond Light Sources, Harwell Science and Innovation Campus, Didcot OX11 0DE, UK.
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13
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Tools for the cryo-EM gold rush: going from the cryo-EM map to the atomistic model. Biosci Rep 2017; 37:BSR20170072. [PMID: 28963369 PMCID: PMC5715128 DOI: 10.1042/bsr20170072] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2017] [Revised: 09/26/2017] [Accepted: 09/27/2017] [Indexed: 12/16/2022] Open
Abstract
As cryo-electron microscopy (cryo-EM) enters mainstream structural biology, the demand for fitting methods is high. Here, we review existing flexible fitting methods for cryo-EM. We discuss their importance, potential concerns and assessment strategies. We aim to give readers concrete descriptions of cryo-EM flexible fitting methods with corresponding examples.
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14
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Dou H, Burrows DW, Baker ML, Ju T. Flexible Fitting of Atomic Models into Cryo-EM Density Maps Guided by Helix Correspondences. Biophys J 2017. [PMID: 28636906 DOI: 10.1016/j.bpj.2017.04.054] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Although electron cryo-microscopy (cryo-EM) has recently achieved resolutions of better than 3 Å, at which point molecular modeling can be done directly from the density map, analysis and annotation of a cryo-EM density map still primarily rely on fitting atomic or homology models to the density map. In this article, we present, to our knowledge, a new method for flexible fitting of known or modeled protein structures into cryo-EM density maps. Unlike existing methods that are guided by local density gradients, our method is guided by correspondences between the α-helices in the density map and model, and does not require an initial rigid-body fitting step. Compared with current methods on both simulated and experimental density maps, our method not only achieves greater accuracy for proteins with large deformations but also runs as fast or faster than many of the other flexible fitting routines.
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Affiliation(s)
- Hang Dou
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri.
| | - Derek W Burrows
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri
| | - Matthew L Baker
- Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas
| | - Tao Ju
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri
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15
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Structural insights into the functional cycle of the ATPase module of the 26S proteasome. Proc Natl Acad Sci U S A 2017; 114:1305-1310. [PMID: 28115689 DOI: 10.1073/pnas.1621129114] [Citation(s) in RCA: 112] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
In eukaryotic cells, the ubiquitin-proteasome system (UPS) is responsible for the regulated degradation of intracellular proteins. The 26S holocomplex comprises the core particle (CP), where proteolysis takes place, and one or two regulatory particles (RPs). The base of the RP is formed by a heterohexameric AAA+ ATPase module, which unfolds and translocates substrates into the CP. Applying single-particle cryo-electron microscopy (cryo-EM) and image classification to samples in the presence of different nucleotides and nucleotide analogs, we were able to observe four distinct conformational states (s1 to s4). The resolution of the four conformers allowed for the construction of atomic models of the AAA+ ATPase module as it progresses through the functional cycle. In a hitherto unobserved state (s4), the gate controlling access to the CP is open. The structures described in this study allow us to put forward a model for the 26S functional cycle driven by ATP hydrolysis.
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16
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A central cavity within the holo-translocon suggests a mechanism for membrane protein insertion. Sci Rep 2016; 6:38399. [PMID: 27924919 PMCID: PMC5141469 DOI: 10.1038/srep38399] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2016] [Accepted: 11/08/2016] [Indexed: 12/21/2022] Open
Abstract
The conserved SecYEG protein-conducting channel and the accessory proteins SecDF-YajC and YidC constitute the bacterial holo-translocon (HTL), capable of protein-secretion and membrane-protein insertion. By employing an integrative approach combining small-angle neutron scattering (SANS), low-resolution electron microscopy and biophysical analyses we determined the arrangement of the proteins and lipids within the super-complex. The results guided the placement of X-ray structures of individual HTL components and allowed the proposal of a model of the functional translocon. Their arrangement around a central lipid-containing pool conveys an unexpected, but compelling mechanism for membrane-protein insertion. The periplasmic domains of YidC and SecD are poised at the protein-channel exit-site of SecY, presumably to aid the emergence of translocating polypeptides. The SecY lateral gate for membrane-insertion is adjacent to the membrane 'insertase' YidC. Absolute-scale SANS employing a novel contrast-match-point analysis revealed a dynamic complex adopting open and compact configurations around an adaptable central lipid-filled chamber, wherein polytopic membrane-proteins could fold, sheltered from aggregation and proteolysis.
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17
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Hanif M, Hafeez A, Suleman Y, Mustafa Rafique M, Butt AR, Iqbal SM. An accelerated framework for the classification of biological targets from solid-state micropore data. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2016; 134:53-67. [PMID: 27480732 DOI: 10.1016/j.cmpb.2016.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2015] [Revised: 05/05/2016] [Accepted: 06/13/2016] [Indexed: 06/06/2023]
Abstract
Micro- and nanoscale systems have provided means to detect biological targets, such as DNA, proteins, and human cells, at ultrahigh sensitivity. However, these devices suffer from noise in the raw data, which continues to be significant as newer and devices that are more sensitive produce an increasing amount of data that needs to be analyzed. An important dimension that is often discounted in these systems is the ability to quickly process the measured data for an instant feedback. Realizing and developing algorithms for the accurate detection and classification of biological targets in realtime is vital. Toward this end, we describe a supervised machine-learning approach that records single cell events (pulses), computes useful pulse features, and classifies the future patterns into their respective types, such as cancerous/non-cancerous cells based on the training data. The approach detects cells with an accuracy of 70% from the raw data followed by an accurate classification when larger training sets are employed. The parallel implementation of the algorithm on graphics processing unit (GPU) demonstrates a speedup of three to four folds as compared to a serial implementation on an Intel Core i7 processor. This incredibly efficient GPU system is an effort to streamline the analysis of pulse data in an academic setting. This paper presents for the first time ever, a non-commercial technique using a GPU system for realtime analysis, paired with biological cluster targeting analysis.
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Affiliation(s)
- Madiha Hanif
- Nano-Bio Lab, University of Texas at Arlington, Arlington, TX 76019; Department of Bioengineering, University of Texas at Arlington, Arlington, TX 76019; Nanotechnology Research Center, University of Texas at Arlington, Arlington, TX 76019
| | - Abdul Hafeez
- Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24060
| | - Yusuf Suleman
- Nano-Bio Lab, University of Texas at Arlington, Arlington, TX 76019; Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019
| | | | - Ali R Butt
- Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24060
| | - Samir M Iqbal
- Nano-Bio Lab, University of Texas at Arlington, Arlington, TX 76019; Department of Bioengineering, University of Texas at Arlington, Arlington, TX 76019; Nanotechnology Research Center, University of Texas at Arlington, Arlington, TX 76019; Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX 76019; Department of Urology, University of Texas Southwestern Medical Center at Dallas, Dallas, TX 75390, USA.
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18
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Singharoy A, Teo I, McGreevy R, Stone JE, Zhao J, Schulten K. Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps. eLife 2016; 5. [PMID: 27383269 PMCID: PMC4990421 DOI: 10.7554/elife.16105] [Citation(s) in RCA: 108] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2016] [Accepted: 07/06/2016] [Indexed: 12/12/2022] Open
Abstract
Two structure determination methods, based on the molecular dynamics flexible fitting (MDFF) paradigm, are presented that resolve sub-5 Å cryo-electron microscopy (EM) maps with either single structures or ensembles of such structures. The methods, denoted cascade MDFF and resolution exchange MDFF, sequentially re-refine a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution. Application of sequential re-refinement enables MDFF to achieve a radius of convergence of ~25 Å demonstrated with the accurate modeling of β-galactosidase and TRPV1 proteins at 3.2 Å and 3.4 Å resolution, respectively. The MDFF refinements uniquely offer map-model validation and B-factor determination criteria based on the inherent dynamics of the macromolecules studied, captured by means of local root mean square fluctuations. The MDFF tools described are available to researchers through an easy-to-use and cost-effective cloud computing resource on Amazon Web Services. DOI:http://dx.doi.org/10.7554/eLife.16105.001 To understand the roles that proteins and other large molecules play inside cells, it is important to determine their structures. One of the techniques that researchers can use to do this is called cryo-electron microscopy (cryo-EM), which rapidly freezes molecules to fix them in position before imaging them in fine detail. The cryo-EM images are like maps that show the approximate position of atoms. These images must then be processed in order to build a three-dimensional model of the protein that shows how its atoms are arranged relative to each other. One computational approach called Molecular Dynamics Flexible Fitting (MDFF) works by flexibly fitting possible atomic structures into cryo-EM maps. Although this approach works well with relatively undetailed (or ‘low resolution’) cryo-EM images, it struggles to handle the high-resolution cryo-EM maps now being generated. Singharoy, Teo, McGreevy et al. have now developed two MDFF methods – called cascade MDFF and resolution exchange MDFF – that help to resolve atomic models of biological molecules from cryo-EM images. Each method can refine poorly guessed models into ones that are consistent with the high-resolution experimental images. The refinement is achieved by interpreting a range of images that starts with a ‘fuzzy’ image. The contrast of the image is then progressively improved until an image is produced that has a resolution that is good enough to almost distinguish individual atoms. The method works because each cryo-EM image shows not just one, but a collection of atomic structures that the molecule can take on, with the fuzzier parts of the image representing the more flexible parts of the molecule. By taking into account this flexibility, the large-scale features of the protein structure can be determined first from the fuzzier images, and increasing the contrast of the images allows smaller-scale refinements to be made to the structure. The MDFF tools have been designed to be easy to use and are available to researchers at low cost through cloud computing platforms. They can now be used to unravel the structure of many different proteins and protein complexes including those involved in photosynthesis, respiration and protein synthesis. DOI:http://dx.doi.org/10.7554/eLife.16105.002
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Affiliation(s)
- Abhishek Singharoy
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Ivan Teo
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States.,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Ryan McGreevy
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States
| | - John E Stone
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States
| | - Jianhua Zhao
- Department of Biochemistry and Biophysics, University of California San Francisco School of Medicine, San Francisco, United States
| | - Klaus Schulten
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States.,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, United States
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19
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Stone JE, Sener M, Vandivort KL, Barragan A, Singharoy A, Teo I, Ribeiro JV, Isralewitz B, Liu B, Goh BC, Phillips JC, MacGregor-Chatwin C, Johnson MP, Kourkoutis LF, Hunter CN, Schulten K. Atomic Detail Visualization of Photosynthetic Membranes with GPU-Accelerated Ray Tracing. PARALLEL COMPUTING 2016; 55:17-27. [PMID: 27274603 PMCID: PMC4890717 DOI: 10.1016/j.parco.2015.10.015] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
The cellular process responsible for providing energy for most life on Earth, namely photosynthetic light-harvesting, requires the cooperation of hundreds of proteins across an organelle, involving length and time scales spanning several orders of magnitude over quantum and classical regimes. Simulation and visualization of this fundamental energy conversion process pose many unique methodological and computational challenges. We present, in two accompanying movies, light-harvesting in the photosynthetic apparatus found in purple bacteria, the so-called chromatophore. The movies are the culmination of three decades of modeling efforts, featuring the collaboration of theoretical, experimental, and computational scientists. We describe the techniques that were used to build, simulate, analyze, and visualize the structures shown in the movies, and we highlight cases where scientific needs spurred the development of new parallel algorithms that efficiently harness GPU accelerators and petascale computers.
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Affiliation(s)
- John E Stone
- Beckman Institute, University of Illinois at Urbana-Champaign, 405 N. Mathews Ave, Urbana, IL 61801, USA
| | - Melih Sener
- Beckman Institute, University of Illinois at Urbana-Champaign, 405 N. Mathews Ave, Urbana, IL 61801, USA
| | - Kirby L Vandivort
- Beckman Institute, University of Illinois at Urbana-Champaign, 405 N. Mathews Ave, Urbana, IL 61801, USA
| | - Angela Barragan
- Beckman Institute, University of Illinois at Urbana-Champaign, 405 N. Mathews Ave, Urbana, IL 61801, USA
| | - Abhishek Singharoy
- Beckman Institute, University of Illinois at Urbana-Champaign, 405 N. Mathews Ave, Urbana, IL 61801, USA
| | - Ivan Teo
- Department of Physics, University of Illinois at Urbana-Champaign, 1110 W Green St, Urbana, IL 61801, USA
| | - João V Ribeiro
- Beckman Institute, University of Illinois at Urbana-Champaign, 405 N. Mathews Ave, Urbana, IL 61801, USA
| | - Barry Isralewitz
- Beckman Institute, University of Illinois at Urbana-Champaign, 405 N. Mathews Ave, Urbana, IL 61801, USA
| | - Bo Liu
- Beckman Institute, University of Illinois at Urbana-Champaign, 405 N. Mathews Ave, Urbana, IL 61801, USA
| | - Boon Chong Goh
- Beckman Institute, University of Illinois at Urbana-Champaign, 405 N. Mathews Ave, Urbana, IL 61801, USA; Department of Physics, University of Illinois at Urbana-Champaign, 1110 W Green St, Urbana, IL 61801, USA
| | - James C Phillips
- Beckman Institute, University of Illinois at Urbana-Champaign, 405 N. Mathews Ave, Urbana, IL 61801, USA
| | - Craig MacGregor-Chatwin
- Department of Molecular Biology and Biotechnology, University of Sheffield, Western Bank, Sheffield, South Yorkshire S10 2TN, UK
| | - Matthew P Johnson
- Department of Molecular Biology and Biotechnology, University of Sheffield, Western Bank, Sheffield, South Yorkshire S10 2TN, UK
| | - Lena F Kourkoutis
- School of Applied and Engineering Physics, Cornell University, 271 Clark Hall, Ithaca, New York 14853, USA; Kavli Institute at Cornell for Nanoscale Sciences, 420 Physical Sciences Building, Ithaca, New York 14853, USA
| | - C Neil Hunter
- Department of Molecular Biology and Biotechnology, University of Sheffield, Western Bank, Sheffield, South Yorkshire S10 2TN, UK
| | - Klaus Schulten
- Beckman Institute, University of Illinois at Urbana-Champaign, 405 N. Mathews Ave, Urbana, IL 61801, USA; Department of Physics, University of Illinois at Urbana-Champaign, 1110 W Green St, Urbana, IL 61801, USA
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20
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Abstract
Protein degradation in eukaryotic cells is performed by the Ubiquitin-Proteasome System (UPS). The 26S proteasome holocomplex consists of a core particle (CP) that proteolytically degrades polyubiquitylated proteins, and a regulatory particle (RP) containing the AAA-ATPase module. This module controls access to the proteolytic chamber inside the CP and is surrounded by non-ATPase subunits (Rpns) that recognize substrates and deubiquitylate them before unfolding and degradation. The architecture of the 26S holocomplex is highly conserved between yeast and humans. The structure of the human 26S holocomplex described here reveals previously unidentified features of the AAA-ATPase heterohexamer. One subunit, Rpt6, has ADP bound, whereas the other five have ATP in their binding pockets. Rpt6 is structurally distinct from the other five Rpt subunits, most notably in its pore loop region. For Rpns, the map reveals two main, previously undetected, features: the C terminus of Rpn3 protrudes into the mouth of the ATPase ring; and Rpn1 and Rpn2, the largest proteasome subunits, are linked by an extended connection. The structural features of the 26S proteasome observed in this study are likely to be important for coordinating the proteasomal subunits during substrate processing.
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21
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Early Experiences Porting the NAMD and VMD Molecular Simulation and Analysis Software to GPU-Accelerated OpenPOWER Platforms. HIGH PERFORMANCE COMPUTING : 31ST INTERNATIONAL CONFERENCE, ISC HIGH PERFORMANCE 2016, FRANKFURT, GERMANY, JUNE 19-23, 2016, PROCEEDINGS. ISC HIGH PERFORMANCE (CONFERENCE) (31ST : 2016 : FRANKFURT, GERMANY) 2016; 9945:188-206. [PMID: 29202130 DOI: 10.1007/978-3-319-46079-6_14] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
All-atom molecular dynamics simulations of biomolecules provide a powerful tool for exploring the structure and dynamics of large protein complexes within realistic cellular environments. Unfortunately, such simulations are extremely demanding in terms of their computational requirements, and they present many challenges in terms of preparation, simulation methodology, and analysis and visualization of results. We describe our early experiences porting the popular molecular dynamics simulation program NAMD and the simulation preparation, analysis, and visualization tool VMD to GPU-accelerated OpenPOWER hardware platforms. We report our experiences with compiler-provided autovectorization and compare with hand-coded vector intrinsics for the POWER8 CPU. We explore the performance benefits obtained from unique POWER8 architectural features such as 8-way SMT and its value for particular molecular modeling tasks. Finally, we evaluate the performance of several GPU-accelerated molecular modeling kernels and relate them to other hardware platforms.
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22
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QwikMD - Integrative Molecular Dynamics Toolkit for Novices and Experts. Sci Rep 2016; 6:26536. [PMID: 27216779 PMCID: PMC4877583 DOI: 10.1038/srep26536] [Citation(s) in RCA: 118] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2016] [Accepted: 05/03/2016] [Indexed: 12/22/2022] Open
Abstract
The proper functioning of biomolecules in living cells requires them to assume particular structures and to undergo conformational changes. Both biomolecular structure and motion can be studied using a wide variety of techniques, but none offers the level of detail as do molecular dynamics (MD) simulations. Integrating two widely used modeling programs, namely NAMD and VMD, we have created a robust, user-friendly software, QwikMD, which enables novices and experts alike to address biomedically relevant questions, where often only molecular dynamics simulations can provide answers. Performing both simple and advanced MD simulations interactively, QwikMD automates as many steps as necessary for preparing, carrying out, and analyzing simulations while checking for common errors and enabling reproducibility. QwikMD meets also the needs of experts in the field, increasing the efficiency and quality of their work by carrying out tedious or repetitive tasks while enabling easy control of every step. Whether carrying out simulations within the live view mode on a small laptop or performing complex and large simulations on supercomputers or Cloud computers, QwikMD uses the same steps and user interface. QwikMD is freely available by download on group and personal computers. It is also available on the cloud at Amazon Web Services.
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23
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Goh BC, Hadden JA, Bernardi RC, Singharoy A, McGreevy R, Rudack T, Cassidy CK, Schulten K. Computational Methodologies for Real-Space Structural Refinement of Large Macromolecular Complexes. Annu Rev Biophys 2016; 45:253-78. [PMID: 27145875 DOI: 10.1146/annurev-biophys-062215-011113] [Citation(s) in RCA: 53] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The rise of the computer as a powerful tool for model building and refinement has revolutionized the field of structure determination for large biomolecular systems. Despite the wide availability of robust experimental methods capable of resolving structural details across a range of spatiotemporal resolutions, computational hybrid methods have the unique ability to integrate the diverse data from multimodal techniques such as X-ray crystallography and electron microscopy into consistent, fully atomistic structures. Here, commonly employed strategies for computational real-space structural refinement are reviewed, and their specific applications are illustrated for several large macromolecular complexes: ribosome, virus capsids, chemosensory array, and photosynthetic chromatophore. The increasingly important role of computational methods in large-scale structural refinement, along with current and future challenges, is discussed.
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Affiliation(s)
- Boon Chong Goh
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Jodi A Hadden
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Energy Biosciences Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Rafael C Bernardi
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Energy Biosciences Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Abhishek Singharoy
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Ryan McGreevy
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Till Rudack
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - C Keith Cassidy
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
| | - Klaus Schulten
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Energy Biosciences Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801.,Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801;
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24
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Stone JE, Messmer P, Sisneros R, Schulten K. High Performance Molecular Visualization: In-Situ and Parallel Rendering with EGL. IEEE INTERNATIONAL SYMPOSIUM ON PARALLEL & DISTRIBUTED PROCESSING, WORKSHOPS AND PHD FORUM : [PROCEEDINGS]. IEEE INTERNATIONAL SYMPOSIUM ON PARALLEL & DISTRIBUTED PROCESSING, WORKSHOPS AND PHD FORUM 2016; 2016:1014-1023. [PMID: 27747137 PMCID: PMC5061511 DOI: 10.1109/ipdpsw.2016.127] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/20/2023]
Abstract
Large scale molecular dynamics simulations produce terabytes of data that is impractical to transfer to remote facilities. It is therefore necessary to perform visualization tasks in-situ as the data are generated, or by running interactive remote visualization sessions and batch analyses co-located with direct access to high performance storage systems. A significant challenge for deploying visualization software within clouds, clusters, and supercomputers involves the operating system software required to initialize and manage graphics acceleration hardware. Recently, it has become possible for applications to use the Embedded-system Graphics Library (EGL) to eliminate the requirement for windowing system software on compute nodes, thereby eliminating a significant obstacle to broader use of high performance visualization applications. We outline the potential benefits of this approach in the context of visualization applications used in the cloud, on commodity clusters, and supercomputers. We discuss the implementation of EGL support in VMD, a widely used molecular visualization application, and we outline benefits of the approach for molecular visualization tasks on petascale computers, clouds, and remote visualization servers. We then provide a brief evaluation of the use of EGL in VMD, with tests using developmental graphics drivers on conventional workstations and on Amazon EC2 G2 GPU-accelerated cloud instance types. We expect that the techniques described here will be of broad benefit to many other visualization applications.
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Affiliation(s)
- John E Stone
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL;
| | - Peter Messmer
- NVIDIA, Developer Technology Group, Zurich, Switzerland;
| | - Robert Sisneros
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL;
| | - Klaus Schulten
- Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL;
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25
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Stone JE, Hallock MJ, Phillips JC, Peterson JR, Luthey-Schulten Z, Schulten K. Evaluation of Emerging Energy-Efficient Heterogeneous Computing Platforms for Biomolecular and Cellular Simulation Workloads. IEEE INTERNATIONAL SYMPOSIUM ON PARALLEL & DISTRIBUTED PROCESSING, WORKSHOPS AND PHD FORUM : [PROCEEDINGS]. IEEE INTERNATIONAL SYMPOSIUM ON PARALLEL & DISTRIBUTED PROCESSING, WORKSHOPS AND PHD FORUM 2016; 2016:89-100. [PMID: 27516922 DOI: 10.1109/ipdpsw.2016.130] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Many of the continuing scientific advances achieved through computational biology are predicated on the availability of ongoing increases in computational power required for detailed simulation and analysis of cellular processes on biologically-relevant timescales. A critical challenge facing the development of future exascale supercomputer systems is the development of new computing hardware and associated scientific applications that dramatically improve upon the energy efficiency of existing solutions, while providing increased simulation, analysis, and visualization performance. Mobile computing platforms have recently become powerful enough to support interactive molecular visualization tasks that were previously only possible on laptops and workstations, creating future opportunities for their convenient use for meetings, remote collaboration, and as head mounted displays for immersive stereoscopic viewing. We describe early experiences adapting several biomolecular simulation and analysis applications for emerging heterogeneous computing platforms that combine power-efficient system-on-chip multi-core CPUs with high-performance massively parallel GPUs. We present low-cost power monitoring instrumentation that provides sufficient temporal resolution to evaluate the power consumption of individual CPU algorithms and GPU kernels. We compare the performance and energy efficiency of scientific applications running on emerging platforms with results obtained on traditional platforms, identify hardware and algorithmic performance bottlenecks that affect the usability of these platforms, and describe avenues for improving both the hardware and applications in pursuit of the needs of molecular modeling tasks on mobile devices and future exascale computers.
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Affiliation(s)
- John E Stone
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Michael J Hallock
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - James C Phillips
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Joseph R Peterson
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Zaida Luthey-Schulten
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Klaus Schulten
- Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
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McGreevy R, Teo I, Singharoy A, Schulten K. Advances in the molecular dynamics flexible fitting method for cryo-EM modeling. Methods 2016; 100:50-60. [PMID: 26804562 PMCID: PMC4848153 DOI: 10.1016/j.ymeth.2016.01.009] [Citation(s) in RCA: 65] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2015] [Revised: 01/16/2016] [Accepted: 01/20/2016] [Indexed: 02/02/2023] Open
Abstract
Molecular Dynamics Flexible Fitting (MDFF) is an established technique for fitting all-atom structures of molecules into corresponding cryo-electron microscopy (cryo-EM) densities. The practical application of MDFF is simple but requires a user to be aware of and take measures against a variety of possible challenges presented by each individual case. Some of these challenges arise from the complexity of a molecular structure or the limited quality of available structural models and densities to be interpreted, while others stem from the intricacies of MDFF itself. The current article serves as an overview of the strategies that have been developed since MDFF's inception to overcome common challenges and successfully perform MDFF simulations.
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Affiliation(s)
- Ryan McGreevy
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, USA
| | - Ivan Teo
- Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Abhishek Singharoy
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, USA
| | - Klaus Schulten
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, USA; Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
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27
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Cyclophilin A stabilizes the HIV-1 capsid through a novel non-canonical binding site. Nat Commun 2016; 7:10714. [PMID: 26940118 PMCID: PMC4785225 DOI: 10.1038/ncomms10714] [Citation(s) in RCA: 107] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2015] [Accepted: 01/12/2016] [Indexed: 02/07/2023] Open
Abstract
The host cell factor cyclophilin A (CypA) interacts directly with the HIV-1 capsid and regulates viral infectivity. Although the crystal structure of CypA in complex with the N-terminal domain of the HIV-1 capsid protein (CA) has been known for nearly two decades, how CypA interacts with the viral capsid and modulates HIV-1 infectivity remains unclear. We determined the cryoEM structure of CypA in complex with the assembled HIV-1 capsid at 8-Å resolution. The structure exhibits a distinct CypA-binding pattern in which CypA selectively bridges the two CA hexamers along the direction of highest curvature. EM-guided all-atom molecular dynamics simulations and solid-state NMR further reveal that the CypA-binding pattern is achieved by single-CypA molecules simultaneously interacting with two CA subunits, in different hexamers, through a previously uncharacterized non-canonical interface. These results provide new insights into how CypA stabilizes the HIV-1 capsid and is recruited to facilitate HIV-1 infection. The host cell factor cyclophilin A (CypA) interacts with the HIV-1 capsid and regulates infectivity. Here the authors combine cryo-EM, solid-state NMR and all-atom MD simulations, identifying an interaction interface between CypA and the HIV capsid that stabilizes the viral capsid and regulates infectivity.
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Cortes-Ciriano I, Bouvier G, Nilges M, Maragliano L, Malliavin TE. Temperature Accelerated Molecular Dynamics with Soft-Ratcheting Criterion Orients Enhanced Sampling by Low-Resolution Information. J Chem Theory Comput 2015; 11:3446-54. [PMID: 26575778 DOI: 10.1021/acs.jctc.5b00153] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Many proteins exhibit an equilibrium between multiple conformations, some of them being characterized only by low-resolution information. Visiting all conformations is a demanding task for computational techniques performing enhanced but unfocused exploration of collective variable (CV) space. Otherwise, pulling a structure toward a target condition biases the exploration in a way difficult to assess. To address this problem, we introduce here the soft-ratcheting temperature-accelerated molecular dynamics (sr-TAMD), where the exploration of CV space by TAMD is coupled to a soft-ratcheting algorithm that filters the evolving CV values according to a predefined criterion. Any low resolution or even qualitative information can be used to orient the exploration. We validate this technique by exploring the conformational space of the inactive state of the catalytic domain of the adenyl cyclase AC from Bordetella pertussis. The domain AC gets activated by association with calmodulin (CaM), and the available crystal structure shows that in the complex the protein has an elongated shape. High-resolution data are not available for the inactive, CaM-free protein state, but hydrodynamic measurements have shown that the inactive AC displays a more globular conformation. Here, using as CVs several geometric centers, we use sr-TAMD to enhance CV space sampling while filtering for CV values that correspond to centers moving close to each other, and we thus rapidly visit regions of conformational space that correspond to globular structures. The set of conformations sampled using sr-TAMD provides the most extensive description of the inactive state of AC up to now, consistent with available experimental information.
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Affiliation(s)
- Isidro Cortes-Ciriano
- Unité de Bioinformatique Structurale, CNRS UMR 3528, Structural Biology and Chemistry Department, Institut Pasteur , 25-28, rue Dr. Roux, 75 724 Paris, France
| | - Guillaume Bouvier
- Unité de Bioinformatique Structurale, CNRS UMR 3528, Structural Biology and Chemistry Department, Institut Pasteur , 25-28, rue Dr. Roux, 75 724 Paris, France
| | - Michael Nilges
- Unité de Bioinformatique Structurale, CNRS UMR 3528, Structural Biology and Chemistry Department, Institut Pasteur , 25-28, rue Dr. Roux, 75 724 Paris, France
| | - Luca Maragliano
- Department of Neuroscience and Brain Technologies, Istituto Italiano di Tecnologia , Genoa, Italy
| | - Thérèse E Malliavin
- Unité de Bioinformatique Structurale, CNRS UMR 3528, Structural Biology and Chemistry Department, Institut Pasteur , 25-28, rue Dr. Roux, 75 724 Paris, France
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Mortier J, Rakers C, Bermudez M, Murgueitio MS, Riniker S, Wolber G. The impact of molecular dynamics on drug design: applications for the characterization of ligand-macromolecule complexes. Drug Discov Today 2015; 20:686-702. [PMID: 25615716 DOI: 10.1016/j.drudis.2015.01.003] [Citation(s) in RCA: 106] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2014] [Revised: 12/08/2014] [Accepted: 01/08/2015] [Indexed: 10/24/2022]
Abstract
Among all tools available to design new drugs, molecular dynamics (MD) simulations have become an essential technique. Initially developed to investigate molecular models with a limited number of atoms, computers now enable investigations of large macromolecular systems with a simulation time reaching the microsecond range. The reviewed articles cover four years of research to give an overview on the actual impact of MD on the current medicinal chemistry landscape with a particular emphasis on studies of ligand-protein interactions. With a special focus on studies combining computational approaches with data gained from other techniques, this review shows how deeply embedded MD simulations are in drug design strategies and articulates what the future of this technique could be.
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Affiliation(s)
- Jérémie Mortier
- Institute of Pharmacy, Freie Universität Berlin, Königin-Luise-Strasse 2+4, 14195 Berlin, Germany.
| | - Christin Rakers
- Institute of Pharmacy, Freie Universität Berlin, Königin-Luise-Strasse 2+4, 14195 Berlin, Germany
| | - Marcel Bermudez
- Institute of Pharmacy, Freie Universität Berlin, Königin-Luise-Strasse 2+4, 14195 Berlin, Germany
| | - Manuela S Murgueitio
- Institute of Pharmacy, Freie Universität Berlin, Königin-Luise-Strasse 2+4, 14195 Berlin, Germany
| | - Sereina Riniker
- Laboratory of Physical Chemistry, ETH Zürich, Vladimir-Prelog-Weg 2, CH-8093 Zurich, Switzerland
| | - Gerhard Wolber
- Institute of Pharmacy, Freie Universität Berlin, Königin-Luise-Strasse 2+4, 14195 Berlin, Germany.
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Zhang L, Lua LHL, Middelberg APJ, Sun Y, Connors NK. Biomolecular engineering of virus-like particles aided by computational chemistry methods. Chem Soc Rev 2015; 44:8608-18. [DOI: 10.1039/c5cs00526d] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Multi-scale investigation of VLP self-assembly aided by computational methods is facilitating the design, redesign, and modification of functionalized VLPs.
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Affiliation(s)
- Lin Zhang
- Department of Biochemical Engineering and Key Laboratory of Systems Bioengineering of the Ministry of Education
- School of Chemical Engineering and Technology
- Tianjin University
- Tianjin 300072, People's Republic of China
| | - Linda H. L. Lua
- Protein Expression Facility
- The University of Queensland
- Brisbane, Australia
| | - Anton P. J. Middelberg
- Australian Institute for Bioengineering and Nanotechnology
- The University of Queensland
- Brisbane, Australia
| | - Yan Sun
- Department of Biochemical Engineering and Key Laboratory of Systems Bioengineering of the Ministry of Education
- School of Chemical Engineering and Technology
- Tianjin University
- Tianjin 300072, People's Republic of China
| | - Natalie K. Connors
- Australian Institute for Bioengineering and Nanotechnology
- The University of Queensland
- Brisbane, Australia
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