1
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Domanska M, Setny P. Exploring the Properties of Curved Lipid Membranes: Comparative Analysis of Atomistic and Coarse-Grained Force Fields. J Phys Chem B 2024; 128:7160-7171. [PMID: 38990314 DOI: 10.1021/acs.jpcb.4c02310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/12/2024]
Abstract
Curvature emerges as a fundamental membrane characteristic crucial for diverse biological processes, including vesicle formation, cell signaling, and membrane trafficking. Increasingly valuable insights into atomistic details governing curvature-dependent membrane properties are provided by computer simulations. Nevertheless, the underlying force field models are conventionally calibrated and tested in relation to experimentally derived parameters of planar bilayers, thereby leaving uncertainties concerning their consistency in reproducing curved lipid systems. In this study we compare the depiction of buckled phosphatidylcholine (POPC) and POPC-cholesterol membranes by four popular force field models. Aside from agreement with respect to general trends in curvature dependence of a number of parameters, we observe a few qualitative differences. Among the most prominent ones is the difference between atomistic and coarse grained force fields in their representation of relative compressibility of the polar headgroup region and hydrophobic lipid core. Through a number of downstream effects, this discrepancy can influence the way in which curvature modulates the behavior of membrane bound proteins depending on the adopted simulation model.
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Affiliation(s)
- Maria Domanska
- Centre of New Technologies, University of Warsaw, Banacha 2c, 02-097 Warsaw, Poland
| | - Piotr Setny
- Centre of New Technologies, University of Warsaw, Banacha 2c, 02-097 Warsaw, Poland
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2
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Kern NR, Lee J, Choi YK, Im W. CHARMM-GUI Multicomponent Assembler for modeling and simulation of complex multicomponent systems. Nat Commun 2024; 15:5459. [PMID: 38937468 PMCID: PMC11211406 DOI: 10.1038/s41467-024-49700-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 06/17/2024] [Indexed: 06/29/2024] Open
Abstract
Atomic-scale molecular modeling and simulation are powerful tools for computational biology. However, constructing models with large, densely packed molecules, non-water solvents, or with combinations of multiple biomembranes, polymers, and nanomaterials remains challenging and requires significant time and expertise. Furthermore, existing tools do not support such assemblies under the periodic boundary conditions (PBC) necessary for molecular simulation. Here, we describe Multicomponent Assembler in CHARMM-GUI that automates complex molecular assembly and simulation input preparation under the PBC. In this work, we demonstrate its versatility by preparing 6 challenging systems with varying density of large components: (1) solvated proteins, (2) solvated proteins with a pre-equilibrated membrane, (3) solvated proteins with a sheet-like nanomaterial, (4) solvated proteins with a sheet-like polymer, (5) a mixed membrane-nanomaterial system, and (6) a sheet-like polymer with gaseous solvent. Multicomponent Assembler is expected to be a unique cyberinfrastructure to study complex interactions between small molecules, biomacromolecules, polymers, and nanomaterials.
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Affiliation(s)
- Nathan R Kern
- Department of Computer Science & Engineering, Lehigh University, Bethlehem, PA, USA
| | - Jumin Lee
- Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA
| | - Yeol Kyo Choi
- Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA
| | - Wonpil Im
- Department of Computer Science & Engineering, Lehigh University, Bethlehem, PA, USA.
- Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA.
- Department of Bioengineering, Lehigh University, Bethlehem, PA, USA.
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3
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Rao S, Skulsuppaisarn M, Strong LM, Ren X, Lazarou M, Hurley JH, Hummer G. Three-step docking by WIPI2, ATG16L1, and ATG3 delivers LC3 to the phagophore. SCIENCE ADVANCES 2024; 10:eadj8027. [PMID: 38324698 PMCID: PMC10851258 DOI: 10.1126/sciadv.adj8027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 01/05/2024] [Indexed: 02/09/2024]
Abstract
The covalent attachment of ubiquitin-like LC3 proteins (microtubule-associated proteins 1A/1B light chain 3) prepares the autophagic membrane for cargo recruitment. We resolve key steps in LC3 lipidation by combining molecular dynamics simulations and experiments in vitro and in cellulo. We show how the E3-like ligaseautophagy-related 12 (ATG12)-ATG5-ATG16L1 in complex with the E2-like conjugase ATG3 docks LC3 onto the membrane in three steps by (i) the phosphatidylinositol 3-phosphate effector protein WD repeat domain phosphoinositide-interacting protein 2 (WIPI2), (ii) helix α2 of ATG16L1, and (iii) a membrane-interacting surface of ATG3. Phosphatidylethanolamine (PE) lipids concentrate in a region around the thioester bond between ATG3 and LC3, highlighting residues with a possible role in the catalytic transfer of LC3 to PE, including two conserved histidines. In a near-complete pathway from the initial membrane recruitment to the LC3 lipidation reaction, the three-step targeting of the ATG12-ATG5-ATG16L1 machinery establishes a high level of regulatory control.
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Affiliation(s)
- Shanlin Rao
- Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Frankfurt am Main, Germany
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
| | - Marvin Skulsuppaisarn
- Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia
- Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Melbourne, Victoria, Australia
| | - Lisa M. Strong
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
- California Institute for Quantitative Biosciences, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Xuefeng Ren
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
- California Institute for Quantitative Biosciences, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Michael Lazarou
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia
- Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Melbourne, Victoria, Australia
- Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia
| | - James H. Hurley
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
- California Institute for Quantitative Biosciences, University of California, Berkeley, Berkeley, CA 94720, USA
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Gerhard Hummer
- Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Frankfurt am Main, Germany
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- Institute of Biophysics, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany
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4
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McCafferty CL, Klumpe S, Amaro RE, Kukulski W, Collinson L, Engel BD. Integrating cellular electron microscopy with multimodal data to explore biology across space and time. Cell 2024; 187:563-584. [PMID: 38306982 DOI: 10.1016/j.cell.2024.01.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 01/03/2024] [Accepted: 01/03/2024] [Indexed: 02/04/2024]
Abstract
Biology spans a continuum of length and time scales. Individual experimental methods only glimpse discrete pieces of this spectrum but can be combined to construct a more holistic view. In this Review, we detail the latest advancements in volume electron microscopy (vEM) and cryo-electron tomography (cryo-ET), which together can visualize biological complexity across scales from the organization of cells in large tissues to the molecular details inside native cellular environments. In addition, we discuss emerging methodologies for integrating three-dimensional electron microscopy (3DEM) imaging with multimodal data, including fluorescence microscopy, mass spectrometry, single-particle analysis, and AI-based structure prediction. This multifaceted approach fills gaps in the biological continuum, providing functional context, spatial organization, molecular identity, and native interactions. We conclude with a perspective on incorporating diverse data into computational simulations that further bridge and extend length scales while integrating the dimension of time.
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Affiliation(s)
| | - Sven Klumpe
- Research Group CryoEM Technology, Max-Planck-Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany.
| | - Rommie E Amaro
- Department of Molecular Biology, University of California, San Diego, La Jolla, CA 92093, USA.
| | - Wanda Kukulski
- Institute of Biochemistry and Molecular Medicine, University of Bern, Bühlstrasse 28, 3012 Bern, Switzerland.
| | - Lucy Collinson
- Electron Microscopy Science Technology Platform, Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK.
| | - Benjamin D Engel
- Biozentrum, University of Basel, Spitalstrasse 41, 4056 Basel, Switzerland.
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5
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Kern NR, Lee J, Choi YK, Im W. CHARMM-GUI Multicomponent Assembler for Modeling and Simulation of Complex Multicomponent Systems. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.30.555590. [PMID: 37693396 PMCID: PMC10491218 DOI: 10.1101/2023.08.30.555590] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Atomic-scale molecular modeling and simulation are powerful tools for computational biology. However, constructing models with large, densely packed molecules, non-water solvents, or with combinations of multiple biomembranes, polymers, and nanomaterials remains challenging and requires significant time and expertise. Furthermore, existing tools do not support such assemblies under the periodic boundary conditions (PBC) necessary for molecular simulation. Here, we describe Multicomponent Assembler in CHARMM-GUI that automates complex molecular assembly and simulation input preparation under the PBC. We demonstrate its versatility by preparing 6 challenging systems with varying density of large components: (1) solvated proteins, (2) solvated proteins with a pre-equilibrated membrane, (3) solvated proteins with a sheet-like nanomaterial, (4) solvated proteins with a sheet-like polymer, (5) a mixed membrane-nanomaterial system, and (6) a sheet-like polymer with gaseous solvent. Multicomponent Assembler is expected to be a unique cyberinfrastructure to facilitate innovative studies of complex interactions between small (organic and inorganic) molecules, biomacromolecules, polymers, and nanomaterials.
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Affiliation(s)
- Nathan R. Kern
- Department of Computer Science & Engineering, Lehigh University, Bethlehem, PA, USA
| | - Jumin Lee
- Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA
| | - Yeol Kyo Choi
- Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA
| | - Wonpil Im
- Departments of Biological Sciences, Chemistry, Bioengineering, and Computer Science & Engineering, Lehigh University, Bethlehem, PA, USA
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6
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González A, Covarrubias-Pinto A, Bhaskara RM, Glogger M, Kuncha SK, Xavier A, Seemann E, Misra M, Hoffmann ME, Bräuning B, Balakrishnan A, Qualmann B, Dötsch V, Schulman BA, Kessels MM, Hübner CA, Heilemann M, Hummer G, Dikić I. Ubiquitination regulates ER-phagy and remodelling of endoplasmic reticulum. Nature 2023:10.1038/s41586-023-06089-2. [PMID: 37225996 DOI: 10.1038/s41586-023-06089-2] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 04/14/2023] [Indexed: 05/26/2023]
Abstract
The endoplasmic reticulum (ER) undergoes continuous remodelling via a selective autophagy pathway, known as ER-phagy1. ER-phagy receptors have a central role in this process2, but the regulatory mechanism remains largely unknown. Here we report that ubiquitination of the ER-phagy receptor FAM134B within its reticulon homology domain (RHD) promotes receptor clustering and binding to lipidated LC3B, thereby stimulating ER-phagy. Molecular dynamics (MD) simulations showed how ubiquitination perturbs the RHD structure in model bilayers and enhances membrane curvature induction. Ubiquitin molecules on RHDs mediate interactions between neighbouring RHDs to form dense receptor clusters that facilitate the large-scale remodelling of lipid bilayers. Membrane remodelling was reconstituted in vitro with liposomes and ubiquitinated FAM134B. Using super-resolution microscopy, we discovered FAM134B nanoclusters and microclusters in cells. Quantitative image analysis revealed a ubiquitin-mediated increase in FAM134B oligomerization and cluster size. We found that the E3 ligase AMFR, within multimeric ER-phagy receptor clusters, catalyses FAM134B ubiquitination and regulates the dynamic flux of ER-phagy. Our results show that ubiquitination enhances RHD functions via receptor clustering, facilitates ER-phagy and controls ER remodelling in response to cellular demands.
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Affiliation(s)
- Alexis González
- Institute of Biochemistry II, Faculty of Medicine, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Adriana Covarrubias-Pinto
- Institute of Biochemistry II, Faculty of Medicine, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Ramachandra M Bhaskara
- Institute of Biochemistry II, Faculty of Medicine, Goethe University Frankfurt, Frankfurt am Main, Germany
- Buchmann Institute for Molecular Life Sciences, Goethe University Frankfurt, Frankfurt am Main, Germany
- Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Frankfurt am Main, Germany
| | - Marius Glogger
- Institute of Physical and Theoretical Chemistry, Goethe University Frankfurt, Frankfurt, Germany
| | - Santosh K Kuncha
- Institute of Biochemistry II, Faculty of Medicine, Goethe University Frankfurt, Frankfurt am Main, Germany
- Buchmann Institute for Molecular Life Sciences, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Audrey Xavier
- Institute of Biochemistry II, Faculty of Medicine, Goethe University Frankfurt, Frankfurt am Main, Germany
- Buchmann Institute for Molecular Life Sciences, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Eric Seemann
- Institute of Biochemistry I, Jena University Hospital, Friedrich Schiller University Jena, Jena, Germany
| | - Mohit Misra
- Institute of Biochemistry II, Faculty of Medicine, Goethe University Frankfurt, Frankfurt am Main, Germany
- Buchmann Institute for Molecular Life Sciences, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Marina E Hoffmann
- Institute of Biochemistry II, Faculty of Medicine, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Bastian Bräuning
- Department of Molecular Machines and Signaling, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Ashwin Balakrishnan
- Institute of Physical and Theoretical Chemistry, Goethe University Frankfurt, Frankfurt, Germany
| | - Britta Qualmann
- Institute of Biochemistry I, Jena University Hospital, Friedrich Schiller University Jena, Jena, Germany
| | - Volker Dötsch
- Institute of Biophysical Chemistry, Center for Biomolecular Magnetic Resonance, Goethe University Frankfurt, Frankfurt, Germany
| | - Brenda A Schulman
- Department of Molecular Machines and Signaling, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Michael M Kessels
- Institute of Biochemistry I, Jena University Hospital, Friedrich Schiller University Jena, Jena, Germany
| | - Christian A Hübner
- Institute of Human Genetics, University Hospital Jena, Friedrich Schiller University, Jena, Germany
| | - Mike Heilemann
- Institute of Physical and Theoretical Chemistry, Goethe University Frankfurt, Frankfurt, Germany
| | - Gerhard Hummer
- Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Frankfurt am Main, Germany
- Institute of Biophysics, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Ivan Dikić
- Institute of Biochemistry II, Faculty of Medicine, Goethe University Frankfurt, Frankfurt am Main, Germany.
- Buchmann Institute for Molecular Life Sciences, Goethe University Frankfurt, Frankfurt am Main, Germany.
- Fraunhofer Institute of Translational Medicine and Pharmacology, Frankfurt am Main, Germany.
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7
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Lynch DL, Pavlova A, Fan Z, Gumbart JC. Understanding Virus Structure and Dynamics through Molecular Simulations. J Chem Theory Comput 2023. [PMID: 37192279 DOI: 10.1021/acs.jctc.3c00116] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Viral outbreaks remain a serious threat to human and animal populations and motivate the continued development of antiviral drugs and vaccines, which in turn benefits from a detailed understanding of both viral structure and dynamics. While great strides have been made in characterizing these systems experimentally, molecular simulations have proven to be an essential, complementary approach. In this work, we review the contributions of molecular simulations to the understanding of viral structure, functional dynamics, and processes related to the viral life cycle. Approaches ranging from coarse-grained to all-atom representations are discussed, including current efforts at modeling complete viral systems. Overall, this review demonstrates that computational virology plays an essential role in understanding these systems.
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Affiliation(s)
- Diane L Lynch
- School of Physics, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Anna Pavlova
- School of Physics, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Zixing Fan
- Interdisciplinary Bioengineering Graduate Program, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - James C Gumbart
- School of Physics, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
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8
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Feng S, Park S, Choi YK, Im W. CHARMM-GUI Membrane Builder: Past, Current, and Future Developments and Applications. J Chem Theory Comput 2023; 19:2161-2185. [PMID: 37014931 PMCID: PMC10174225 DOI: 10.1021/acs.jctc.2c01246] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/06/2023]
Abstract
Molecular dynamics simulations of membranes and membrane proteins serve as computational microscopes, revealing coordinated events at the membrane interface. As G protein-coupled receptors, ion channels, transporters, and membrane-bound enzymes are important drug targets, understanding their drug binding and action mechanisms in a realistic membrane becomes critical. Advances in materials science and physical chemistry further demand an atomistic understanding of lipid domains and interactions between materials and membranes. Despite a wide range of membrane simulation studies, generating a complex membrane assembly remains challenging. Here, we review the capability of CHARMM-GUI Membrane Builder in the context of emerging research demands, as well as the application examples from the CHARMM-GUI user community, including membrane biophysics, membrane protein drug-binding and dynamics, protein-lipid interactions, and nano-bio interface. We also provide our perspective on future Membrane Builder development.
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Affiliation(s)
- Shasha Feng
- Departments of Biological Sciences and Chemistry, Lehigh University, Bethlehem, Pennsylvania 18015, United States
| | - Soohyung Park
- Departments of Biological Sciences and Chemistry, Lehigh University, Bethlehem, Pennsylvania 18015, United States
| | - Yeol Kyo Choi
- Departments of Biological Sciences and Chemistry, Lehigh University, Bethlehem, Pennsylvania 18015, United States
| | - Wonpil Im
- Departments of Biological Sciences and Chemistry, Lehigh University, Bethlehem, Pennsylvania 18015, United States
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9
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Rasouli A, Yu Q, Dehghani-Ghahnaviyeh S, Wen PC, Kowal J, Locher KP, Tajkhorshid E. Differential dynamics and direct interaction of bound ligands with lipids in multidrug transporter ABCG2. Proc Natl Acad Sci U S A 2023; 120:e2213437120. [PMID: 36580587 PMCID: PMC9910490 DOI: 10.1073/pnas.2213437120] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 10/20/2022] [Indexed: 12/31/2022] Open
Abstract
ABCG2 is an ATP-binding cassette (ABC) transporter that extrudes a wide range of xenobiotics and drugs from the cell and contributes to multidrug resistance in cancer cells. Following our recent structural characterization of topotecan-bound ABCG2, here, we present cryo-EM structures of ABCG2 under turnover conditions in complex with a special modulator and slow substrate, tariquidar, in nanodiscs. The structures reveal that similar to topotecan, tariquidar induces two distinct ABCG2 conformations under turnover conditions (turnover-1 and turnover-2). μs-scale molecular dynamics simulations of drug-bound and apo ABCG2 in native-like lipid bilayers, in both topotecan- and tariquidar-bound states, characterize the ligand size as a major determinant of its binding stability. The simulations highlight direct lipid-drug interactions for the smaller topotecan, which exhibits a highly dynamic binding mode. In contrast, the larger tariquidar occupies most of the available volume in the binding pocket, thus leaving little space for lipids to enter the cavity and interact with it. Similarly, when simulating ABCG2 in the apo inward-open state, we also observe spontaneous penetration of phospholipids into the binding cavity. The captured phospholipid diffusion pathway into ABCG2 offers a putative general path to recruit any hydrophobic/amphiphilic substrates directly from the membrane. Our simulations also reveal that ABCG2 rejects cholesterol as a substrate, which is omnipresent in plasma membranes that contain ABCG2. At the same time, cholesterol is found to prohibit the penetration of phospholipids into ABCG2. These molecular findings have direct functional ramifications on ABCG2's function as a transporter.
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Affiliation(s)
- Ali Rasouli
- Theoretical and Computational Biophysics Group, NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute for Advanced Science and Technology, Department of Biochemistry, University of Illinois, Urbana, IL61801
- Center for Biophysics and Quantitative Biology University of Illinois, Urbana, IL61801
| | - Qin Yu
- Institute of Molecular Biology and Biophysics, Department of Biology, ETH Zürich, 8093, Zürich, Switzerland
| | - Sepehr Dehghani-Ghahnaviyeh
- Theoretical and Computational Biophysics Group, NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute for Advanced Science and Technology, Department of Biochemistry, University of Illinois, Urbana, IL61801
- Center for Biophysics and Quantitative Biology University of Illinois, Urbana, IL61801
| | - Po-Chao Wen
- Theoretical and Computational Biophysics Group, NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute for Advanced Science and Technology, Department of Biochemistry, University of Illinois, Urbana, IL61801
- Center for Biophysics and Quantitative Biology University of Illinois, Urbana, IL61801
| | - Julia Kowal
- Institute of Molecular Biology and Biophysics, Department of Biology, ETH Zürich, 8093, Zürich, Switzerland
| | - Kaspar P. Locher
- Institute of Molecular Biology and Biophysics, Department of Biology, ETH Zürich, 8093, Zürich, Switzerland
| | - Emad Tajkhorshid
- Theoretical and Computational Biophysics Group, NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute for Advanced Science and Technology, Department of Biochemistry, University of Illinois, Urbana, IL61801
- Center for Biophysics and Quantitative Biology University of Illinois, Urbana, IL61801
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10
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Dommer A, Casalino L, Kearns F, Rosenfeld M, Wauer N, Ahn SH, Russo J, Oliveira S, Morris C, Bogetti A, Trifan A, Brace A, Sztain T, Clyde A, Ma H, Chennubhotla C, Lee H, Turilli M, Khalid S, Tamayo-Mendoza T, Welborn M, Christensen A, Smith DG, Qiao Z, Sirumalla SK, O'Connor M, Manby F, Anandkumar A, Hardy D, Phillips J, Stern A, Romero J, Clark D, Dorrell M, Maiden T, Huang L, McCalpin J, Woods C, Gray A, Williams M, Barker B, Rajapaksha H, Pitts R, Gibbs T, Stone J, Zuckerman DM, Mulholland AJ, Miller T, Jha S, Ramanathan A, Chong L, Amaro RE. #COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol. THE INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2023; 37:28-44. [PMID: 36647365 PMCID: PMC9527558 DOI: 10.1177/10943420221128233] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2023]
Abstract
We seek to completely revise current models of airborne transmission of respiratory viruses by providing never-before-seen atomic-level views of the SARS-CoV-2 virus within a respiratory aerosol. Our work dramatically extends the capabilities of multiscale computational microscopy to address the significant gaps that exist in current experimental methods, which are limited in their ability to interrogate aerosols at the atomic/molecular level and thus obscure our understanding of airborne transmission. We demonstrate how our integrated data-driven platform provides a new way of exploring the composition, structure, and dynamics of aerosols and aerosolized viruses, while driving simulation method development along several important axes. We present a series of initial scientific discoveries for the SARS-CoV-2 Delta variant, noting that the full scientific impact of this work has yet to be realized.
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Affiliation(s)
| | | | | | | | | | | | - John Russo
- Oregon Health & Science University, Portland, OR, USA
| | | | | | | | - Anda Trifan
- Argonne National Laboratory, Lemont, IL, USA
- University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Alexander Brace
- Argonne National Laboratory, Lemont, IL, USA
- University of Chicago, Chicago, IL, USA
| | - Terra Sztain
- UC San Diego, La Jolla, CA, USA
- Freie Universitat Berlin
| | - Austin Clyde
- Argonne National Laboratory, Lemont, IL, USA
- University of Chicago, Chicago, IL, USA
| | - Heng Ma
- Argonne National Laboratory, Lemont, IL, USA
| | | | - Hyungro Lee
- Brookhaven National Lab and Rutgers University
| | | | | | | | | | | | | | - Zhuoran Qiao
- California Institute of Technology, Pasadena, CA, USA
| | | | | | | | - Anima Anandkumar
- California Institute of Technology, Pasadena, CA, USA
- NVIDIA Corp, Santa Clara, CA, USA
| | - David Hardy
- University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - James Phillips
- University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | | | | | | | | | - Tom Maiden
- Pittsburgh Supercomputing Center, Pittsburgh, PA, USA
| | - Lei Huang
- Texas Advanced Computing Center, Austin, TX, USA
| | | | | | | | | | | | | | | | | | - John Stone
- University of Illinois at Urbana-Champaign, Urbana, IL, USA
- NVIDIA Corp, Santa Clara, CA, USA
| | | | | | - Thomas Miller
- Entos, Inc., San Diego, CA, USA
- California Institute of Technology, Pasadena, CA, USA
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11
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Casalino L, Seitz C, Lederhofer J, Tsybovsky Y, Wilson IA, Kanekiyo M, Amaro RE. Breathing and Tilting: Mesoscale Simulations Illuminate Influenza Glycoprotein Vulnerabilities. ACS CENTRAL SCIENCE 2022; 8:1646-1663. [PMID: 36589893 PMCID: PMC9801513 DOI: 10.1021/acscentsci.2c00981] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Indexed: 05/28/2023]
Abstract
Influenza virus has resurfaced recently from inactivity during the early stages of the COVID-19 pandemic, raising serious concerns about the nature and magnitude of future epidemics. The main antigenic targets of influenza virus are two surface glycoproteins, hemagglutinin (HA) and neuraminidase (NA). Whereas the structural and dynamical properties of both glycoproteins have been studied previously, the understanding of their plasticity in the whole-virion context is fragmented. Here, we investigate the dynamics of influenza glycoproteins in a crowded protein environment through mesoscale all-atom molecular dynamics simulations of two evolutionary-linked glycosylated influenza A whole-virion models. Our simulations reveal and kinetically characterize three main molecular motions of influenza glycoproteins: NA head tilting, HA ectodomain tilting, and HA head breathing. The flexibility of HA and NA highlights antigenically relevant conformational states, as well as facilitates the characterization of a novel monoclonal antibody, derived from convalescent human donor, that binds to the underside of the NA head. Our work provides previously unappreciated views on the dynamics of HA and NA, advancing the understanding of their interplay and suggesting possible strategies for the design of future vaccines and antivirals against influenza.
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Affiliation(s)
- Lorenzo Casalino
- Department
of Chemistry and Biochemistry, University
of California San Diego, La Jolla, California92093, United States
| | - Christian Seitz
- Department
of Chemistry and Biochemistry, University
of California San Diego, La Jolla, California92093, United States
| | - Julia Lederhofer
- Vaccine
Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland20892, United States
| | - Yaroslav Tsybovsky
- Electron
Microscopy Laboratory, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research
Sponsored by the National Cancer Institute, Frederick, Maryland21702, United States
| | - Ian A. Wilson
- Department
of Integrative Structural and Computational Biology and the Skaggs
Institute for Chemical Biology, The Scripps
Research Institute, La Jolla, California92037, United States
| | - Masaru Kanekiyo
- Vaccine
Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland20892, United States
| | - Rommie E. Amaro
- Department
of Chemistry and Biochemistry, University
of California San Diego, La Jolla, California92093, United States
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12
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Jensen LE, Rao S, Schuschnig M, Cada AK, Martens S, Hummer G, Hurley JH. Membrane curvature sensing and stabilization by the autophagic LC3 lipidation machinery. SCIENCE ADVANCES 2022; 8:eadd1436. [PMID: 36516251 PMCID: PMC9750143 DOI: 10.1126/sciadv.add1436] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 11/10/2022] [Indexed: 05/28/2023]
Abstract
How the highly curved phagophore membrane is stabilized during autophagy initiation is a major open question in autophagosome biogenesis. Here, we use in vitro reconstitution on membrane nanotubes and molecular dynamics simulations to investigate how core autophagy proteins in the LC3 (Microtubule-associated proteins 1A/1B light chain 3) lipidation cascade interact with curved membranes, providing insight into their possible roles in regulating membrane shape during autophagosome biogenesis. ATG12(Autophagy-related 12)-ATG5-ATG16L1 was up to 100-fold enriched on highly curved nanotubes relative to flat membranes. At high surface density, ATG12-ATG5-ATG16L1 binding increased the curvature of the nanotubes. While WIPI2 (WD repeat domain phosphoinositide-interacting protein 2) binding directs membrane recruitment, the amphipathic helix α2 of ATG16L1 is responsible for curvature sensitivity. Molecular dynamics simulations revealed that helix α2 of ATG16L1 inserts shallowly into the membrane, explaining its curvature-sensitive binding to the membrane. These observations show how the binding of the ATG12-ATG5-ATG16L1 complex to the early phagophore rim could stabilize membrane curvature and facilitate autophagosome growth.
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Affiliation(s)
- Liv E. Jensen
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, CA 94720, USA
- California Institute for Quantitative Biosciences, University of California, Berkeley, CA 94720, USA
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
| | - Shanlin Rao
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Frankfurt am Main, Germany
| | - Martina Schuschnig
- Department of Biochemistry and Cell Biology, Max Perutz Labs, University of Vienna, Vienna BioCenter, Vienna, Austria
| | - A. King Cada
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, CA 94720, USA
- California Institute for Quantitative Biosciences, University of California, Berkeley, CA 94720, USA
| | - Sascha Martens
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- Department of Biochemistry and Cell Biology, Max Perutz Labs, University of Vienna, Vienna BioCenter, Vienna, Austria
| | - Gerhard Hummer
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Frankfurt am Main, Germany
- Institute of Biophysics, Goethe University Frankfurt, Frankfurt am Main 60438, Germany
| | - James H. Hurley
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, CA 94720, USA
- California Institute for Quantitative Biosciences, University of California, Berkeley, CA 94720, USA
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
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13
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Winogradoff D, Chou HY, Maffeo C, Aksimentiev A. Percolation transition prescribes protein size-specific barrier to passive transport through the nuclear pore complex. Nat Commun 2022; 13:5138. [PMID: 36050301 PMCID: PMC9437005 DOI: 10.1038/s41467-022-32857-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 08/18/2022] [Indexed: 11/19/2022] Open
Abstract
Nuclear pore complexes (NPCs) control biomolecular transport in and out of the nucleus. Disordered nucleoporins in the complex's pore form a permeation barrier, preventing unassisted transport of large biomolecules. Here, we combine coarse-grained simulations of experimentally derived NPC structures with a theoretical model to determine the microscopic mechanism of passive transport. Brute-force simulations of protein transport reveal telegraph-like behavior, where prolonged diffusion on one side of the NPC is interrupted by rapid crossings to the other. We rationalize this behavior using a theoretical model that reproduces the energetics and kinetics of permeation solely from statistics of transient voids within the disordered mesh. As the protein size increases, the mesh transforms from a soft to a hard barrier, enabling orders-of-magnitude reduction in permeation rate for proteins beyond the percolation size threshold. Our model enables exploration of alternative NPC architectures and sets the stage for uncovering molecular mechanisms of facilitated nuclear transport.
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Affiliation(s)
- David Winogradoff
- grid.35403.310000 0004 1936 9991Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL 61801 USA ,grid.35403.310000 0004 1936 9991Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, IL 61801 USA
| | - Han-Yi Chou
- grid.35403.310000 0004 1936 9991Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL 61801 USA
| | - Christopher Maffeo
- grid.35403.310000 0004 1936 9991Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL 61801 USA ,grid.35403.310000 0004 1936 9991Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801 USA
| | - Aleksei Aksimentiev
- Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA. .,Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA. .,Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
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14
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Santos DES, Coutinho K, Soares TA. Surface Assessment via Grid Evaluation (SuAVE) for Every Surface Curvature and Cavity Shape. J Chem Inf Model 2022; 62:4690-4701. [PMID: 35946873 PMCID: PMC9554907 DOI: 10.1021/acs.jcim.2c00673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
![]()
The surface assessment via grid evaluation
(SuAVE)
software was developed to account for the effect of curvature in the
calculations of structural properties of chemical interfaces regardless
of the chemical composition, asymmetry, and level of atom coarseness.
It employs differential geometry techniques, enabling the representation
of chemical surfaces as fully differentiable. In this article, we
present novel developments of SuAVE to treat closed surfaces and complex
cavity shapes. These developments expand the repertoire of curvature-dependent
analyses already available in the previous version of SuAVE (e.g., area per lipid, density profiles, membrane thickness,
deuterium-order parameters, volume per lipid, and surface curvature
angle) to include new functionalities applicable to soft matter (e.g., sphericity, average radius, principal moment of inertia,
and roundness) and crystalline porous materials (e.g., pore diameter, internal void volume, total area, and the total
void volume of the unit cell structure). SuAVE can accurately handle
chemical systems with high and low atom density as demonstrated for
two distinct chemical systems: the lipid A vesicle and a set of selected
metal–organic frameworks. The SuAVE software v2.0 is fully
parallel and benefits from a compiler that supports OpenMP. SuAVE
is freely available from https://github.com/SuAVE-Software/source and https://www.biomatsite.net/.
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Affiliation(s)
- Denys E S Santos
- Departamento de Química Fundamental, Universidade Federal de Pernambuco, Cidade Universitária, Recife 50740-560, Brazil
| | - Kaline Coutinho
- Instituto de Física, Universidade de São Paulo, Cidade Universitária, São Paulo 05508-090, Brazil
| | - Thereza A Soares
- Instituto de Física, Universidade de São Paulo, Cidade Universitária, São Paulo 05508-090, Brazil.,Hylleraas Centre for Quantum Molecular Sciences, University of Oslo, 0315 Oslo, Norway
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15
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Casalino L, Seitz C, Lederhofer J, Tsybovsky Y, Wilson IA, Kanekiyo M, Amaro RE. Breathing and tilting: mesoscale simulations illuminate influenza glycoprotein vulnerabilities. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2022:2022.08.02.502576. [PMID: 35982676 PMCID: PMC9387122 DOI: 10.1101/2022.08.02.502576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Influenza virus has resurfaced recently from inactivity during the early stages of the COVID-19 pandemic, raising serious concerns about the nature and magnitude of future epidemics. The main antigenic targets of influenza virus are two surface glycoproteins, hemagglutinin (HA) and neuraminidase (NA). Whereas the structural and dynamical properties of both glycoproteins have been studied previously, the understanding of their plasticity in the whole-virion context is fragmented. Here, we investigate the dynamics of influenza glycoproteins in a crowded protein environment through mesoscale all-atom molecular dynamics simulations of two evolutionary-linked glycosylated influenza A whole-virion models. Our simulations reveal and kinetically characterize three main molecular motions of influenza glycoproteins: NA head tilting, HA ectodomain tilting, and HA head breathing. The flexibility of HA and NA highlights antigenically relevant conformational states, as well as facilitates the characterization of a novel monoclonal antibody, derived from human convalescent plasma, that binds to the underside of the NA head. Our work provides previously unappreciated views on the dynamics of HA and NA, advancing the understanding of their interplay and suggesting possible strategies for the design of future vaccines and antivirals against influenza.
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Affiliation(s)
- Lorenzo Casalino
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
| | - Christian Seitz
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
| | - Julia Lederhofer
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Yaroslav Tsybovsky
- Electron Microscopy Laboratory, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research sponsored by the National Cancer Institute, Frederick, MD 21702, United States
| | - Ian A. Wilson
- Department of Integrative Structural and Computational Biology and the Skaggs Institute for Chemical Biology, The Scripps Research Institute, La Jolla, CA 92037, United States
| | - Masaru Kanekiyo
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Rommie E. Amaro
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States,Corresponding author.
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16
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Larsen AH. Molecular Dynamics Simulations of Curved Lipid Membranes. Int J Mol Sci 2022; 23:ijms23158098. [PMID: 35897670 PMCID: PMC9331392 DOI: 10.3390/ijms23158098] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 07/19/2022] [Accepted: 07/20/2022] [Indexed: 02/04/2023] Open
Abstract
Eukaryotic cells contain membranes with various curvatures, from the near-plane plasma membrane to the highly curved membranes of organelles, vesicles, and membrane protrusions. These curvatures are generated and sustained by curvature-inducing proteins, peptides, and lipids, and describing these mechanisms is an important scientific challenge. In addition to that, some molecules can sense membrane curvature and thereby be trafficked to specific locations. The description of curvature sensing is another fundamental challenge. Curved lipid membranes and their interplay with membrane-associated proteins can be investigated with molecular dynamics (MD) simulations. Various methods for simulating curved membranes with MD are discussed here, including tools for setting up simulation of vesicles and methods for sustaining membrane curvature. The latter are divided into methods that exploit scaffolding virtual beads, methods that use curvature-inducing molecules, and methods applying virtual forces. The variety of simulation tools allow researcher to closely match the conditions of experimental studies of membrane curvatures.
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17
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Gupta C, Sarkar D, Tieleman DP, Singharoy A. The ugly, bad, and good stories of large-scale biomolecular simulations. Curr Opin Struct Biol 2022; 73:102338. [PMID: 35245737 DOI: 10.1016/j.sbi.2022.102338] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 11/29/2021] [Accepted: 01/24/2022] [Indexed: 12/20/2022]
Abstract
Molecular modeling of large biomolecular assemblies exemplifies a disruptive area holding both promises and contentions. Propelled by peta and exascale computing, several simulation methodologies have now matured into user-friendly tools that are successfully employed for modeling viruses, membranous nano-constructs, and key pieces of the genetic machinery. We present three unifying biophysical themes that emanate from some of the most recent multi-million atom simulation endeavors. Despite connecting molecular changes with phenotypic outcomes, the quality measures of these simulations remain questionable. We discuss the existing and upcoming strategies for constructing representative ensembles of large systems, how new computing technologies will boost this area, and make a point that integrative modeling guided by experimental data is the future of biomolecular computations.
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Affiliation(s)
- Chitrak Gupta
- School of Molecular Sciences, Center for Applied Structural Discovery, Arizona State University at Tempe, Tempe, AZ, 85282, USA; Biodesign Institute, Tempe, AZ, 85281, USA. https://twitter.com/ChitrakGupta2
| | - Daipayan Sarkar
- School of Molecular Sciences, Center for Applied Structural Discovery, Arizona State University at Tempe, Tempe, AZ, 85282, USA; MSU-DOE Plant Research Laboratory, Michigan State University, East Lansing, MI, 48824-1319, USA. https://twitter.com/17Dsarkar
| | - D Peter Tieleman
- Centre for Molecular Simulation and Department of Biological Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada.
| | - Abhishek Singharoy
- School of Molecular Sciences, Center for Applied Structural Discovery, Arizona State University at Tempe, Tempe, AZ, 85282, USA; Biodesign Institute, Tempe, AZ, 85281, USA.
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18
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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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19
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Maritan M, Autin L, Karr J, Covert MW, Olson AJ, Goodsell DS. Building Structural Models of a Whole Mycoplasma Cell. J Mol Biol 2022; 434:167351. [PMID: 34774566 PMCID: PMC8752489 DOI: 10.1016/j.jmb.2021.167351] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 11/04/2021] [Accepted: 11/05/2021] [Indexed: 02/01/2023]
Abstract
Building structural models of entire cells has been a long-standing cross-discipline challenge for the research community, as it requires an unprecedented level of integration between multiple sources of biological data and enhanced methods for computational modeling and visualization. Here, we present the first 3D structural models of an entire Mycoplasma genitalium (MG) cell, built using the CellPACK suite of computational modeling tools. Our model recapitulates the data described in recent whole-cell system biology simulations and provides a structural representation for all MG proteins, DNA and RNA molecules, obtained by combining experimental and homology-modeled structures and lattice-based models of the genome. We establish a framework for gathering, curating and evaluating these structures, exposing current weaknesses of modeling methods and the boundaries of MG structural knowledge, and visualization methods to explore functional characteristics of the genome and proteome. We compare two approaches for data gathering, a manually-curated workflow and an automated workflow that uses homologous structures, both of which are appropriate for the analysis of mesoscale properties such as crowding and volume occupancy. Analysis of model quality provides estimates of the regularization that will be required when these models are used as starting points for atomic molecular dynamics simulations.
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Affiliation(s)
- Martina Maritan
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, 92037 USA. https://twitter.com/MartinaMaritan
| | - Ludovic Autin
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, 92037 USA. https://twitter.com/grinche
| | - Jonathan Karr
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Markus W Covert
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Arthur J Olson
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, 92037 USA
| | - David S Goodsell
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, 92037 USA; RCSB Protein Data Bank and Institute for Quantitative Biomedicine, Rutgers, the State University of New Jersey, Piscataway, NJ 08854, USA.
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20
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Integrative structural modelling and visualisation of a cellular organelle. QRB DISCOVERY 2022. [PMID: 37529283 PMCID: PMC10392685 DOI: 10.1017/qrd.2022.10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
Abstract
Models of insulin secretory vesicles from pancreatic beta cells have been created using the cellPACK suite of tools to research, curate, construct and visualise the current state of knowledge. The model integrates experimental information from proteomics, structural biology, cryoelectron microscopy and X-ray tomography, and is used to generate models of mature and immature vesicles. A new method was developed to generate a confidence score that reconciles inconsistencies between three available proteomes using expert annotations of cellular localisation. The models are used to simulate soft X-ray tomograms, allowing quantification of features that are observed in experimental tomograms, and in turn, allowing interpretation of X-ray tomograms at the molecular level.
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21
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Dommer A, Casalino L, Kearns F, Rosenfeld M, Wauer N, Ahn SH, Russo J, Oliveira S, Morris C, Bogetti A, Trifan A, Brace A, Sztain T, Clyde A, Ma H, Chennubhotla C, Lee H, Turilli M, Khalid S, Tamayo-Mendoza T, Welborn M, Christensen A, Smith DGA, Qiao Z, Sirumalla SK, O'Connor M, Manby F, Anandkumar A, Hardy D, Phillips J, Stern A, Romero J, Clark D, Dorrell M, Maiden T, Huang L, McCalpin J, Woods C, Gray A, Williams M, Barker B, Rajapaksha H, Pitts R, Gibbs T, Stone J, Zuckerman D, Mulholland A, Miller T, Jha S, Ramanathan A, Chong L, Amaro R. #COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy of Delta SARS-CoV-2 in a Respiratory Aerosol. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.11.12.468428. [PMID: 34816263 PMCID: PMC8609898 DOI: 10.1101/2021.11.12.468428] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/12/2023]
Abstract
We seek to completely revise current models of airborne transmission of respiratory viruses by providing never-before-seen atomic-level views of the SARS-CoV-2 virus within a respiratory aerosol. Our work dramatically extends the capabilities of multiscale computational microscopy to address the significant gaps that exist in current experimental methods, which are limited in their ability to interrogate aerosols at the atomic/molecular level and thus ob-scure our understanding of airborne transmission. We demonstrate how our integrated data-driven platform provides a new way of exploring the composition, structure, and dynamics of aerosols and aerosolized viruses, while driving simulation method development along several important axes. We present a series of initial scientific discoveries for the SARS-CoV-2 Delta variant, noting that the full scientific impact of this work has yet to be realized. ACM REFERENCE FORMAT Abigail Dommer 1† , Lorenzo Casalino 1† , Fiona Kearns 1† , Mia Rosenfeld 1 , Nicholas Wauer 1 , Surl-Hee Ahn 1 , John Russo, 2 Sofia Oliveira 3 , Clare Morris 1 , AnthonyBogetti 4 , AndaTrifan 5,6 , Alexander Brace 5,7 , TerraSztain 1,8 , Austin Clyde 5,7 , Heng Ma 5 , Chakra Chennubhotla 4 , Hyungro Lee 9 , Matteo Turilli 9 , Syma Khalid 10 , Teresa Tamayo-Mendoza 11 , Matthew Welborn 11 , Anders Christensen 11 , Daniel G. A. Smith 11 , Zhuoran Qiao 12 , Sai Krishna Sirumalla 11 , Michael O'Connor 11 , Frederick Manby 11 , Anima Anandkumar 12,13 , David Hardy 6 , James Phillips 6 , Abraham Stern 13 , Josh Romero 13 , David Clark 13 , Mitchell Dorrell 14 , Tom Maiden 14 , Lei Huang 15 , John McCalpin 15 , Christo- pherWoods 3 , Alan Gray 13 , MattWilliams 3 , Bryan Barker 16 , HarindaRajapaksha 16 , Richard Pitts 16 , Tom Gibbs 13 , John Stone 6 , Daniel Zuckerman 2 *, Adrian Mulholland 3 *, Thomas MillerIII 11,12 *, ShantenuJha 9 *, Arvind Ramanathan 5 *, Lillian Chong 4 *, Rommie Amaro 1 *. 2021. #COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy ofDeltaSARS-CoV-2 in a Respiratory Aerosol. In Supercomputing '21: International Conference for High Perfor-mance Computing, Networking, Storage, and Analysis . ACM, New York, NY, USA, 14 pages. https://doi.org/finalDOI.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Anda Trifan
- Argonne National Laboratory
- University of Illinois at Urbana-Champaign
| | | | | | - Austin Clyde
- Argonne National Laboratory
- University of Chicago
| | | | | | - Hyungro Lee
- Brookhaven National Lab & Rutgers University
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - John Stone
- University of Illinois at Urbana-Champaign
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22
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Casalino L, Dommer AC, Gaieb Z, Barros EP, Sztain T, Ahn SH, Trifan A, Brace A, Bogetti AT, Clyde A, Ma H, Lee H, Turilli M, Khalid S, Chong LT, Simmerling C, Hardy DJ, Maia JD, Phillips JC, Kurth T, Stern AC, Huang L, McCalpin JD, Tatineni M, Gibbs T, Stone JE, Jha S, Ramanathan A, Amaro RE. AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics. THE INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2021; 35:432-451. [PMID: 38603008 PMCID: PMC8064023 DOI: 10.1177/10943420211006452] [Citation(s) in RCA: 60] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
We develop a generalizable AI-driven workflow that leverages heterogeneous HPC resources to explore the time-dependent dynamics of molecular systems. We use this workflow to investigate the mechanisms of infectivity of the SARS-CoV-2 spike protein, the main viral infection machinery. Our workflow enables more efficient investigation of spike dynamics in a variety of complex environments, including within a complete SARS-CoV-2 viral envelope simulation, which contains 305 million atoms and shows strong scaling on ORNL Summit using NAMD. We present several novel scientific discoveries, including the elucidation of the spike's full glycan shield, the role of spike glycans in modulating the infectivity of the virus, and the characterization of the flexible interactions between the spike and the human ACE2 receptor. We also demonstrate how AI can accelerate conformational sampling across different systems and pave the way for the future application of such methods to additional studies in SARS-CoV-2 and other molecular systems.
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Affiliation(s)
- Lorenzo Casalino
- University of California San Diego, La Jolla, CA, USA
- Authors with symbol indicate equal contribution
| | - Abigail C Dommer
- University of California San Diego, La Jolla, CA, USA
- Authors with symbol indicate equal contribution
| | - Zied Gaieb
- University of California San Diego, La Jolla, CA, USA
- Authors with symbol indicate equal contribution
| | | | - Terra Sztain
- University of California San Diego, La Jolla, CA, USA
| | - Surl-Hee Ahn
- University of California San Diego, La Jolla, CA, USA
| | - Anda Trifan
- Argonne National Lab, Lemont, IL, USA
- University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | | | | | - Austin Clyde
- Argonne National Lab, Lemont, IL, USA
- University of Chicago, Chicago, IL, USA
| | - Heng Ma
- Argonne National Lab, Lemont, IL, USA
| | | | | | | | | | | | - David J Hardy
- University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Julio Dc Maia
- University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | | | | | | | - Lei Huang
- Texas Advanced Computing Center, Austin, TX, USA
| | | | | | - Tom Gibbs
- NVIDIA Corporation, Santa Clara, CA, USA
| | - John E Stone
- University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Shantenu Jha
- Rutgers University, Piscataway, NJ, USA
- Brookhaven National Lab, Upton, NY, USA
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23
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Wilson E, Vant J, Layton J, Boyd R, Lee H, Turilli M, Hernández B, Wilkinson S, Jha S, Gupta C, Sarkar D, Singharoy A. Large-Scale Molecular Dynamics Simulations of Cellular Compartments. Methods Mol Biol 2021; 2302:335-356. [PMID: 33877636 DOI: 10.1007/978-1-0716-1394-8_18] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
Molecular dynamics or MD simulation is gradually maturing into a tool for constructing in vivo models of living cells in atomistic details. The feasibility of such models is bolstered by integrating the simulations with data from microscopic, tomographic and spectroscopic experiments on exascale supercomputers, facilitated by the use of deep learning technologies. Over time, MD simulation has evolved from tens of thousands of atoms to over 100 million atoms comprising an entire cell organelle, a photosynthetic chromatophore vesicle from a purple bacterium. In this chapter, we present a step-by-step outline for preparing, executing and analyzing such large-scale MD simulations of biological systems that are essential to life processes. All scripts are provided via GitHub.
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Affiliation(s)
- Eric Wilson
- The School of Molecular Sciences, Arizona State University, Tempe, AZ, USA
| | - John Vant
- The School of Molecular Sciences, Arizona State University, Tempe, AZ, USA
| | - Jacob Layton
- The School of Molecular Sciences, Arizona State University, Tempe, AZ, USA
| | - Ryan Boyd
- The School of Molecular Sciences, Arizona State University, Tempe, AZ, USA
| | - Hyungro Lee
- RADICAL, ECE, Rutgers University, Piscataway, NJ, USA
| | | | | | | | - Shantenu Jha
- RADICAL, ECE, Rutgers University, Piscataway, NJ, USA.,Brookhaven National Laboratory, Upton, NY, USA
| | - Chitrak Gupta
- The School of Molecular Sciences, Arizona State University, Tempe, AZ, USA.
| | - Daipayan Sarkar
- The School of Molecular Sciences, Arizona State University, Tempe, AZ, USA. .,Department of Biological Sciences, Purdue University, West Lafayette, IN, USA.
| | - Abhishek Singharoy
- The School of Molecular Sciences, Arizona State University, Tempe, AZ, USA.
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24
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Machado MR, Pantano S. Fighting viruses with computers, right now. Curr Opin Virol 2021; 48:91-99. [PMID: 33975154 DOI: 10.1016/j.coviro.2021.04.004] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 03/20/2021] [Accepted: 04/06/2021] [Indexed: 10/21/2022]
Abstract
The synergistic conjunction of various technological revolutions with the accumulated knowledge and workflows is rapidly transforming several scientific fields. Particularly, Virology can now feed from accurate physical models, polished computational tools, and massive computational power to readily integrate high-resolution structures into biological representations of unprecedented detail. That preparedness allows for the first time to get crucial information for vaccine and drug design from in-silico experiments against emerging pathogens of worldwide concern at relevant action windows. The present work reviews some of the main milestones leading to these breakthroughs in Computational Virology, providing an outlook for future developments in capacity building and accessibility to computational resources.
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Affiliation(s)
- Matías R Machado
- Biomolecular Simulations Group, Institut Pasteur de Montevideo, Mataojo 2020, Montevideo, 11400, Uruguay.
| | - Sergio Pantano
- Biomolecular Simulations Group, Institut Pasteur de Montevideo, Mataojo 2020, Montevideo, 11400, Uruguay.
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25
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Nguyen N, Strnad O, Klein T, Luo D, Alharbi R, Wonka P, Maritan M, Mindek P, Autin L, Goodsell DS, Viola I. Modeling in the Time of COVID-19: Statistical and Rule-based Mesoscale Models. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2021; 27:722-732. [PMID: 33055034 PMCID: PMC8642830 DOI: 10.1109/tvcg.2020.3030415] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 07/31/2020] [Accepted: 08/14/2020] [Indexed: 06/11/2023]
Abstract
We present a new technique for the rapid modeling and construction of scientifically accurate mesoscale biological models. The resulting 3D models are based on a few 2D microscopy scans and the latest knowledge available about the biological entity, represented as a set of geometric relationships. Our new visual-programming technique is based on statistical and rule-based modeling approaches that are rapid to author, fast to construct, and easy to revise. From a few 2D microscopy scans, we determine the statistical properties of various structural aspects, such as the outer membrane shape, the spatial properties, and the distribution characteristics of the macromolecular elements on the membrane. This information is utilized in the construction of the 3D model. Once all the imaging evidence is incorporated into the model, additional information can be incorporated by interactively defining the rules that spatially characterize the rest of the biological entity, such as mutual interactions among macromolecules, and their distances and orientations relative to other structures. These rules are defined through an intuitive 3D interactive visualization as a visual-programming feedback loop. We demonstrate the applicability of our approach on a use case of the modeling procedure of the SARS-CoV-2 virion ultrastructure. This atomistic model, which we present here, can steer biological research to new promising directions in our efforts to fight the spread of the virus.
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Affiliation(s)
- Ngan Nguyen
- King Abdullah University of Science and Technology (KAUST)Saudi Arabia
| | - Ondřej Strnad
- King Abdullah University of Science and Technology (KAUST)Saudi Arabia
| | | | - Deng Luo
- King Abdullah University of Science and Technology (KAUST)Saudi Arabia
| | - Ruwayda Alharbi
- King Abdullah University of Science and Technology (KAUST)Saudi Arabia
| | - Peter Wonka
- King Abdullah University of Science and Technology (KAUST)Saudi Arabia
| | | | | | | | | | - Ivan Viola
- King Abdullah University of Science and Technology (KAUST)Saudi Arabia
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26
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Soñora M, Martínez L, Pantano S, Machado MR. Wrapping Up Viruses at Multiscale Resolution: Optimizing PACKMOL and SIRAH Execution for Simulating the Zika Virus. J Chem Inf Model 2021; 61:408-422. [PMID: 33415985 DOI: 10.1021/acs.jcim.0c01205] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Simulating huge biomolecular complexes of million atoms at relevant biological time scales is becoming accessible to the broad scientific community. That proves to be crucial for urgent responses against emergent diseases in real time. Yet, there are still issues to sort regarding the system setup so that molecular dynamics (MD) simulations can be run in a simple and standard way. Here, we introduce an optimized pipeline for building and simulating enveloped virus-like particles (VLP). First, the membrane packing problem is tackled with new features and optimized options in PACKMOL. This allows preparing accurate membrane models of thousands of lipids in the context of a VLP within a few hours using a single CPU. Then, the assembly of the VLP system is done within the multiscale framework of the coarse-grained SIRAH force field. Finally, the equilibration protocol provides a system ready for production MD simulations within a few days on broadly accessible GPU resources. The pipeline is applied to study the Zika virus as a test case for large biomolecular systems. The VLP stabilizes at approximately 0.5 μs of MD simulation, reproducing correlations greater than 0.90 against experimental density maps from cryo-electron microscopy. Detailed structural analysis of the protein envelope also shows very good agreement in root-mean-square deviations and B-factors with the experimental data. The level of details attained shows for the first time a possible role for anionic phospholipids in stabilizing the envelope. Combining an efficient and reliable setup procedure with an accurate coarse-grained force field provides a valuable pipeline for simulating arbitrary viral systems or subcellular compartments, paving the way toward whole-cell simulations.
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Affiliation(s)
- Martín Soñora
- Biomolecular Simulations Group, Institut Pasteur de Montevideo, Mataojo 2020, Montevideo, 11400, Uruguay
| | - Leandro Martínez
- Institute of Chemistry and Center for Computational Engineering & Science, University of Campinas, Rua Josué de Castro s/n, Cidade Universitária "Zeferino Vaz", Barão Geraldo, 13083-861 Campinas, SP, Brazil
| | - Sergio Pantano
- Biomolecular Simulations Group, Institut Pasteur de Montevideo, Mataojo 2020, Montevideo, 11400, Uruguay
| | - Matías R Machado
- Biomolecular Simulations Group, Institut Pasteur de Montevideo, Mataojo 2020, Montevideo, 11400, Uruguay
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27
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Casalino L, Dommer A, Gaieb Z, Barros EP, Sztain T, Ahn SH, Trifan A, Brace A, Bogetti A, Ma H, Lee H, Turilli M, Khalid S, Chong L, Simmerling C, Hardy DJ, Maia JDC, Phillips JC, Kurth T, Stern A, Huang L, McCalpin J, Tatineni M, Gibbs T, Stone JE, Jha S, Ramanathan A, Amaro RE. AI-Driven Multiscale Simulations Illuminate Mechanisms of SARS-CoV-2 Spike Dynamics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2020:2020.11.19.390187. [PMID: 33236007 PMCID: PMC7685317 DOI: 10.1101/2020.11.19.390187] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/17/2023]
Abstract
We develop a generalizable AI-driven workflow that leverages heterogeneous HPC resources to explore the time-dependent dynamics of molecular systems. We use this workflow to investigate the mechanisms of infectivity of the SARS-CoV-2 spike protein, the main viral infection machinery. Our workflow enables more efficient investigation of spike dynamics in a variety of complex environments, including within a complete SARS-CoV-2 viral envelope simulation, which contains 305 million atoms and shows strong scaling on ORNL Summit using NAMD. We present several novel scientific discoveries, including the elucidation of the spike's full glycan shield, the role of spike glycans in modulating the infectivity of the virus, and the characterization of the flexible interactions between the spike and the human ACE2 receptor. We also demonstrate how AI can accelerate conformational sampling across different systems and pave the way for the future application of such methods to additional studies in SARS-CoV-2 and other molecular systems.
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Affiliation(s)
| | | | | | | | | | | | - Anda Trifan
- Argonne National Lab
- University of Illinois at Urbana-Champaign
| | | | | | | | - Hyungro Lee
- Rutgers University & Brookhaven National Lab
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28
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Pezeshkian W, König M, Wassenaar TA, Marrink SJ. Backmapping triangulated surfaces to coarse-grained membrane models. Nat Commun 2020; 11:2296. [PMID: 32385270 PMCID: PMC7210967 DOI: 10.1038/s41467-020-16094-y] [Citation(s) in RCA: 75] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 04/07/2020] [Indexed: 12/14/2022] Open
Abstract
Many biological processes involve large-scale changes in membrane shape. Computer simulations of these processes are challenging since they occur across a wide range of spatiotemporal scales that cannot be investigated in full by any single current simulation technique. A potential solution is to combine different levels of resolution through a multiscale scheme. Here, we present a multiscale algorithm that backmaps a continuum membrane model represented as a dynamically triangulated surface (DTS) to its corresponding molecular model based on the coarse-grained (CG) Martini force field. Thus, we can use DTS simulations to equilibrate slow large-scale membrane conformational changes and then explore the local properties at CG resolution. We demonstrate the power of our method by backmapping a vesicular bud induced by binding of Shiga toxin and by transforming the membranes of an entire mitochondrion to near-atomic resolution. Our approach opens the way to whole cell simulations at molecular detail. Computer simulations of large-scale changes in membrane shape are challenging since they occur across a wide range of spatiotemporal scales. Here, authors present a multiscale algorithm that backmaps a continuum membrane model represented as a dynamically triangulated surface to its corresponding molecular model based on the coarse-grained Martini force field.
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Affiliation(s)
- Weria Pezeshkian
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen, Groningen, Netherlands.
| | - Melanie König
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen, Groningen, Netherlands
| | - Tsjerk A Wassenaar
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen, Groningen, Netherlands
| | - Siewert J Marrink
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen, Groningen, Netherlands.
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29
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Singharoy A, Maffeo C, Delgado-Magnero KH, Swainsbury DJK, Sener M, Kleinekathöfer U, Vant JW, Nguyen J, Hitchcock A, Isralewitz B, Teo I, Chandler DE, Stone JE, Phillips JC, Pogorelov TV, Mallus MI, Chipot C, Luthey-Schulten Z, Tieleman DP, Hunter CN, Tajkhorshid E, Aksimentiev A, Schulten K. Atoms to Phenotypes: Molecular Design Principles of Cellular Energy Metabolism. Cell 2019; 179:1098-1111.e23. [PMID: 31730852 PMCID: PMC7075482 DOI: 10.1016/j.cell.2019.10.021] [Citation(s) in RCA: 105] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Revised: 09/04/2019] [Accepted: 10/21/2019] [Indexed: 01/01/2023]
Abstract
We report a 100-million atom-scale model of an entire cell organelle, a photosynthetic chromatophore vesicle from a purple bacterium, that reveals the cascade of energy conversion steps culminating in the generation of ATP from sunlight. Molecular dynamics simulations of this vesicle elucidate how the integral membrane complexes influence local curvature to tune photoexcitation of pigments. Brownian dynamics of small molecules within the chromatophore probe the mechanisms of directional charge transport under various pH and salinity conditions. Reproducing phenotypic properties from atomistic details, a kinetic model evinces that low-light adaptations of the bacterium emerge as a spontaneous outcome of optimizing the balance between the chromatophore's structural integrity and robust energy conversion. Parallels are drawn with the more universal mitochondrial bioenergetic machinery, from whence molecular-scale insights into the mechanism of cellular aging are inferred. Together, our integrative method and spectroscopic experiments pave the way to first-principles modeling of whole living cells.
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Affiliation(s)
- Abhishek Singharoy
- School of Molecular Sciences, Center for Applied Structural Discovery, Arizona State University at Tempe, Tempe, AZ 85282, USA.
| | - Christopher Maffeo
- Department of Physics, NSF Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Karelia H Delgado-Magnero
- Centre for Molecular Simulation and Department of Biological Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - David J K Swainsbury
- Department of Molecular Biology and Biotechnology, University of Sheffield, Sheffield S10 2TN, UK
| | - Melih Sener
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Ulrich Kleinekathöfer
- Department of Physics and Earth Sciences, Jacobs University Bremen, 28759 Bremen, Germany
| | - John W Vant
- School of Molecular Sciences, Center for Applied Structural Discovery, Arizona State University at Tempe, Tempe, AZ 85282, USA
| | - Jonathan Nguyen
- School of Molecular Sciences, Center for Applied Structural Discovery, Arizona State University at Tempe, Tempe, AZ 85282, USA
| | - Andrew Hitchcock
- Department of Molecular Biology and Biotechnology, University of Sheffield, Sheffield S10 2TN, UK
| | - Barry Isralewitz
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Ivan Teo
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Danielle E Chandler
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - John E Stone
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - James C Phillips
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Taras V Pogorelov
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Department of Chemistry, School of Chemical Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - M Ilaria Mallus
- Department of Physics and Earth Sciences, Jacobs University Bremen, 28759 Bremen, Germany
| | - Christophe Chipot
- Department of Physics, NSF Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Laboratoire International Associé CNRS-UIUC, UMR 7019, Université de Lorraine, 54506 Vandœuvre-lès-Nancy, France
| | - Zaida Luthey-Schulten
- Department of Physics, NSF Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Department of Chemistry, School of Chemical Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - D Peter Tieleman
- Centre for Molecular Simulation and Department of Biological Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - C Neil Hunter
- Department of Molecular Biology and Biotechnology, University of Sheffield, Sheffield S10 2TN, UK.
| | - Emad Tajkhorshid
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Departments of Biochemistry, Chemistry, Bioengineering, and Pharmacology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
| | - Aleksei Aksimentiev
- Department of Physics, NSF Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
| | - Klaus Schulten
- Department of Physics, NSF Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
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30
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Sun W, Reyes-Serratos E, Barilla D, Santos JRL, Bujold M, Graves S, Marcet-Palacios M. Mathematical determination of the HIV-1 matrix shell structure and its impact on the biology of HIV-1. PLoS One 2019; 14:e0224965. [PMID: 31714942 PMCID: PMC6850549 DOI: 10.1371/journal.pone.0224965] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Accepted: 10/26/2019] [Indexed: 11/21/2022] Open
Abstract
Since its discovery in the early 1980s, there has been significant progress in understanding the biology of type 1 human immunodeficiency virus (HIV-1). Structural biologists have made tremendous contributions to this challenge, guiding the development of current therapeutic strategies. Despite our efforts, there are unresolved structural features of the virus and consequently, significant knowledge gaps in our understanding. The superstructure of the HIV-1 matrix (MA) shell has not been elucidated. Evidence by various high-resolution microscopy techniques support a model composed of MA trimers arranged in a hexameric configuration consisting of 6 MA trimers forming a hexagon. In this manuscript we review the mathematical limitations of this model and propose a new model consisting of a 6-lune hosohedra structure, which aligns with available structural evidence. We used geometric and rotational matrix computation methods to construct our model and predict a new mechanism for viral entry that explains the increase in particle size observed during CD4 receptor engagement and the most common HIV-1 ellipsoidal shapes observed in cryo-EM tomograms. A better understanding of the HIV-1 MA shell structure is a key step towards better models for viral assembly, maturation and entry. Our new model will facilitate efforts to improve understanding of the biology of HIV-1.
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Affiliation(s)
- Weijie Sun
- Department of Medicine, Alberta Respiratory Centre, University of Alberta, Edmonton, Alberta, Canada
| | - Eduardo Reyes-Serratos
- Department of Medicine, Alberta Respiratory Centre, University of Alberta, Edmonton, Alberta, Canada
| | - David Barilla
- Department of Medicine, Alberta Respiratory Centre, University of Alberta, Edmonton, Alberta, Canada
| | - Joy Ramielle L. Santos
- Department of Biological Sciences Technology, Laboratory Research and Biotechnology, Northern Alberta Institute of Technology, Edmonton, Alberta, Canada
| | - Mattéa Bujold
- Department of Biological Sciences Technology, Laboratory Research and Biotechnology, Northern Alberta Institute of Technology, Edmonton, Alberta, Canada
| | - Sean Graves
- Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - Marcelo Marcet-Palacios
- Department of Medicine, Alberta Respiratory Centre, University of Alberta, Edmonton, Alberta, Canada
- Department of Biological Sciences Technology, Laboratory Research and Biotechnology, Northern Alberta Institute of Technology, Edmonton, Alberta, Canada
- * E-mail:
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31
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Bhatia H, Ingólfsson HI, Carpenter TS, Lightstone FC, Bremer PT. MemSurfer: A Tool for Robust Computation and Characterization of Curved Membranes. J Chem Theory Comput 2019; 15:6411-6421. [DOI: 10.1021/acs.jctc.9b00453] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
- Harsh Bhatia
- Center for Applied Scientific Computing, Computation Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - Helgi I. Ingólfsson
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - Timothy S. Carpenter
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - Felice C. Lightstone
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - Peer-Timo Bremer
- Center for Applied Scientific Computing, Computation Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
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32
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Abstract
Symmetry plays a functional role in the structure and action of biomolecules and their associations and interactions in living cells. This symmetry is a natural consequence of the evolutionary mechanisms that lead to the development of life, and it ranges from perfect point-group symmetry in protein oligomers to more approximate symmetries in the higher-order mesoscale structure of cellular environments.
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33
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Marrink SJ, Corradi V, Souza PC, Ingólfsson HI, Tieleman DP, Sansom MS. Computational Modeling of Realistic Cell Membranes. Chem Rev 2019; 119:6184-6226. [PMID: 30623647 PMCID: PMC6509646 DOI: 10.1021/acs.chemrev.8b00460] [Citation(s) in RCA: 422] [Impact Index Per Article: 84.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Indexed: 12/15/2022]
Abstract
Cell membranes contain a large variety of lipid types and are crowded with proteins, endowing them with the plasticity needed to fulfill their key roles in cell functioning. The compositional complexity of cellular membranes gives rise to a heterogeneous lateral organization, which is still poorly understood. Computational models, in particular molecular dynamics simulations and related techniques, have provided important insight into the organizational principles of cell membranes over the past decades. Now, we are witnessing a transition from simulations of simpler membrane models to multicomponent systems, culminating in realistic models of an increasing variety of cell types and organelles. Here, we review the state of the art in the field of realistic membrane simulations and discuss the current limitations and challenges ahead.
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Affiliation(s)
- Siewert J. Marrink
- Groningen
Biomolecular Sciences and Biotechnology Institute & Zernike Institute
for Advanced Materials, University of Groningen, Nijenborgh 7, 9747 AG Groningen, The Netherlands
| | - Valentina Corradi
- Centre
for Molecular Simulation and Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Paulo C.T. Souza
- Groningen
Biomolecular Sciences and Biotechnology Institute & Zernike Institute
for Advanced Materials, University of Groningen, Nijenborgh 7, 9747 AG Groningen, The Netherlands
| | - Helgi I. Ingólfsson
- Biosciences
and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550, United States
| | - D. Peter Tieleman
- Centre
for Molecular Simulation and Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Mark S.P. Sansom
- Department
of Biochemistry, University of Oxford, South Parks Road, Oxford OX1 3QU, U.K.
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34
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Smith DJ, Klauda JB, Sodt AJ. Simulation Best Practices for Lipid Membranes [Article v1.0]. LIVING JOURNAL OF COMPUTATIONAL MOLECULAR SCIENCE 2019; 1:5966. [PMID: 36204133 PMCID: PMC9534443 DOI: 10.33011/livecoms.1.1.5966] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/06/2023]
Abstract
We establish a reliable and robust standardization of settings for practical molecular dynamics (MD) simulations of pure and mixed (single- and multi-component) lipid bilayer membranes. In lipid membranes research, particle-based molecular simulations are a powerful tool alongside continuum theory, lipidomics, and model, in vitro, and in vivo experiments. Molecular simulations can provide precise and reproducible spatiotemporal (atomic- and femtosecond-level) information about membrane structure, mechanics, thermodynamics, kinetics, and dynamics. Yet the simulation of lipid membranes can be a daunting task, given the uniqueness of lipid membranes relative to conventional liquid-liquid and solid-liquid interfaces, the immense and complex thermodynamic and statistical mechanical theory, the diversity of multiscale lipid models, limitations of modern computing power, the difficulty and ambiguity of simulation controls, finite size effects, competitive continuum simulation alternatives, and the desired application, including vesicle experiments and biological membranes. These issues can complicate an essential understanding of the field of lipid membranes, and create major bottlenecks to simulation advancement. In this article, we clarify these issues and present a consistent, thorough, and user-friendly framework for the design of state-of-the-art lipid membrane MD simulations. We hope to allow early-career researchers to quickly overcome common obstacles in the field of lipid membranes and reach maximal impact in their simulations.
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Affiliation(s)
- David J. Smith
- Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, CA, USA
| | - Jeffery B. Klauda
- Department of Chemical and Biomolecular Engineering and Biophysics Program, University of Maryland, College Park, MD, USA
| | - Alexander J. Sodt
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
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35
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Huber RG, Carpenter TS, Dube N, Holdbrook DA, Ingólfsson HI, Irvine WA, Marzinek JK, Samsudin F, Allison JR, Khalid S, Bond PJ. Multiscale Modeling and Simulation Approaches to Lipid-Protein Interactions. Methods Mol Biol 2019; 2003:1-30. [PMID: 31218611 DOI: 10.1007/978-1-4939-9512-7_1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Lipid membranes play a crucial role in living systems by compartmentalizing biological processes and forming a barrier between these processes and the environment. Naturally, a large apparatus of biomolecules is responsible for construction, maintenance, transport, and degradation of these lipid barriers. Additional classes of biomolecules are tasked with transport of specific substances or transduction of signals from the environment across lipid membranes. In this article, we intend to describe a set of techniques that enable one to build accurate models of lipid systems and their associated proteins, and to simulate their dynamics over a variety of time and length scales. We discuss the methods and challenges that allow us to derive structural, mechanistic, and thermodynamic information from these models. We also show how these models have recently been applied in research to study some of the most complex lipid-protein systems to date, including bacterial and viral envelopes, neuronal membranes, and mammalian signaling systems.
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Affiliation(s)
- Roland G Huber
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Timothy S Carpenter
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA, USA
| | - Namita Dube
- Department of Chemistry, University of Cambridge, Cambridge, UK
| | - Daniel A Holdbrook
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Helgi I Ingólfsson
- Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA, USA
| | - William A Irvine
- Centre for Theoretical Chemistry and Physics, Institute of Natural and Mathematical Sciences, Massey University, Auckland, New Zealand
| | - Jan K Marzinek
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | | | - Jane R Allison
- School of Biological Sciences and Maurice Wilkins Centre for Molecular Biodiscovery, The University of Auckland, Auckland, New Zealand
- Biomolecular Interaction Centre, University of Canterbury, Christchurch, New Zealand
| | - Syma Khalid
- School of Chemistry, University of Southampton, Southampton, UK
| | - Peter J Bond
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore.
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36
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Boyd KJ, May ER. BUMPy: A Model-Independent Tool for Constructing Lipid Bilayers of Varying Curvature and Composition. J Chem Theory Comput 2018; 14:6642-6652. [PMID: 30431272 DOI: 10.1021/acs.jctc.8b00765] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Molecular dynamics is a powerful tool to investigate atomistic and mesoscopic phenomena in lipid bilayer systems. These studies have progressed with the advent of increased computational power, and efforts are now increasingly being directed toward investigating the role of curvature and bilayer morphology, as these are critical features of biological processes. Computational studies of lipid bilayers benefit from tools that can create starting configurations for molecular dynamics simulations, but the majority of such tools are restricted to generating flat bilayers. Generating curved bilayer configurations comes with practical complications and potential ramifications on physical properties in the simulated system if the bilayer is initiated in a high-strain state. We present a new tool for creating curved lipid bilayers that combines flexibility of shape, force field, model resolution, and bilayer composition. A key aspect of our approach is the use of the monolayer pivotal plane location to accurately estimate interleaflet area differences in a curved bilayer. Our tool is named BUMPy (Building Unique Membranes in Python), is written in Python, is fast, and has a simple command line interface.
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Affiliation(s)
- Kevin J Boyd
- Department of Molecular and Cell Biology , University of Connecticut , Storrs , Connecticut 06269 , United States
| | - Eric R May
- Department of Molecular and Cell Biology , University of Connecticut , Storrs , Connecticut 06269 , United States
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37
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Amaro RE, Ieong PU, Huber G, Dommer A, Steven AC, Bush RM, Durrant JD, Votapka LW. A Computational Assay that Explores the Hemagglutinin/Neuraminidase Functional Balance Reveals the Neuraminidase Secondary Site as a Novel Anti-Influenza Target. ACS CENTRAL SCIENCE 2018; 4:1570-1577. [PMID: 30555910 PMCID: PMC6276040 DOI: 10.1021/acscentsci.8b00666] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Indexed: 05/09/2023]
Abstract
Studies of pathogen-host specificity, virulence, and transmissibility are critical for basic research as well as for assessing the pandemic potential of emerging infectious diseases. This is especially true for viruses such as influenza, which continue to affect millions of people annually through both seasonal and occasional pandemic events. Although the influenza virus has been fairly well studied for decades, our understanding of host-cell binding and its relation to viral transmissibility and infection is still incomplete. Assessing the binding mechanisms of complex biological systems with atomic-scale detail is challenging given current experimental limitations. Much remains to be learned, for example, about how the terminal residue of influenza-binding host-cell receptors (sialic acid) interacts with the viral surface. Here, we present an integrative structural-modeling and physics-based computational assay that reveals the sialic acid association rate constants (k on) to three influenza sites: the hemagglutinin (HA), neuraminidase (NA) active, and NA secondary binding sites. We developed a series of highly detailed (atomic-resolution) structural models of fully intact influenza viral envelopes. Brownian dynamics simulations of these systems showed how structural properties, such as stalk height and secondary-site binding, affect sialic acid k on values. Comparing the k on values of the three sialic acid binding sites across different viral strains suggests a detailed model of encounter-complex formation and indicates that the secondary NA binding site may play a compensatory role in host-cell receptor binding. Our method elucidates the competition among these sites, all present on the same virion, and provides a new technology for directly studying the functional balance between HA and NA.
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Affiliation(s)
- Rommie E. Amaro
- Department
of Chemistry and Biochemistry, University
of California, San Diego, La Jolla, California, United States
- E-mail: . (R.E.A.)
| | - Pek U Ieong
- Department
of Chemistry and Biochemistry, University
of California, San Diego, La Jolla, California, United States
| | - Gary Huber
- Department
of Chemistry and Biochemistry, University
of California, San Diego, La Jolla, California, United States
| | - Abigail Dommer
- Department
of Chemistry and Biochemistry, University
of California, San Diego, La Jolla, California, United States
| | - Alasdair C. Steven
- Structural
Biology Laboratory, National Institutes
of Health, Bethesda, Maryland, United States
| | - Robin M. Bush
- Department
of Ecology and Evolutionary Biology, University
of California, Irvine, Irvine, California, United States
| | - Jacob D. Durrant
- Department
of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
- E-mail: . (J.D.D.)
| | - Lane W. Votapka
- Department
of Chemistry, Point Loma Nazarene University, San Diego, California, United States
- E-mail: . (L.W.V.)
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38
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Goodsell DS, Franzen MA, Herman T. From Atoms to Cells: Using Mesoscale Landscapes to Construct Visual Narratives. J Mol Biol 2018; 430:3954-3968. [PMID: 29885327 PMCID: PMC6186495 DOI: 10.1016/j.jmb.2018.06.009] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Revised: 05/31/2018] [Accepted: 06/01/2018] [Indexed: 10/14/2022]
Abstract
Modeling and visualization of the cellular mesoscale, bridging the nanometer scale of molecules to the micrometer scale of cells, is being studied by an integrative approach. Data from structural biology, proteomics, and microscopy are combined to simulate the molecular structure of living cells. These cellular landscapes are used as research tools for hypothesis generation and testing, and to present visual narratives of the cellular context of molecular biology for dissemination, education, and outreach.
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Affiliation(s)
- David S Goodsell
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA; RCSB Protein Data Bank & Center for Integrative Proteomics Research, Rutgers State University, Piscataway, NJ 08854, USA.
| | - Margaret A Franzen
- Center for BioMolecular Modeling, Milwaukee School of Engineering, Milwaukee, WI 53202, USA
| | - Tim Herman
- Center for BioMolecular Modeling, Milwaukee School of Engineering, Milwaukee, WI 53202, USA
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39
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Huggins DJ, Biggin PC, Dämgen MA, Essex JW, Harris SA, Henchman RH, Khalid S, Kuzmanic A, Laughton CA, Michel J, Mulholland AJ, Rosta E, Sansom MSP, van der Kamp MW. Biomolecular simulations: From dynamics and mechanisms to computational assays of biological activity. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2018. [DOI: 10.1002/wcms.1393] [Citation(s) in RCA: 71] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
- David J. Huggins
- TCM Group, Cavendish Laboratory University of Cambridge Cambridge UK
- Unilever Centre, Department of Chemistry University of Cambridge Cambridge UK
- Department of Physiology and Biophysics Weill Cornell Medical College New York NY
| | | | - Marc A. Dämgen
- Department of Biochemistry University of Oxford Oxford UK
| | - Jonathan W. Essex
- School of Chemistry University of Southampton Southampton UK
- Institute for Life Sciences University of Southampton Southampton UK
| | - Sarah A. Harris
- School of Physics and Astronomy University of Leeds Leeds UK
- Astbury Centre for Structural and Molecular Biology University of Leeds Leeds UK
| | - Richard H. Henchman
- Manchester Institute of Biotechnology The University of Manchester Manchester UK
- School of Chemistry The University of Manchester Oxford UK
| | - Syma Khalid
- School of Chemistry University of Southampton Southampton UK
- Institute for Life Sciences University of Southampton Southampton UK
| | | | - Charles A. Laughton
- School of Pharmacy University of Nottingham Nottingham UK
- Centre for Biomolecular Sciences University of Nottingham Nottingham UK
| | - Julien Michel
- EaStCHEM school of Chemistry University of Edinburgh Edinburgh UK
| | - Adrian J. Mulholland
- Centre of Computational Chemistry, School of Chemistry University of Bristol Bristol UK
| | - Edina Rosta
- Department of Chemistry King's College London London UK
| | | | - Marc W. van der Kamp
- Centre of Computational Chemistry, School of Chemistry University of Bristol Bristol UK
- School of Biochemistry, Biomedical Sciences Building University of Bristol Bristol UK
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40
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Amaro RE, Mulholland AJ. Multiscale Methods in Drug Design Bridge Chemical and Biological Complexity in the Search for Cures. Nat Rev Chem 2018; 2:0148. [PMID: 30949587 PMCID: PMC6445369 DOI: 10.1038/s41570-018-0148] [Citation(s) in RCA: 94] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Drug action is inherently multiscale: it connects molecular interactions to emergent properties at cellular and larger scales. Simulation techniques at each of these different scales are already central to drug design and development, but methods capable of connecting across these scales will extend understanding of complex mechanisms and the ability to predict biological effects. Improved algorithms, ever-more-powerful computing architectures and the accelerating growth of rich datasets are driving advances in multiscale modeling methods capable of bridging chemical and biological complexity from the atom to the cell. Particularly exciting is the development of highly detailed, structure-based, physical simulations of biochemical systems, which are now able to access experimentally relevant timescales for large systems and, at the same time, achieve unprecedented accuracy. In this Perspective, we discuss how emerging data-rich, physics-based multiscale approaches are of the cusp of realizing long-promised impact in the discovery, design and development of novel therapeutics. We highlight emerging methods and applications in this growing field, and outline how different scales can be combined in practical modelling and simulation strategies.
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Affiliation(s)
- Rommie E Amaro
- Department of Chemistry and Biochemistry, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093-0304
| | - Adrian J Mulholland
- Centre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, UK
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41
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Abstract
Mesoscale molecular modeling is providing a new window into the inner workings of living cells. Modeling of genomes, however, remains a technical challenge, due to their large size and complexity. We describe a lattice method for rapid generation of bacterial nucleoid models that integrates experimental data from a variety of biophysical techniques and provides a starting point for simulation and hypothesis generation. The current method builds models of a circular bacterial genome with supercoiled plectonemes, packed within the small space of the bacterial cell. Lattice models are generated for Mycoplasma genitalium and Escherichia coli nucleoids, and used to simulate interaction data. The method is rapid enough to allow generation of multiple models when analyzing structure/function relationships, and we demonstrate use of the lattice models in creation of an all-atom representation of an entire cell.
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Affiliation(s)
- David S Goodsell
- Department of Integrative Structural and Computational Biology , The Scripps Research Institute , 10550 North Torrey Pines Road , La Jolla , California , United States.,Center for Integrative Proteomics Research , Rutgers State University , 174 Frelinghuysen Road , Piscataway , New Jersey , United States
| | - Ludovic Autin
- Department of Integrative Structural and Computational Biology , The Scripps Research Institute , 10550 North Torrey Pines Road , La Jolla , California , United States
| | - Arthur J Olson
- Department of Integrative Structural and Computational Biology , The Scripps Research Institute , 10550 North Torrey Pines Road , La Jolla , California , United States
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42
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Klein T, Autin L, Kozlikova B, Goodsell DS, Olson A, Groller ME, Viola I. Instant Construction and Visualization of Crowded Biological Environments. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2018; 24:862-872. [PMID: 28866533 PMCID: PMC5746312 DOI: 10.1109/tvcg.2017.2744258] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
We present the first approach to integrative structural modeling of the biological mesoscale within an interactive visual environment. These complex models can comprise up to millions of molecules with defined atomic structures, locations, and interactions. Their construction has previously been attempted only within a non-visual and non-interactive environment. Our solution unites the modeling and visualization aspect, enabling interactive construction of atomic resolution mesoscale models of large portions of a cell. We present a novel set of GPU algorithms that build the basis for the rapid construction of complex biological structures. These structures consist of multiple membrane-enclosed compartments including both soluble molecules and fibrous structures. The compartments are defined using volume voxelization of triangulated meshes. For membranes, we present an extension of the Wang Tile concept that populates the bilayer with individual lipids. Soluble molecules are populated within compartments distributed according to a Halton sequence. Fibrous structures, such as RNA or actin filaments, are created by self-avoiding random walks. Resulting overlaps of molecules are resolved by a forced-based system. Our approach opens new possibilities to the world of interactive construction of cellular compartments. We demonstrate its effectiveness by showcasing scenes of different scale and complexity that comprise blood plasma, mycoplasma, and HIV.
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43
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Trovato F, Fumagalli G. Molecular simulations of cellular processes. Biophys Rev 2017; 9:941-958. [PMID: 29185136 DOI: 10.1007/s12551-017-0363-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Accepted: 11/19/2017] [Indexed: 12/12/2022] Open
Abstract
It is, nowadays, possible to simulate biological processes in conditions that mimic the different cellular compartments. Several groups have performed these calculations using molecular models that vary in performance and accuracy. In many cases, the atomistic degrees of freedom have been eliminated, sacrificing both structural complexity and chemical specificity to be able to explore slow processes. In this review, we will discuss the insights gained from computer simulations on macromolecule diffusion, nuclear body formation, and processes involving the genetic material inside cell-mimicking spaces. We will also discuss the challenges to generate new models suitable for the simulations of biological processes on a cell scale and for cell-cycle-long times, including non-equilibrium events such as the co-translational folding, misfolding, and aggregation of proteins. A prominent role will be played by the wise choice of the structural simplifications and, simultaneously, of a relatively complex energetic description. These challenging tasks will rely on the integration of experimental and computational methods, achieved through the application of efficient algorithms. Graphical abstract.
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Affiliation(s)
- Fabio Trovato
- Department of Mathematics and Computer Science, Freie Universität Berlin, Arnimallee 6, 14195, Berlin, Germany.
| | - Giordano Fumagalli
- Nephrology and Dialysis Unit, USL Toscana Nord Ovest, 55041, Lido di Camaiore, Lucca, Italy
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44
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Lipid topology and electrostatic interactions underpin lytic activity of linear cationic antimicrobial peptides in membranes. Proc Natl Acad Sci U S A 2017; 114:E8324-E8332. [PMID: 28931578 DOI: 10.1073/pnas.1704489114] [Citation(s) in RCA: 52] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
Linear cationic antimicrobial peptides are a diverse class of molecules that interact with a wide range of cell membranes. Many of these peptides disrupt cell integrity by forming membrane-spanning pores that ultimately lead to their death. Despite these peptides high potency and ability to evade acquired bacterial drug resistance, there is a lack of knowledge on their selectivity and activity mechanisms. Such an understanding would provide an informative framework for rational design and could lead to potential antimicrobial therapeutic targets. In this paper, we use a high-throughput microfluidic platform as a quantitative screen to assess peptide activity and selectivity by precisely controlling exposure to vesicles with lipid compositions that mimic both bacterial and mammalian cell membranes. We explore the complexity of the lipid-peptide interactions governing membrane-disruptive behaviors and establish a link between peptide pore formation and both lipid-peptide charge and topological interactions. We propose a topological model for linear antimicrobial peptide activity based on the increase in membrane strain caused by the continuous adsorption of peptides to the target vesicle coupled with the effects of both lipid-peptide charge and topographical interactions. We also show the validity of the proposed model by investigating the activity of two prototypical linear cationic peptides: magainin 2 amide (which is selective for bacterial cells) and melittin (which targets both mammalian and bacterial cells indiscriminately). Finally, we propose the existence of a negative feedback mechanism that governs the pore formation process and controls the membrane's apparent permeability.
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45
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Ropp P, Friedman A, Durrant JD. Scoria: a Python module for manipulating 3D molecular data. J Cheminform 2017; 9:52. [PMID: 29086076 PMCID: PMC5603467 DOI: 10.1186/s13321-017-0237-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2017] [Accepted: 09/04/2017] [Indexed: 01/19/2023] Open
Abstract
Third-party packages have transformed the Python programming language into a powerful computational-biology tool. Package installation is easy for experienced users, but novices sometimes struggle with dependencies and compilers. This presents a barrier that can hinder the otherwise broad adoption of new tools. We present Scoria, a Python package for manipulating three-dimensional molecular data. Unlike similar packages, Scoria requires no dependencies, compilation, or system-wide installation. One can incorporate the Scoria source code directly into their own programs. But Scoria is not designed to compete with other similar packages. Rather, it complements them. Our package leverages others (e.g. NumPy, SciPy), if present, to speed and extend its own functionality. To show its utility, we use Scoria to analyze a molecular dynamics trajectory. Our FootPrint script colors the atoms of one chain by the frequency of their contacts with a second chain. We are hopeful that Scoria will be a useful tool for the computational-biology community. A copy is available for download free of charge (Apache License 2.0) at http://durrantlab.com/scoria/.. ![]()
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Affiliation(s)
- Patrick Ropp
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, 15260, USA
| | - Aaron Friedman
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, 92093, USA
| | - Jacob D Durrant
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, 15260, USA.
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46
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Reddy T, Sansom MSP. Computational virology: From the inside out. BIOCHIMICA ET BIOPHYSICA ACTA 2016; 1858:1610-8. [PMID: 26874202 PMCID: PMC4884666 DOI: 10.1016/j.bbamem.2016.02.007] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2015] [Revised: 02/05/2016] [Accepted: 02/08/2016] [Indexed: 12/23/2022]
Abstract
Viruses typically pack their genetic material within a protein capsid. Enveloped viruses also have an outer membrane made up of a lipid bilayer and membrane-spanning glycoproteins. X-ray diffraction and cryoelectron microscopy provide high resolution static views of viral structure. Molecular dynamics (MD) simulations may be used to provide dynamic insights into the structures of viruses and their components. There have been a number of simulations of viral capsids and (in some cases) of the inner core of RNA or DNA packaged within them. These simulations have generally focussed on the structural integrity and stability of the capsid and/or on the influence of the nucleic acid core on capsid stability. More recently there have been a number of simulation studies of enveloped viruses, including HIV-1, influenza A, and dengue virus. These have addressed the dynamic behaviour of the capsid, the matrix, and/or of the outer envelope. Analysis of the dynamics of the lipid bilayer components of the envelopes of influenza A and of dengue virus reveals a degree of biophysical robustness, which may contribute to the stability of virus particles in different environments. Significant computational challenges need to be addressed to aid simulation of complex viruses and their membranes, including the need to integrate structural data from a range of sources to enable us to move towards simulations of intact virions. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.
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Affiliation(s)
- Tyler Reddy
- Department of Biochemistry, University of Oxford, South Parks Road, Oxford OX1 3QU, UK
| | - Mark S P Sansom
- Department of Biochemistry, University of Oxford, South Parks Road, Oxford OX1 3QU, UK.
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47
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Reddy T, Sansom MSP. The Role of the Membrane in the Structure and Biophysical Robustness of the Dengue Virion Envelope. Structure 2016; 24:375-82. [PMID: 26833387 PMCID: PMC4780862 DOI: 10.1016/j.str.2015.12.011] [Citation(s) in RCA: 66] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2015] [Revised: 12/15/2015] [Accepted: 12/22/2015] [Indexed: 01/11/2023]
Abstract
The dengue virion is surrounded by an envelope of membrane proteins surrounding a lipid bilayer. We have combined the cryoelectron microscopy structures of the membrane proteins (PDB: 3J27) with a lipid bilayer whose composition is based on lipidomics data for insect cell membranes, to obtain a near-atomic resolution computational model of the envelope of the dengue virion. A coarse-grained molecular dynamics simulation on the microsecond timescale enables analysis of key biophysical properties of the dengue outer envelope. Properties analyzed include area per lipid values (for a spherical virion with a mixed lipid composition), bilayer thickness, and lipid diffusion coefficients. Despite the absence of cholesterol from the lipid bilayer, the virion exhibits biophysical robustness (slow lipid diffusion alongside stable bilayer thickness, virion diameter, and shape) that matches the cholesterol-rich membrane of influenza A, with similarly anomalous diffusion of lipids. Biophysical robustness of the envelope may confer resilience to environmental perturbations. The dengue virus envelope is a lipid bilayer plus an outer layer of membrane proteins The structures of the proteins plus lipidomics data were used to model the envelope Microsecond MD simulations revealed the dynamic behavior of the lipid bilayer Protein interactions confer “raft-like” robustness on a cholesterol-free membrane
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Affiliation(s)
- Tyler Reddy
- Department of Biochemistry, University of Oxford, South Parks Road, Oxford OX1 3QU, UK
| | - Mark S P Sansom
- Department of Biochemistry, University of Oxford, South Parks Road, Oxford OX1 3QU, UK.
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48
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Qi Y, Ingólfsson HI, Cheng X, Lee J, Marrink SJ, Im W. CHARMM-GUI Martini Maker for Coarse-Grained Simulations with the Martini Force Field. J Chem Theory Comput 2015; 11:4486-94. [PMID: 26575938 DOI: 10.1021/acs.jctc.5b00513] [Citation(s) in RCA: 271] [Impact Index Per Article: 30.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Coarse-grained simulations are widely used to study large biological systems. Nonetheless, building such simulation systems becomes nontrivial, especially when membranes with various lipid types are involved. Taking advantage of the frameworks in all-atom CHARMM-GUI modules, we have developed CHARMM-GUI Martini Maker for building solution, micelle, bilayer, and vesicle systems as well as systems with randomly distributed lipids using the Martini force field. Martini Maker supports 82 lipid types and different flavors of the Martini force field, including polar and nonpolar Martini, Dry Martini, and ElNeDyn (an elastic network model for proteins). The qualities of the systems generated by Martini Maker are validated by simulations of various examples involving proteins and lipids. We expect Martini Maker to be a useful tool for modeling large, complicated biomolecular systems in a user-friendly way.
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Affiliation(s)
- Yifei Qi
- Department of Molecular Biosciences and Center for Computational Biology, The University of Kansas , 2030 Becker Drive, Lawrence, Kansas 66047, United States
| | - Helgi I Ingólfsson
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen , Nijenborgh 7, 9747 AG Groningen, The Netherlands
| | - Xi Cheng
- Department of Molecular Biosciences and Center for Computational Biology, The University of Kansas , 2030 Becker Drive, Lawrence, Kansas 66047, United States
| | - Jumin Lee
- Department of Molecular Biosciences and Center for Computational Biology, The University of Kansas , 2030 Becker Drive, Lawrence, Kansas 66047, United States
| | - Siewert J Marrink
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen , Nijenborgh 7, 9747 AG Groningen, The Netherlands
| | - Wonpil Im
- Department of Molecular Biosciences and Center for Computational Biology, The University of Kansas , 2030 Becker Drive, Lawrence, Kansas 66047, United States
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49
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Jefferys E, Sands ZA, Shi J, Sansom MS, Fowler PW. Alchembed: A Computational Method for Incorporating Multiple Proteins into Complex Lipid Geometries. J Chem Theory Comput 2015; 11:2743-2754. [PMID: 26089745 PMCID: PMC4467903 DOI: 10.1021/ct501111d] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2014] [Indexed: 02/06/2023]
Abstract
A necessary step prior to starting any membrane protein computer simulation is the creation of a well-packed configuration of protein(s) and lipids. Here, we demonstrate a method, alchembed, that can simultaneously and rapidly embed multiple proteins into arrangements of lipids described using either atomistic or coarse-grained force fields. During a short simulation, the interactions between the protein(s) and lipids are gradually switched on using a soft-core van der Waals potential. We validate the method on a range of membrane proteins and determine the optimal soft-core parameters required to insert membrane proteins. Since all of the major biomolecular codes include soft-core van der Waals potentials, no additional code is required to apply this method. A tutorial is included in the Supporting Information.
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Affiliation(s)
- Elizabeth Jefferys
- Department
of Biochemistry, University of Oxford, Oxford OX1 3QU, United Kingdom
| | - Zara A. Sands
- UCB
NewMedicines, Chemin
du Foriest, 1420 Braine-l’Alleud, Belgium
| | - Jiye Shi
- UCB
NewMedicines, Chemin
du Foriest, 1420 Braine-l’Alleud, Belgium
| | - Mark S.
P. Sansom
- Department
of Biochemistry, University of Oxford, Oxford OX1 3QU, United Kingdom
| | - Philip W. Fowler
- Department
of Biochemistry, University of Oxford, Oxford OX1 3QU, United Kingdom
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50
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Wassenaar TA, Ingólfsson HI, Böckmann RA, Tieleman DP, Marrink SJ. Computational Lipidomics with insane: A Versatile Tool for Generating Custom Membranes for Molecular Simulations. J Chem Theory Comput 2015; 11:2144-55. [PMID: 26574417 DOI: 10.1021/acs.jctc.5b00209] [Citation(s) in RCA: 676] [Impact Index Per Article: 75.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
For simulations of membranes and membrane proteins, the generation of the lipid bilayer is a critical step in the setup of the system. Membranes comprising multiple components pose a particular challenge, because the relative abundances need to be controlled and the equilibration of the system may take several microseconds. Here we present a comprehensive method for building membrane containing systems, characterized by simplicity and versatility. The program uses preset, coarse-grain lipid templates to build the membrane, and also allows on-the-fly generation of simple lipid types by specifying the headgroup, linker, and lipid tails on the command line. The resulting models can be equilibrated, after which a relaxed atomistic model can be obtained by reverse transformation. For multicomponent membranes, this provides an efficient means for generating equilibrated atomistic models. The method is called insane, an acronym for INSert membrANE. The program has been made available, together with the complementary method for reverse transformation, at http://cgmartini.nl/ . This work highlights the key features of insane and presents a survey of properties for a large range of lipids as a start of a computational lipidomics project.
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Affiliation(s)
- Tsjerk A Wassenaar
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen , Nijenborgh 7, 9747 AG Groningen, The Netherlands.,Computational Biology, Department of Biology, Friedrich-Alexander University of Erlangen-Nürnberg , Staudtstrasse 5, 91052 Erlangen, Germany
| | - Helgi I Ingólfsson
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen , Nijenborgh 7, 9747 AG Groningen, The Netherlands
| | - Rainer A Böckmann
- Computational Biology, Department of Biology, Friedrich-Alexander University of Erlangen-Nürnberg , Staudtstrasse 5, 91052 Erlangen, Germany
| | - D Peter Tieleman
- Centre for Molecular Simulation and Department of Biological Sciences, University of Calgary , 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Siewert J Marrink
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen , Nijenborgh 7, 9747 AG Groningen, The Netherlands
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