1
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Tiemann JKS, Szczuka M, Bouarroudj L, Oussaren M, Garcia S, Howard RJ, Delemotte L, Lindahl E, Baaden M, Lindorff-Larsen K, Chavent M, Poulain P. MDverse, shedding light on the dark matter of molecular dynamics simulations. eLife 2024; 12:RP90061. [PMID: 39212001 PMCID: PMC11364437 DOI: 10.7554/elife.90061] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/04/2024] Open
Abstract
The rise of open science and the absence of a global dedicated data repository for molecular dynamics (MD) simulations has led to the accumulation of MD files in generalist data repositories, constituting the dark matter of MD - data that is technically accessible, but neither indexed, curated, or easily searchable. Leveraging an original search strategy, we found and indexed about 250,000 files and 2000 datasets from Zenodo, Figshare and Open Science Framework. With a focus on files produced by the Gromacs MD software, we illustrate the potential offered by the mining of publicly available MD data. We identified systems with specific molecular composition and were able to characterize essential parameters of MD simulation such as temperature and simulation length, and could identify model resolution, such as all-atom and coarse-grain. Based on this analysis, we inferred metadata to propose a search engine prototype to explore the MD data. To continue in this direction, we call on the community to pursue the effort of sharing MD data, and to report and standardize metadata to reuse this valuable matter.
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Affiliation(s)
- Johanna KS Tiemann
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of CopenhagenCopenhagenDenmark
| | - Magdalena Szczuka
- Institut de Pharmacologie et Biologie Structurale, CNRS, Université de ToulouseToulouseFrance
| | - Lisa Bouarroudj
- Université Paris Cité, CNRS, Institut Jacques MonodParisFrance
| | | | | | - Rebecca J Howard
- Department of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm UniversityStockholmSweden
| | - Lucie Delemotte
- Department of applied physics, Science for Life Laboratory, KTH Royal Institute of TechnologyStockholmSweden
| | - Erik Lindahl
- Department of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm UniversityStockholmSweden
- Department of applied physics, Science for Life Laboratory, KTH Royal Institute of TechnologyStockholmSweden
| | - Marc Baaden
- Laboratoire de Biochimie Théorique, CNRS, Université Paris CitéParisFrance
| | - Kresten Lindorff-Larsen
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of CopenhagenCopenhagenDenmark
| | - Matthieu Chavent
- Institut de Pharmacologie et Biologie Structurale, CNRS, Université de ToulouseToulouseFrance
| | - Pierre Poulain
- Université Paris Cité, CNRS, Institut Jacques MonodParisFrance
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2
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Gomaz B, Pandini A, Maršavelski A, Štefanić Z. MDavocado: Analysis and Visualization of Protein Motion by Time-Dependent Angular Diagrams. J Chem Inf Model 2024; 64:5742-5748. [PMID: 39056185 DOI: 10.1021/acs.jcim.4c00650] [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: 07/28/2024]
Abstract
Extracting meaningful information from atomistic molecular dynamics (MD) simulations of proteins remains a challenging task due to the high-dimensionality and complexity of the data. MD simulations yield trajectories that contain the positions of thousands of atoms in millions of steps. Gaining a comprehensive understanding of local dynamical events across the entire trajectory is often difficult. Here, we present a novel approach to visualize MD trajectories in the form of time-dependent Ramachandran plots. Specialized data aggregation techniques are employed to address the challenge of plotting millions of data points on a single image, thereby ensuring that the analysis is independent of the molecule size and/or length of the MD simulation. This approach facilitates quick identification of flexible and dynamic regions, and its strength is the ability to simultaneously observe the movements of all amino acids over time. The Python program MDavocado is freely available at GitHub (https://github.com/zoranstefanic/MDavocado).
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Affiliation(s)
- Boris Gomaz
- Division of Physical Chemistry, Ruđer Bošković Institute, Bijenička 54, 10000 Zagreb, Croatia
| | - Alessandro Pandini
- Department of Computer Science, Brunel University London, Uxbridge UB8 3PH, United Kingdom
| | - Aleksandra Maršavelski
- Department of Chemistry, Faculty of Science, University of Zagreb, Horvatovac 102a, 10000 Zagreb, Croatia
| | - Zoran Štefanić
- Division of Physical Chemistry, Ruđer Bošković Institute, Bijenička 54, 10000 Zagreb, Croatia
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3
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Philipp M, Moth C, Ristic N, Tiemann J, Seufert F, Panfilova A, Meiler J, Hildebrand P, Stein A, Wiegreffe D, Staritzbichler R. MutationExplorer: a webserver for mutation of proteins and 3D visualization of energetic impacts. Nucleic Acids Res 2024; 52:W132-W139. [PMID: 38647044 PMCID: PMC11223880 DOI: 10.1093/nar/gkae301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 03/22/2024] [Accepted: 04/09/2024] [Indexed: 04/25/2024] Open
Abstract
The possible effects of mutations on stability and function of a protein can only be understood in the context of protein 3D structure. The MutationExplorer webserver maps sequence changes onto protein structures and allows users to study variation by inputting sequence changes. As the user enters variants, the 3D model evolves, and estimated changes in energy are highlighted. In addition to a basic per-residue input format, MutationExplorer can also upload an entire replacement sequence. Previously the purview of desktop applications, such an upload can back-mutate PDB structures to wildtype sequence in a single step. Another supported variation source is human single nucelotide polymorphisms (SNPs), genomic coordinates input in VCF format. Structures are flexibly colorable, not only by energetic differences, but also by hydrophobicity, sequence conservation, or other biochemical profiling. Coloring by interface score reveals mutation impacts on binding surfaces. MutationExplorer strives for efficiency in user experience. For example, we have prepared 45 000 PDB depositions for instant retrieval and initial display. All modeling steps are performed by Rosetta. Visualizations leverage MDsrv/Mol*. MutationExplorer is available at: http://proteinformatics.org/mutation_explorer/.
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Affiliation(s)
- Michelle Philipp
- Image and Signal Processing Group, Department of Computer Science, Leipzig University, Augustusplatz 10, 04109 Leipzig, Germany
| | - Christopher W Moth
- Vanderbilt University, Center for Structural Biology, 465 21st Ave South, Nashville, TN 37232, USA
| | - Nikola Ristic
- Institute for Medical Physics and Biophysics, Leipzig University, Härtelstraße 16-18, 04107 Leipzig, Germany
| | - Johanna K S Tiemann
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, DK-2200 Copenhagen N., Denmark
- Novozymes A/S, 2800 Kgs. Lyngby, Denmark
| | - Florian Seufert
- Institute for Medical Physics and Biophysics, Leipzig University, Härtelstraße 16-18, 04107 Leipzig, Germany
| | - Aleksandra Panfilova
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, DK-2200 Copenhagen N., Denmark
| | - Jens Meiler
- Vanderbilt University, Center for Structural Biology, 465 21st Ave South, Nashville, TN 37232, USA
- Leipzig University Medical School, Institute for Drug Discovery, Brüderstraße 34, 04103 Leipzig, Germany
| | - Peter W Hildebrand
- Institute for Medical Physics and Biophysics, Leipzig University, Härtelstraße 16-18, 04107 Leipzig, Germany
- Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI) Dresden/Leipzig, Leipzig University, Germany
- Berlin Institute of Health, 10178 Berlin, Germany
| | - Amelie Stein
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, DK-2200 Copenhagen N., Denmark
| | - Daniel Wiegreffe
- Image and Signal Processing Group, Department of Computer Science, Leipzig University, Augustusplatz 10, 04109 Leipzig, Germany
| | - René Staritzbichler
- Institute for Medical Physics and Biophysics, Leipzig University, Härtelstraße 16-18, 04107 Leipzig, Germany
- University Institute for Laboratory Medicine, Microbiology and Clinical Pathobiochemistry, University Hospital of Bielefeld University, Germany
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4
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Batebi H, Pérez-Hernández G, Rahman SN, Lan B, Kamprad A, Shi M, Speck D, Tiemann JKS, Guixà-González R, Reinhardt F, Stadler PF, Papasergi-Scott MM, Skiniotis G, Scheerer P, Kobilka BK, Mathiesen JM, Liu X, Hildebrand PW. Mechanistic insights into G-protein coupling with an agonist-bound G-protein-coupled receptor. Nat Struct Mol Biol 2024:10.1038/s41594-024-01334-2. [PMID: 38867113 DOI: 10.1038/s41594-024-01334-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2024] [Accepted: 05/14/2024] [Indexed: 06/14/2024]
Abstract
G-protein-coupled receptors (GPCRs) activate heterotrimeric G proteins by promoting guanine nucleotide exchange. Here, we investigate the coupling of G proteins with GPCRs and describe the events that ultimately lead to the ejection of GDP from its binding pocket in the Gα subunit, the rate-limiting step during G-protein activation. Using molecular dynamics simulations, we investigate the temporal progression of structural rearrangements of GDP-bound Gs protein (Gs·GDP; hereafter GsGDP) upon coupling to the β2-adrenergic receptor (β2AR) in atomic detail. The binding of GsGDP to the β2AR is followed by long-range allosteric effects that significantly reduce the energy needed for GDP release: the opening of α1-αF helices, the displacement of the αG helix and the opening of the α-helical domain. Signal propagation to the Gs occurs through an extended receptor interface, including a lysine-rich motif at the intracellular end of a kinked transmembrane helix 6, which was confirmed by site-directed mutagenesis and functional assays. From this β2AR-GsGDP intermediate, Gs undergoes an in-plane rotation along the receptor axis to approach the β2AR-Gsempty state. The simulations shed light on how the structural elements at the receptor-G-protein interface may interact to transmit the signal over 30 Å to the nucleotide-binding site. Our analysis extends the current limited view of nucleotide-free snapshots to include additional states and structural features responsible for signaling and G-protein coupling specificity.
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Affiliation(s)
- Hossein Batebi
- Universität Leipzig, Medizinische Fakultät, Institut für Medizinische Physik und Biophysik, Leipzig, Germany
- Freie Universität Berlin, Fachbereich Physik, Berlin, Germany
| | - Guillermo Pérez-Hernández
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Physics and Biophysics, Berlin, Germany
| | - Sabrina N Rahman
- University of Copenhagen, Department of Drug Design and Pharmacology, Copenhagen, Denmark
| | - Baoliang Lan
- State Key Laboratory of Membrane Biology, Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, School of Pharmaceutical Sciences, Tsinghua University, Beijing, China
| | - Antje Kamprad
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Physics and Biophysics, Group Structural Biology of Cellular Signaling, Berlin, Germany
| | - Mingyu Shi
- State Key Laboratory of Membrane Biology, Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, School of Pharmaceutical Sciences, Tsinghua University, Beijing, China
| | - David Speck
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Physics and Biophysics, Group Structural Biology of Cellular Signaling, Berlin, Germany
| | - Johanna K S Tiemann
- Universität Leipzig, Medizinische Fakultät, Institut für Medizinische Physik und Biophysik, Leipzig, Germany
- Novozymes A/S, Lyngby, Denmark
| | - Ramon Guixà-González
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Physics and Biophysics, Berlin, Germany
- Department of Biological Chemistry, Institute for Advanced Chemistry of Catalonia (IQAC-CSIC), Barcelona, Spain
| | - Franziska Reinhardt
- Universität Leipzig, Department of Computer Science, Bioinformatics, Leipzig, Germany
| | - Peter F Stadler
- Universität Leipzig, Department of Computer Science, Bioinformatics, Leipzig, Germany
| | - Makaía M Papasergi-Scott
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Georgios Skiniotis
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Patrick Scheerer
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Physics and Biophysics, Group Structural Biology of Cellular Signaling, Berlin, Germany
| | - Brian K Kobilka
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Jesper M Mathiesen
- University of Copenhagen, Department of Drug Design and Pharmacology, Copenhagen, Denmark
| | - Xiangyu Liu
- State Key Laboratory of Membrane Biology, Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, School of Pharmaceutical Sciences, Tsinghua University, Beijing, China
| | - Peter W Hildebrand
- Universität Leipzig, Medizinische Fakultät, Institut für Medizinische Physik und Biophysik, Leipzig, Germany.
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Physics and Biophysics, Berlin, Germany.
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5
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Tiemann JKS, Szczuka M, Bouarroudj L, Oussaren M, Garcia S, Howard RJ, Delemotte L, Lindahl E, Baaden M, Lindorff-Larsen K, Chavent M, Poulain P. MDverse: Shedding Light on the Dark Matter of Molecular Dynamics Simulations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.05.02.538537. [PMID: 37205542 PMCID: PMC10187166 DOI: 10.1101/2023.05.02.538537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
The rise of open science and the absence of a global dedicated data repository for molecular dynamics (MD) simulations has led to the accumulation of MD files in generalist data repositories, constituting the dark matter of MD - data that is technically accessible, but neither indexed, curated, or easily searchable. Leveraging an original search strategy, we found and indexed about 250,000 files and 2,000 datasets from Zenodo, Figshare and Open Science Framework. With a focus on files produced by the Gromacs MD software, we illustrate the potential offered by the mining of publicly available MD data. We identified systems with specific molecular composition and were able to characterize essential parameters of MD simulation such as temperature and simulation length, and could identify model resolution, such as all-atom and coarse-grain. Based on this analysis, we inferred metadata to propose a search engine prototype to explore the MD data. To continue in this direction, we call on the community to pursue the effort of sharing MD data, and to report and standardize metadata to reuse this valuable matter.
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6
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Papasergi-Scott MM, Pérez-Hernández G, Batebi H, Gao Y, Eskici G, Seven AB, Panova O, Hilger D, Casiraghi M, He F, Maul L, Gmeiner P, Kobilka BK, Hildebrand PW, Skiniotis G. Time-resolved cryo-EM of G-protein activation by a GPCR. Nature 2024; 629:1182-1191. [PMID: 38480881 DOI: 10.1038/s41586-024-07153-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 02/02/2024] [Indexed: 03/26/2024]
Abstract
G-protein-coupled receptors (GPCRs) activate heterotrimeric G proteins by stimulating guanine nucleotide exchange in the Gα subunit1. To visualize this mechanism, we developed a time-resolved cryo-EM approach that examines the progression of ensembles of pre-steady-state intermediates of a GPCR-G-protein complex. By monitoring the transitions of the stimulatory Gs protein in complex with the β2-adrenergic receptor at short sequential time points after GTP addition, we identified the conformational trajectory underlying G-protein activation and functional dissociation from the receptor. Twenty structures generated from sequential overlapping particle subsets along this trajectory, compared to control structures, provide a high-resolution description of the order of main events driving G-protein activation in response to GTP binding. Structural changes propagate from the nucleotide-binding pocket and extend through the GTPase domain, enacting alterations to Gα switch regions and the α5 helix that weaken the G-protein-receptor interface. Molecular dynamics simulations with late structures in the cryo-EM trajectory support that enhanced ordering of GTP on closure of the α-helical domain against the nucleotide-bound Ras-homology domain correlates with α5 helix destabilization and eventual dissociation of the G protein from the GPCR. These findings also highlight the potential of time-resolved cryo-EM as a tool for mechanistic dissection of GPCR signalling events.
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MESH Headings
- Humans
- Binding Sites
- Cryoelectron Microscopy
- GTP-Binding Protein alpha Subunits, Gs/chemistry
- GTP-Binding Protein alpha Subunits, Gs/drug effects
- GTP-Binding Protein alpha Subunits, Gs/metabolism
- GTP-Binding Protein alpha Subunits, Gs/ultrastructure
- Guanosine Triphosphate/metabolism
- Guanosine Triphosphate/pharmacology
- Models, Molecular
- Molecular Dynamics Simulation
- Protein Binding
- Receptors, Adrenergic, beta-2/metabolism
- Receptors, Adrenergic, beta-2/chemistry
- Receptors, Adrenergic, beta-2/ultrastructure
- Time Factors
- Enzyme Activation/drug effects
- Protein Domains
- Protein Structure, Secondary
- Signal Transduction/drug effects
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Affiliation(s)
- Makaía M Papasergi-Scott
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Guillermo Pérez-Hernández
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Physics and Biophysics, Berlin, Germany
| | - Hossein Batebi
- Institute of Medical Physics and Biophysics, Faculty of Medicine, Leipzig University, Leipzig, Germany
| | - Yang Gao
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Gözde Eskici
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Alpay B Seven
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Ouliana Panova
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Daniel Hilger
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
- Institute of Pharmaceutical Chemistry, Philipps-University of Marburg, Marburg, Germany
| | - Marina Casiraghi
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
- Dipartimento di Bioscienze, Università degli Studi di Milano, Milan, Italy
| | - Feng He
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Luis Maul
- Department of Chemistry and Pharmacy, Medicinal Chemistry, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Peter Gmeiner
- Department of Chemistry and Pharmacy, Medicinal Chemistry, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Brian K Kobilka
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Peter W Hildebrand
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Physics and Biophysics, Berlin, Germany
- Institute of Medical Physics and Biophysics, Faculty of Medicine, Leipzig University, Leipzig, Germany
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Georgios Skiniotis
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA.
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7
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Belghit H, Spivak M, Dauchez M, Baaden M, Jonquet-Prevoteau J. From complex data to clear insights: visualizing molecular dynamics trajectories. FRONTIERS IN BIOINFORMATICS 2024; 4:1356659. [PMID: 38665177 PMCID: PMC11043564 DOI: 10.3389/fbinf.2024.1356659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 03/14/2024] [Indexed: 04/28/2024] Open
Abstract
Advances in simulations, combined with technological developments in high-performance computing, have made it possible to produce a physically accurate dynamic representation of complex biological systems involving millions to billions of atoms over increasingly long simulation times. The analysis of these computed simulations is crucial, involving the interpretation of structural and dynamic data to gain insights into the underlying biological processes. However, this analysis becomes increasingly challenging due to the complexity of the generated systems with a large number of individual runs, ranging from hundreds to thousands of trajectories. This massive increase in raw simulation data creates additional processing and visualization challenges. Effective visualization techniques play a vital role in facilitating the analysis and interpretation of molecular dynamics simulations. In this paper, we focus mainly on the techniques and tools that can be used for visualization of molecular dynamics simulations, among which we highlight the few approaches used specifically for this purpose, discussing their advantages and limitations, and addressing the future challenges of molecular dynamics visualization.
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Affiliation(s)
- Hayet Belghit
- Université de Reims Champagne-Ardenne, CNRS, MEDYC, Reims, France
| | - Mariano Spivak
- Université Paris Cité, CNRS, Laboratoire de Biochimie Théorique, Paris, France
| | - Manuel Dauchez
- Université de Reims Champagne-Ardenne, CNRS, MEDYC, Reims, France
| | - Marc Baaden
- Université Paris Cité, CNRS, Laboratoire de Biochimie Théorique, Paris, France
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8
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Philipp M, Moth CW, Ristic N, Tiemann JK, Seufert F, Panfilova A, Meiler J, Hildebrand PW, Stein A, Wiegreffe D, Staritzbichler R. MUTATIONEXPLORER- A WEBSERVER FOR MUTATION OF PROTEINS AND 3D VISUALIZATION OF ENERGETIC IMPACTS. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.03.23.533926. [PMID: 38464310 PMCID: PMC10925206 DOI: 10.1101/2023.03.23.533926] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
The possible effects of mutations on stability and function of a protein can only be understood in the context of protein 3D structure. The MutationExplorer webserver maps sequence changes onto protein structures and allows users to study variation by inputting sequence changes. As the user enters variants, the 3D model evolves, and estimated changes in energy are highlighted. In addition to a basic per-residue input format, MutationExplorer can also upload an entire replacement sequence. Previously the purview of desktop applications, such an upload can back-mutate PDB structures to wildtype sequence in a single step. Another supported variation source is human single nucelotide polymorphisms (SNPs), genomic coordinates input in VCF format.
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Affiliation(s)
- Michelle Philipp
- Leipzig University, Image and Signal Processing Group, Leipzig, Germany
| | - Christopher W. Moth
- Vanderbilt University, Center for Structural Biology, Nashville, Tennessee, USA
| | - Nikola Ristic
- Leipzig University, Institute for Medical Physics and Biophysics, Leipzig, Germany
| | - Johanna K.S. Tiemann
- University of Copenhagen, Linderstrøm-Lang Centre for Protein Science, Copenhagen N., Denmark, and Novozymes A/S, Lyngby, Denmark
| | - Florian Seufert
- Leipzig University, Institute for Medical Physics and Biophysics, Leipzig, Germany
| | - Aleksandra Panfilova
- University of Copenhagen, Linderstrøm-Lang Centre for Protein Science, Copenhagen N., Denmark
| | - Jens Meiler
- Vanderbilt University, Center for Structural Biology, Nashville, Tennessee, USA, and Leipzig University Medical School, Institute for Drug Discovery, Leipzig, Germany
| | - Peter W. Hildebrand
- Leipzig University, Institute for Medical Physics and Biophysics, Leipzig, Germany, and Charité Universitätsmedizin Berlin, Institute of Medical Physics and Biophysics, Berlin, Germany, and Berlin Institute of Health, Berlin, Germany
| | - Amelie Stein
- University of Copenhagen, Linderstrøm-Lang Centre for Protein Science, Copenhagen N., Denmark
| | - Daniel Wiegreffe
- Leipzig University, Image and Signal Processing Group, Leipzig, Germany
| | - René Staritzbichler
- Leipzig University, Institute for Medical Physics and Biophysics, Leipzig, Germany
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9
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Scheidt J, Diener A, Maiworm M, Müller KR, Findeisen R, Driessens K, Tautz FS, Wagner C. Concept for the Real-Time Monitoring of Molecular Configurations during Manipulation with a Scanning Probe Microscope. THE JOURNAL OF PHYSICAL CHEMISTRY. C, NANOMATERIALS AND INTERFACES 2023; 127:13817-13836. [PMID: 37492192 PMCID: PMC10364088 DOI: 10.1021/acs.jpcc.3c02072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 06/20/2023] [Indexed: 07/27/2023]
Abstract
A bold vision in nanofabrication is the assembly of functional molecular structures using a scanning probe microscope (SPM). This approach requires continuous monitoring of the molecular configuration during manipulation. Until now, this has been impossible because the SPM tip cannot simultaneously act as an actuator and an imaging probe. Here, we implement configuration monitoring using experimental data other than images collected during the manipulation process. We model the manipulation as a partially observable Markov decision process (POMDP) and approximate the actual configuration in real time using a particle filter. To achieve this, the models underlying the POMDP are precomputed and organized in the form of a finite-state automaton, allowing the use of complex atomistic simulations. We exemplify the configuration monitoring process and reveal structural motifs behind measured force gradients. The proposed methodology marks an important step toward the piece-by-piece creation of supramolecular structures in a robotic and possibly automated manner.
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Affiliation(s)
- Joshua Scheidt
- Peter
Grünberg Institut (PGI-3), Forschungszentrum
Jülich, 52425 Jülich, Germany
- Jülich
Aachen Research Alliance (JARA)-Fundamentals of Future Information
Technology, 52425 Jülich, Germany
- Data
Science and Knowledge Engineering, Maastricht
University, 6229 EN Maastricht, The Netherlands
| | - Alexander Diener
- Peter
Grünberg Institut (PGI-3), Forschungszentrum
Jülich, 52425 Jülich, Germany
- Jülich
Aachen Research Alliance (JARA)-Fundamentals of Future Information
Technology, 52425 Jülich, Germany
- Data
Science and Knowledge Engineering, Maastricht
University, 6229 EN Maastricht, The Netherlands
| | - Michael Maiworm
- Laboratory
for Systems Theory and Automatic Control, Otto-von-Guericke-Universität Magdeburg, 39106 Magdeburg, Germany
| | - Klaus-Robert Müller
- Max
Planck Institute for Informatics, 66123 Saarbrücken, Germany
- Machine Learning
Group, Technische Universität Berlin, 10587 Berlin, Germany
- Department
of Artificial Intelligence, Korea University, Seoul 136-713, South Korea
| | - Rolf Findeisen
- Control
and Cyber-Physical Systems Laboratory, Technische
Universität Darmstadt, 64289 Darmstadt, Germany
| | - Kurt Driessens
- Data
Science and Knowledge Engineering, Maastricht
University, 6229 EN Maastricht, The Netherlands
| | - F. Stefan Tautz
- Peter
Grünberg Institut (PGI-3), Forschungszentrum
Jülich, 52425 Jülich, Germany
- Jülich
Aachen Research Alliance (JARA)-Fundamentals of Future Information
Technology, 52425 Jülich, Germany
- Department
of Artificial Intelligence, Korea University, Seoul 136-713, South Korea
| | - Christian Wagner
- Peter
Grünberg Institut (PGI-3), Forschungszentrum
Jülich, 52425 Jülich, Germany
- Jülich
Aachen Research Alliance (JARA)-Fundamentals of Future Information
Technology, 52425 Jülich, Germany
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10
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Papasergi-Scott MM, Pérez-Hernández G, Batebi H, Gao Y, Eskici G, Seven AB, Panova O, Hilger D, Casiraghi M, He F, Maul L, Gmeiner P, Kobilka BK, Hildebrand PW, Skiniotis G. Time-resolved cryo-EM of G protein activation by a GPCR. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.20.533387. [PMID: 36993214 PMCID: PMC10055275 DOI: 10.1101/2023.03.20.533387] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/31/2023]
Abstract
G protein-coupled receptors (GPCRs) activate heterotrimeric G proteins by stimulating the exchange of guanine nucleotide in the Gα subunit. To visualize this mechanism, we developed a time-resolved cryo-EM approach that examines the progression of ensembles of pre-steady-state intermediates of a GPCR-G protein complex. Using variability analysis to monitor the transitions of the stimulatory Gs protein in complex with the β 2 -adrenergic receptor (β 2 AR) at short sequential time points after GTP addition, we identified the conformational trajectory underlying G protein activation and functional dissociation from the receptor. Twenty transition structures generated from sequential overlapping particle subsets along this trajectory, compared to control structures, provide a high-resolution description of the order of events driving G protein activation upon GTP binding. Structural changes propagate from the nucleotide-binding pocket and extend through the GTPase domain, enacting alterations to Gα Switch regions and the α5 helix that weaken the G protein-receptor interface. Molecular dynamics (MD) simulations with late structures in the cryo-EM trajectory support that enhanced ordering of GTP upon closure of the alpha-helical domain (AHD) against the nucleotide-bound Ras-homology domain (RHD) correlates with irreversible α5 helix destabilization and eventual dissociation of the G protein from the GPCR. These findings also highlight the potential of time-resolved cryo-EM as a tool for mechanistic dissection of GPCR signaling events.
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11
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PacDOCK: A Web Server for Positional Distance-Based and Interaction-Based Analysis of Docking Results. MOLECULES (BASEL, SWITZERLAND) 2022; 27:molecules27206884. [PMID: 36296477 PMCID: PMC9610523 DOI: 10.3390/molecules27206884] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 10/06/2022] [Accepted: 10/12/2022] [Indexed: 11/05/2022]
Abstract
Molecular docking is a key method for structure-based drug design used to predict the conformations assumed by small drug-like ligands when bound to their target. However, the evaluation of molecular docking studies can be hampered by the lack of a free and easy to use platform for the complete analysis of results obtained by the principal docking programs. To this aim, we developed PacDOCK, a freely available and user-friendly web server that comprises a collection of tools for positional distance-based and interaction-based analysis of docking results, which can be provided in several file formats. PacDOCK allows a complete analysis of molecular docking results through root mean square deviation (RMSD) calculation, molecular visualization, and cluster analysis of docked poses. The RMSD calculation compares docked structures with a reference structure, also when atoms are randomly labelled, and their conformational and positional differences can be visualised. In addition, it is possible to visualise a ligand into the target binding pocket and investigate the key receptor–ligand interactions. Moreover, PacDOCK enables the clustering of docking results by identifying a restrained number of clusters from many docked poses. We believe that PacDOCK will contribute to facilitating the analysis of docking results to improve the efficiency of computer-aided drug design.
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12
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Kampfrath M, Staritzbichler R, Hernández GP, Rose AS, Tiemann JKS, Scheuermann G, Wiegreffe D, Hildebrand PW. MDsrv: visual sharing and analysis of molecular dynamics simulations. Nucleic Acids Res 2022; 50:W483-W489. [PMID: 35639717 PMCID: PMC9252803 DOI: 10.1093/nar/gkac398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 05/02/2022] [Accepted: 05/05/2022] [Indexed: 11/24/2022] Open
Abstract
Molecular dynamics simulation is a proven technique for computing and visualizing the time-resolved motion of macromolecules at atomic resolution. The MDsrv is a tool that streams MD trajectories and displays them interactively in web browsers without requiring advanced skills, facilitating interactive exploration and collaborative visual analysis. We have now enhanced the MDsrv to further simplify the upload and sharing of MD trajectories and improve their online viewing and analysis. With the new instance, the MDsrv simplifies the creation of sessions, which allows the exchange of MD trajectories with preset representations and perspectives. An important innovation is that the MDsrv can now access and visualize trajectories from remote datasets, which greatly expands its applicability and use, as the data no longer needs to be accessible on a local server. In addition, initial analyses such as sequence or structure alignments, distance measurements, or RMSD calculations have been implemented, which optionally support visual analysis. Finally, based on Mol*, MDsrv now provides faster and more efficient visualization of even large trajectories compared to its predecessor tool NGL.
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Affiliation(s)
- Michelle Kampfrath
- Image and Signal Processing Group, Department of Computer Science, Leipzig University, Augustusplatz 10, 04109 Leipzig, Germany
| | - René Staritzbichler
- Institute for Medical Physics and Biophysics, Medical Faculty, Leipzig University, Härtelstraße 16-18, 04107 Leipzig, Germany
| | - Guillermo Pérez Hernández
- Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Physics and Biophysics, Berlin, Germany
| | | | - Johanna K S Tiemann
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, DK-2200 Copenhagen N., Denmark
| | - Gerik Scheuermann
- Image and Signal Processing Group, Department of Computer Science, Leipzig University, Augustusplatz 10, 04109 Leipzig, Germany
| | - Daniel Wiegreffe
- Image and Signal Processing Group, Department of Computer Science, Leipzig University, Augustusplatz 10, 04109 Leipzig, Germany
| | - Peter W Hildebrand
- Institute for Medical Physics and Biophysics, Medical Faculty, Leipzig University, Härtelstraße 16-18, 04107 Leipzig, Germany.,Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Physics and Biophysics, Berlin, Germany.,Berlin Institute of Health, 10178 Berlin, Germany
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13
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Bayarri G, Andrio P, Hospital A, Orozco M, Gelpí JL. BioExcel Building Blocks Workflows (BioBB-Wfs), an integrated web-based platform for biomolecular simulations. Nucleic Acids Res 2022; 50:W99-W107. [PMID: 35639735 PMCID: PMC9252775 DOI: 10.1093/nar/gkac380] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 04/19/2022] [Accepted: 05/02/2022] [Indexed: 11/15/2022] Open
Abstract
We present BioExcel Building Blocks Workflows, a web-based graphical user interface (GUI) offering access to a collection of transversal pre-configured biomolecular simulation workflows assembled with the BioExcel Building Blocks library. Available workflows include Molecular Dynamics setup, protein-ligand docking, trajectory analyses and small molecule parameterization. Workflows can be launched in the platform or downloaded to be run in the users’ own premises. Remote launching of long executions to user's available High-Performance computers is possible, only requiring configuration of the appropriate access credentials. The web-based graphical user interface offers a high level of interactivity, with integration with the NGL viewer to visualize and check 3D structures, MDsrv to visualize trajectories, and Plotly to explore 2D plots. The server requires no login but is recommended to store the users’ projects and manage sensitive information such as remote credentials. Private projects can be made public and shared with colleagues with a simple URL. The tool will help biomolecular simulation users with the most common and repetitive processes by means of a very intuitive and interactive graphical user interface. The server is accessible at https://mmb.irbbarcelona.org/biobb-wfs.
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Affiliation(s)
- Genís Bayarri
- Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and Technology. Baldiri Reixac 10-12, 08028 Barcelona, Spain
| | - Pau Andrio
- Barcelona Supercomputing Center (BSC), Jordi Girona 29, 08034, Barcelona, Spain
| | - Adam Hospital
- Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and Technology. Baldiri Reixac 10-12, 08028 Barcelona, Spain
| | - Modesto Orozco
- Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and Technology. Baldiri Reixac 10-12, 08028 Barcelona, Spain.,Department of Biochemistry and Molecular Biology, University of Barcelona, 08028 Barcelona, Spain
| | - Josep Lluís Gelpí
- Barcelona Supercomputing Center (BSC), Jordi Girona 29, 08034, Barcelona, Spain.,Department of Biochemistry and Molecular Biology, University of Barcelona, 08028 Barcelona, Spain
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14
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Karaca E, Prévost C, Sacquin-Mora S. Modeling the Dynamics of Protein-Protein Interfaces, How and Why? Molecules 2022; 27:1841. [PMID: 35335203 PMCID: PMC8950966 DOI: 10.3390/molecules27061841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Revised: 03/06/2022] [Accepted: 03/08/2022] [Indexed: 12/07/2022] Open
Abstract
Protein-protein assemblies act as a key component in numerous cellular processes. Their accurate modeling at the atomic level remains a challenge for structural biology. To address this challenge, several docking and a handful of deep learning methodologies focus on modeling protein-protein interfaces. Although the outcome of these methods has been assessed using static reference structures, more and more data point to the fact that the interaction stability and specificity is encoded in the dynamics of these interfaces. Therefore, this dynamics information must be taken into account when modeling and assessing protein interactions at the atomistic scale. Expanding on this, our review initially focuses on the recent computational strategies aiming at investigating protein-protein interfaces in a dynamic fashion using enhanced sampling, multi-scale modeling, and experimental data integration. Then, we discuss how interface dynamics report on the function of protein assemblies in globular complexes, in fuzzy complexes containing intrinsically disordered proteins, as well as in active complexes, where chemical reactions take place across the protein-protein interface.
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Affiliation(s)
- Ezgi Karaca
- Izmir Biomedicine and Genome Center, Izmir 35340, Turkey;
- Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir 35340, Turkey
| | - Chantal Prévost
- CNRS, Laboratoire de Biochimie Théorique, UPR9080, Université de Paris, 13 rue Pierre et Marie Curie, 75005 Paris, France;
- Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, 75006 Paris, France
| | - Sophie Sacquin-Mora
- CNRS, Laboratoire de Biochimie Théorique, UPR9080, Université de Paris, 13 rue Pierre et Marie Curie, 75005 Paris, France;
- Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, 75006 Paris, France
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15
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Smith AA, Vogel A, Engberg O, Hildebrand PW, Huster D. A method to construct the dynamic landscape of a bio-membrane with experiment and simulation. Nat Commun 2022; 13:108. [PMID: 35013165 PMCID: PMC8748619 DOI: 10.1038/s41467-021-27417-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 11/11/2021] [Indexed: 11/16/2022] Open
Abstract
Biomolecular function is based on a complex hierarchy of molecular motions. While biophysical methods can reveal details of specific motions, a concept for the comprehensive description of molecular dynamics over a wide range of correlation times has been unattainable. Here, we report an approach to construct the dynamic landscape of biomolecules, which describes the aggregate influence of multiple motions acting on various timescales and on multiple positions in the molecule. To this end, we use 13C NMR relaxation and molecular dynamics simulation data for the characterization of fully hydrated palmitoyl-oleoyl-phosphatidylcholine bilayers. We combine dynamics detector methodology with a new frame analysis of motion that yields site-specific amplitudes of motion, separated both by type and timescale of motion. In this study, we show that this separation allows the detailed description of the dynamic landscape, which yields vast differences in motional amplitudes and correlation times depending on molecular position.
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Affiliation(s)
- Albert A Smith
- Institute for Medical Physics and Biophysics, Leipzig University, Härtelstr. 16-18, 04107, Leipzig, Germany.
| | - Alexander Vogel
- Institute for Medical Physics and Biophysics, Leipzig University, Härtelstr. 16-18, 04107, Leipzig, Germany
| | - Oskar Engberg
- Institute for Medical Physics and Biophysics, Leipzig University, Härtelstr. 16-18, 04107, Leipzig, Germany
| | - Peter W Hildebrand
- Institute for Medical Physics and Biophysics, Leipzig University, Härtelstr. 16-18, 04107, Leipzig, Germany
| | - Daniel Huster
- Institute for Medical Physics and Biophysics, Leipzig University, Härtelstr. 16-18, 04107, Leipzig, Germany
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16
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Torrens-Fontanals M, Peralta-García A, Talarico C, Guixà-González R, Giorgino T, Selent J. SCoV2-MD: a database for the dynamics of the SARS-CoV-2 proteome and variant impact predictions. Nucleic Acids Res 2022; 50:D858-D866. [PMID: 34761257 PMCID: PMC8689960 DOI: 10.1093/nar/gkab977] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Revised: 09/21/2021] [Accepted: 11/08/2021] [Indexed: 11/23/2022] Open
Abstract
SCoV2-MD (www.scov2-md.org) is a new online resource that systematically organizes atomistic simulations of the SARS-CoV-2 proteome. The database includes simulations produced by leading groups using molecular dynamics (MD) methods to investigate the structure-dynamics-function relationships of viral proteins. SCoV2-MD cross-references the molecular data with the pandemic evolution by tracking all available variants sequenced during the pandemic and deposited in the GISAID resource. SCoV2-MD enables the interactive analysis of the deposited trajectories through a web interface, which enables users to search by viral protein, isolate, phylogenetic attributes, or specific point mutation. Each mutation can then be analyzed interactively combining static (e.g. a variety of amino acid substitution penalties) and dynamic (time-dependent data derived from the dynamics of the local geometry) scores. Dynamic scores can be computed on the basis of nine non-covalent interaction types, including steric properties, solvent accessibility, hydrogen bonding, and other types of chemical interactions. Where available, experimental data such as antibody escape and change in binding affinities from deep mutational scanning experiments are also made available. All metrics can be combined to build predefined or custom scores to interrogate the impact of evolving variants on protein structure and function.
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Affiliation(s)
- Mariona Torrens-Fontanals
- Research Programme on Biomedical Informatics, Hospital del Mar
Medical Research Institute—Department of Experimental and Health
Sciences, Pompeu Fabra University, Barcelona 08003,
Spain
| | - Alejandro Peralta-García
- Research Programme on Biomedical Informatics, Hospital del Mar
Medical Research Institute—Department of Experimental and Health
Sciences, Pompeu Fabra University, Barcelona 08003,
Spain
| | - Carmine Talarico
- EXSCALATE, Dompé Farmaceutici S.p.A., Via
Tommaso De Amicis, 95, Napoli, 80131, Italy
| | - Ramon Guixà-González
- Laboratory of Biomolecular Research, Paul Scherrer
Institute, CH-5232 Villigen PSI, Switzerland
- Condensed Matter Theory Group, Paul Scherrer
Institute, CH-5232 Villigen PSI, Switzerland
| | - Toni Giorgino
- Biophysics Institute (CNR-IBF), National
Research Council of Italy, Milan 20133, Italy
- Department of Biosciences, University of Milan,
Milan 20133, Italy
| | - Jana Selent
- Research Programme on Biomedical Informatics, Hospital del Mar
Medical Research Institute—Department of Experimental and Health
Sciences, Pompeu Fabra University, Barcelona 08003,
Spain
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17
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Bayarri G, Hospital A, Orozco M. 3dRS, a Web-Based Tool to Share Interactive Representations of 3D Biomolecular Structures and Molecular Dynamics Trajectories. Front Mol Biosci 2021; 8:726232. [PMID: 34485386 PMCID: PMC8414788 DOI: 10.3389/fmolb.2021.726232] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 08/03/2021] [Indexed: 11/13/2022] Open
Abstract
3D Representation Sharing (3dRS) is a web-based tool designed to share biomolecular structure representations, including 4D ensembles derived from Molecular Dynamics (MD) trajectories. The server offers a team working in different locations a single URL to share and discuss structural data in an interactive fashion, with the possibility to use it as a live figure for scientific papers. The web tool allows an easy upload of structures and trajectories in different formats. The 3D representation, powered by NGL viewer, offers an interactive display with smooth visualization in modern web browsers. Multiple structures can be loaded and superposed in the same scene. 1D sequences from the loaded structures are presented and linked to the 3D representation. Multiple, pre-defined 3D molecular representations are available. The powerful NGL selection syntax allows the definition of molecular regions that can be then displayed using different representations. Important descriptors such as distances or interactions can be easily added into the representation. Trajectory frames can be explored using a common video player control panel. Trajectories are efficiently stored and transferred to the NGL viewer thanks to an MDsrv-based data streaming. The server design offers all functionalities in one single web page, with a curated user experience, involving a minimum learning curve. Extended documentation is available, including a gallery with a collection of scenes. The server requires no registration and is available at https://mmb.irbbarcelona.org/3dRS.
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Affiliation(s)
- Genís Bayarri
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
| | - Adam Hospital
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
| | - Modesto Orozco
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Departament de Bioquímica i Biomedicina, Facultat de Biologia, Universitat de Barcelona, Barcelona, Spain
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18
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Staritzbichler R, Ristic N, Goede A, Preissner R, Hildebrand PW. Voronoia 4-ever. Nucleic Acids Res 2021; 49:W685-W690. [PMID: 34107038 PMCID: PMC8265189 DOI: 10.1093/nar/gkab466] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 05/07/2021] [Accepted: 06/07/2021] [Indexed: 11/12/2022] Open
Abstract
We present an updated version of the Voronoia service that enables fully automated analysis of the atomic packing density of macromolecules. Voronoia combines previous efforts to analyse 3D protein and RNA structures into a single service, combined with state-of-the-art online visualization. Voronoia uses the Voronoi cell method to calculate the free space between neighbouring atoms to estimate van der Waals interactions. Compared to other methods that derive van der Waals interactions by calculating solvent-free surfaces, it explicitly considers volume or packing defects. Large internal voids refer either to water molecules or ions unresolved by X-ray crystallography or cryo-EM, cryptic ligand binding pockets, or parts of a structural model that require further refinement. Voronoia is, therefore mainly used for functional analyses of 3D structures and quality assessments of structural models. Voronoia 4-ever updates the database of precomputed packing densities of PDB entries, allows uploading multiple structures, adds new filter options and facilitates direct access to the results through intuitive display with the NGL viewer. Voronoia is available at: htttp://proteinformatics.org/voronoia.
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Affiliation(s)
- Rene Staritzbichler
- University of Leipzig, Institute of Medical Physics and Biophysics, Leipzig, Germany
| | - Nikola Ristic
- University of Leipzig, Institute of Medical Physics and Biophysics, Leipzig, Germany
| | - Andrean Goede
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Physiology, Structural Bioinformatics Group, Berlin 10117, Germany
| | - Robert Preissner
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Physiology, Structural Bioinformatics Group, Berlin 10117, Germany.,Charité -Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Information Technology, Science IT, Charitéplatz 1, 10117 Berlin, Germany
| | - Peter W Hildebrand
- University of Leipzig, Institute of Medical Physics and Biophysics, Leipzig, Germany.,Charité -Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Physics and Biophysics, Charitéplatz 1, 10117 Berlin, Germany.,Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany
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19
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Martinez X, Baaden M. UnityMol prototype for FAIR sharing of molecular-visualization experiences: from pictures in the cloud to collaborative virtual reality exploration in immersive 3D environments. Acta Crystallogr D Struct Biol 2021; 77:746-754. [PMID: 34076589 PMCID: PMC8171070 DOI: 10.1107/s2059798321002941] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2020] [Accepted: 03/19/2021] [Indexed: 11/14/2022] Open
Abstract
Motivated by the current COVID-19 pandemic, which has spurred a substantial flow of structural data, the use of molecular-visualization experiences to make these data sets accessible to a broad audience is described. Using a variety of technology vectors related to the cloud, 3D and virtual reality gear, how to share curated visualizations of structural biology, modeling and/or bioinformatics data sets for interactive and collaborative exploration is examined. FAIR is discussed as an overarching principle for sharing such visualizations. Four initial example scenes related to recent COVID-19 structural data are provided, together with a ready-to-use (and share) implementation in the UnityMol software.
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Affiliation(s)
- Xavier Martinez
- CNRS, Université de Paris, UPR 9080, Laboratoire de Biochimie Théorique, 13 Rue Pierre et Marie Curie, 75005 Paris, France
- Institut de Biologie Physico-Chimique–Fondation Edmond de Rothschild, PSL Research University, Paris, France
| | - Marc Baaden
- CNRS, Université de Paris, UPR 9080, Laboratoire de Biochimie Théorique, 13 Rue Pierre et Marie Curie, 75005 Paris, France
- Institut de Biologie Physico-Chimique–Fondation Edmond de Rothschild, PSL Research University, Paris, France
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20
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Beliu G, Altrichter S, Guixà-González R, Hemberger M, Brauer I, Dahse AK, Scholz N, Wieduwild R, Kuhlemann A, Batebi H, Seufert F, Pérez-Hernández G, Hildebrand PW, Sauer M, Langenhan T. Tethered agonist exposure in intact adhesion/class B2 GPCRs through intrinsic structural flexibility of the GAIN domain. Mol Cell 2021; 81:905-921.e5. [PMID: 33497605 DOI: 10.1016/j.molcel.2020.12.042] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Revised: 08/28/2020] [Accepted: 12/24/2020] [Indexed: 12/11/2022]
Abstract
Adhesion G protein-coupled receptors (aGPCRs)/family B2 GPCRs execute critical tasks during development and the operation of organs, and their genetic lesions are associated with human disorders, including cancers. Exceptional structural aGPCR features are the presence of a tethered agonist (TA) concealed within a GPCR autoproteolysis-inducing (GAIN) domain and their non-covalent heteromeric two-subunit layout. How the TA is poised for activation while maintaining this delicate receptor architecture is central to conflicting signaling paradigms that either involve or exclude aGPCR heterodimer separation. We investigated this matter in five mammalian aGPCR homologs (ADGRB3, ADGRE2, ADGRE5, ADGRG1, and ADGRL1) and demonstrate that intact aGPCR heterodimers exist at the cell surface, that the core TA region becomes unmasked in the cleaved GAIN domain, and that intra-GAIN domain movements regulate the level of tethered agonist exposure, thereby likely controlling aGPCR activity. Collectively, these findings delineate a unifying mechanism for TA-dependent signaling of intact aGPCRs.
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MESH Headings
- Amino Acid Sequence
- Animals
- Antigens, CD/chemistry
- Antigens, CD/genetics
- Antigens, CD/metabolism
- Binding Sites
- COS Cells
- Chlorocebus aethiops
- Crystallography, X-Ray
- Gene Expression
- HEK293 Cells
- Humans
- Molecular Dynamics Simulation
- Nerve Tissue Proteins/chemistry
- Nerve Tissue Proteins/genetics
- Nerve Tissue Proteins/metabolism
- Peptides/chemistry
- Peptides/genetics
- Peptides/metabolism
- Protein Binding
- Protein Conformation, alpha-Helical
- Protein Conformation, beta-Strand
- Protein Interaction Domains and Motifs
- Protein Multimerization
- Proteolysis
- Receptors, G-Protein-Coupled/chemistry
- Receptors, G-Protein-Coupled/genetics
- Receptors, G-Protein-Coupled/metabolism
- Receptors, Peptide/chemistry
- Receptors, Peptide/genetics
- Receptors, Peptide/metabolism
- Recombinant Proteins/chemistry
- Recombinant Proteins/genetics
- Recombinant Proteins/metabolism
- Sequence Alignment
- Sequence Homology, Amino Acid
- Signal Transduction
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Affiliation(s)
- Gerti Beliu
- Department of Biotechnology and Biophysics, Biocenter, University of Würzburg, Am Hubland, 97074 Würzburg, Germany
| | - Steffen Altrichter
- Rudolf Schönheimer Institute of Biochemistry, Division of General Biochemistry, Medical Faculty, Leipzig University, Johannisallee 30, 04103 Leipzig, Germany
| | - Ramon Guixà-González
- Institute for Medical Physics and Biophysics, Medical Faculty, Leipzig University, Härtelstrasse 16-18, 04107 Leipzig, Germany; Laboratory of Biomolecular Research, Paul Scherrer Institute (PSI), 5232 Villigen PSI, Switzerland; Condensed Matter Theory Group, PSI, 5232 Villigen PSI, Switzerland
| | - Mareike Hemberger
- Rudolf Schönheimer Institute of Biochemistry, Division of General Biochemistry, Medical Faculty, Leipzig University, Johannisallee 30, 04103 Leipzig, Germany
| | - Ina Brauer
- Rudolf Schönheimer Institute of Biochemistry, Division of General Biochemistry, Medical Faculty, Leipzig University, Johannisallee 30, 04103 Leipzig, Germany
| | - Anne-Kristin Dahse
- Rudolf Schönheimer Institute of Biochemistry, Division of General Biochemistry, Medical Faculty, Leipzig University, Johannisallee 30, 04103 Leipzig, Germany
| | - Nicole Scholz
- Rudolf Schönheimer Institute of Biochemistry, Division of General Biochemistry, Medical Faculty, Leipzig University, Johannisallee 30, 04103 Leipzig, Germany
| | - Robert Wieduwild
- Rudolf Schönheimer Institute of Biochemistry, Division of General Biochemistry, Medical Faculty, Leipzig University, Johannisallee 30, 04103 Leipzig, Germany
| | - Alexander Kuhlemann
- Department of Biotechnology and Biophysics, Biocenter, University of Würzburg, Am Hubland, 97074 Würzburg, Germany
| | - Hossein Batebi
- Institute for Medical Physics and Biophysics, Medical Faculty, Leipzig University, Härtelstrasse 16-18, 04107 Leipzig, Germany
| | - Florian Seufert
- Institute for Medical Physics and Biophysics, Medical Faculty, Leipzig University, Härtelstrasse 16-18, 04107 Leipzig, Germany
| | - Guillermo Pérez-Hernández
- Institute of Medical Physics and Biophysics, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Peter W Hildebrand
- Institute for Medical Physics and Biophysics, Medical Faculty, Leipzig University, Härtelstrasse 16-18, 04107 Leipzig, Germany; Institute of Medical Physics and Biophysics, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany; Berlin Institute of Health, 10178 Berlin, Germany.
| | - Markus Sauer
- Department of Biotechnology and Biophysics, Biocenter, University of Würzburg, Am Hubland, 97074 Würzburg, Germany.
| | - Tobias Langenhan
- Rudolf Schönheimer Institute of Biochemistry, Division of General Biochemistry, Medical Faculty, Leipzig University, Johannisallee 30, 04103 Leipzig, Germany.
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21
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Sehnal D, Svobodová R, Berka K, Rose AS, Burley SK, Velankar S, Koča J. High-performance macromolecular data delivery and visualization for the web. Acta Crystallogr D Struct Biol 2020; 76:1167-1173. [PMID: 33263322 PMCID: PMC7709201 DOI: 10.1107/s2059798320014515] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Accepted: 11/01/2020] [Indexed: 11/11/2022] Open
Abstract
Biomacromolecular structural data make up a vital and crucial scientific resource that has grown not only in terms of its amount but also in its size and complexity. Furthermore, these data are accompanied by large and increasing amounts of experimental data. Additionally, the macromolecular data are enriched with value-added annotations describing their biological, physicochemical and structural properties. Today, the scientific community requires fast and fully interactive web visualization to exploit this complex structural information. This article provides a survey of the available cutting-edge web services that address this challenge. Specifically, it focuses on data-delivery problems, discusses the visualization of a single structure, including experimental data and annotations, and concludes with a focus on the results of molecular-dynamics simulations and the visualization of structural ensembles.
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Affiliation(s)
- David Sehnal
- CEITEC – Central European Institute of Technology, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic
- National Centre for Biomolecular Research, Faculty of Science, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL–EBI), Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom
| | - Radka Svobodová
- CEITEC – Central European Institute of Technology, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic
- National Centre for Biomolecular Research, Faculty of Science, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic
| | - Karel Berka
- Regional Centre of Advanced Technologies and Materials, Department of Physical Chemistry, Faculty of Science, Palacký University Olomouc, Šlechtitelů 241/27, 779 00 Olomouc, Czech Republic
| | - Alexander S. Rose
- Research Collaboratory for Structural Bioinformatics (RCSB), San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, La Jolla, San Diego, CA 92093-0743, USA
| | - Stephen K. Burley
- RCSB Protein Data Bank, Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854-8076, USA
- Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, 195 Little Albany Street, New Brunswick, NJ 08903-2681, USA
- RCSB Protein Data Bank, San Diego Supercomputer Center and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0654, USA
| | - Sameer Velankar
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL–EBI), Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom
| | - Jaroslav Koča
- CEITEC – Central European Institute of Technology, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic
- National Centre for Biomolecular Research, Faculty of Science, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic
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22
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Vogel A, Bosse M, Gauglitz M, Wistuba S, Schmidt P, Kaiser A, Gurevich VV, Beck-Sickinger AG, Hildebrand PW, Huster D. The Dynamics of the Neuropeptide Y Receptor Type 1 Investigated by Solid-State NMR and Molecular Dynamics Simulation. Molecules 2020; 25:E5489. [PMID: 33255213 PMCID: PMC7727705 DOI: 10.3390/molecules25235489] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 11/09/2020] [Accepted: 11/12/2020] [Indexed: 01/08/2023] Open
Abstract
We report data on the structural dynamics of the neuropeptide Y (NPY) G-protein-coupled receptor (GPCR) type 1 (Y1R), a typical representative of class A peptide ligand GPCRs, using a combination of solid-state NMR and molecular dynamics (MD) simulation. First, the equilibrium dynamics of Y1R were studied using 15N-NMR and quantitative determination of 1H-13C order parameters through the measurement of dipolar couplings in separated-local-field NMR experiments. Order parameters reporting the amplitudes of the molecular motions of the C-H bond vectors of Y1R in DMPC membranes are 0.57 for the Cα sites and lower in the side chains (0.37 for the CH2 and 0.18 for the CH3 groups). Different NMR excitation schemes identify relatively rigid and also dynamic segments of the molecule. In monounsaturated membranes composed of longer lipid chains, Y1R is more rigid, attributed to a higher hydrophobic thickness of the lipid membrane. The presence of an antagonist or NPY has little influence on the amplitude of motions, whereas the addition of agonist and arrestin led to a pronounced rigidization. To investigate Y1R dynamics with site resolution, we conducted extensive all-atom MD simulations of the apo and antagonist-bound state. In each state, three replicas with a length of 20 μs (with one exception, where the trajectory length was 10 μs) were conducted. In these simulations, order parameters of each residue were determined and showed high values in the transmembrane helices, whereas the loops and termini exhibit much lower order. The extracellular helix segments undergo larger amplitude motions than their intracellular counterparts, whereas the opposite is observed for the loops, Helix 8, and termini. Only minor differences in order were observed between the apo and antagonist-bound state, whereas the time scale of the motions is shorter for the apo state. Although these relatively fast motions occurring with correlation times of ns up to a few µs have no direct relevance for receptor activation, it is believed that they represent the prerequisite for larger conformational transitions in proteins.
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Affiliation(s)
- Alexander Vogel
- Institute for Medical Physics and Biophysics, University of Leipzig, Härtelstr. 16-18, D-04107 Leipzig, Germany; (A.V.); (M.B.); (M.G.); (S.W.); (P.S.)
| | - Mathias Bosse
- Institute for Medical Physics and Biophysics, University of Leipzig, Härtelstr. 16-18, D-04107 Leipzig, Germany; (A.V.); (M.B.); (M.G.); (S.W.); (P.S.)
| | - Marcel Gauglitz
- Institute for Medical Physics and Biophysics, University of Leipzig, Härtelstr. 16-18, D-04107 Leipzig, Germany; (A.V.); (M.B.); (M.G.); (S.W.); (P.S.)
| | - Sarah Wistuba
- Institute for Medical Physics and Biophysics, University of Leipzig, Härtelstr. 16-18, D-04107 Leipzig, Germany; (A.V.); (M.B.); (M.G.); (S.W.); (P.S.)
| | - Peter Schmidt
- Institute for Medical Physics and Biophysics, University of Leipzig, Härtelstr. 16-18, D-04107 Leipzig, Germany; (A.V.); (M.B.); (M.G.); (S.W.); (P.S.)
| | - Anette Kaiser
- Faculty of Life Sciences, Institute of Biochemistry, University of Leipzig, Brüderstr. 34, D-04103 Leipzig, Germany; (A.K.); (A.G.B.-S.)
| | - Vsevolod V. Gurevich
- Vanderbilt University Medical Center, 2200 Pierce Avenue, Nashville, TN 37232, USA;
| | - Annette G. Beck-Sickinger
- Faculty of Life Sciences, Institute of Biochemistry, University of Leipzig, Brüderstr. 34, D-04103 Leipzig, Germany; (A.K.); (A.G.B.-S.)
| | - Peter W. Hildebrand
- Institute for Medical Physics and Biophysics, University of Leipzig, Härtelstr. 16-18, D-04107 Leipzig, Germany; (A.V.); (M.B.); (M.G.); (S.W.); (P.S.)
| | - Daniel Huster
- Institute for Medical Physics and Biophysics, University of Leipzig, Härtelstr. 16-18, D-04107 Leipzig, Germany; (A.V.); (M.B.); (M.G.); (S.W.); (P.S.)
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23
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Richardson KE, Kirkpatrick CC, Znosko BM. RNA CoSSMos 2.0: an improved searchable database of secondary structure motifs in RNA three-dimensional structures. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2020; 2020:5707338. [PMID: 31950189 PMCID: PMC6966092 DOI: 10.1093/database/baz153] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Revised: 11/12/2019] [Accepted: 12/13/2019] [Indexed: 01/29/2023]
Abstract
The RNA Characterization of Secondary Structure Motifs, RNA CoSSMos, database is a freely accessible online database that allows users to identify secondary structure motifs among RNA 3D structures and explore their structural features. RNA CoSSMos 2.0 now requires two closing base pairs for all RNA loop motifs to create a less redundant database of secondary structures. Furthermore, RNA CoSSMos 2.0 represents an upgraded database with new features that summarize search findings and aid in the search for 3D structural patterns among RNA secondary structure motifs. Previously, users were limited to viewing search results individually, with no built-in tools to compare search results. RNA CoSSMos 2.0 provides two new features, allowing users to summarize, analyze and compare their search result findings. A function has been added to the website that calculates the average and representative structures of the search results. Additionally, users can now view a summary page of their search results that reports percentages of each structural feature found, including sugar pucker, glycosidic linkage, hydrogen bonding patterns and stacking interactions. Other upgrades include a newly embedded NGL structural viewer, the option to download the clipped structure coordinates in *.pdb format and improved NMR structure results. RNA CoSSMos 2.0 is no longer simply a search engine for a structure database; it now has the capability of analyzing, comparing and summarizing search results. Database URL: http://rnacossmos.com
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Affiliation(s)
- Katherine E Richardson
- Saint Louis University, Department of Chemistry, 3501 Laclede Avenue, St. Louis, MO 63103 USA
| | - Charles C Kirkpatrick
- Saint Louis University, Department of Chemistry, 3501 Laclede Avenue, St. Louis, MO 63103 USA
| | - Brent M Znosko
- Saint Louis University, Department of Chemistry, 3501 Laclede Avenue, St. Louis, MO 63103 USA
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24
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Abstract
Modern scientific visualization is web-based and uses emerging technology such as WebGL (Web Graphics Library) and WebGPU for three-dimensional computer graphics and WebXR for augmented and virtual reality devices. These technologies, paired with the accessibility of websites, potentially offer a user experience beyond traditional standalone visualization systems. We review the state-of-the-art of web-based scientific visualization and present an overview of existing methods categorized by application domain. As part of this analysis, we introduce the Scientific Visualization Future Readiness Score (SciVis FRS) to rank visualizations for a technology-driven disruptive tomorrow. We then summarize challenges, current state of the publication trend, future directions, and opportunities for this exciting research field.
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25
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Madadlou A. Food proteins are a potential resource for mining cathepsin L inhibitory drugs to combat SARS-CoV-2. Eur J Pharmacol 2020; 885:173499. [PMID: 32841639 PMCID: PMC7443098 DOI: 10.1016/j.ejphar.2020.173499] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 08/17/2020] [Accepted: 08/21/2020] [Indexed: 01/21/2023]
Abstract
The entry of SARS-CoV-2 into host cells proceeds by a proteolysis process, which involves the lysosomal peptidase cathepsin L. Inhibition of cathepsin L is therefore considered an effective method to decrease the virus internalization. Analysis from the perspective of structure-functionality elucidates that cathepsin L inhibitory proteins/peptides found in food share specific features: multiple disulfide crosslinks (buried in protein core), lack or low contents of (small) α-helices, and high surface hydrophobicity. Lactoferrin can inhibit cathepsin L, but not cathepsins B and H. This selective inhibition might be useful in fine targeting of cathepsin L. Molecular docking indicated that only the carboxyl-terminal lobe of lactoferrin interacts with cathepsin L and that the active site cleft of cathepsin L is heavily superposed by lactoferrin. A controlled proteolysis process might yield lactoferrin-derived peptides that strongly inhibit cathepsin L.
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Affiliation(s)
- Ashkan Madadlou
- Department of Agrotechnology and Food Sciences, Wageningen University and Research, Wageningen, the Netherlands.
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26
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Torrens-Fontanals M, Stepniewski TM, Aranda-García D, Morales-Pastor A, Medel-Lacruz B, Selent J. How Do Molecular Dynamics Data Complement Static Structural Data of GPCRs. Int J Mol Sci 2020; 21:E5933. [PMID: 32824756 PMCID: PMC7460635 DOI: 10.3390/ijms21165933] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 08/11/2020] [Accepted: 08/15/2020] [Indexed: 01/08/2023] Open
Abstract
G protein-coupled receptors (GPCRs) are implicated in nearly every physiological process in the human body and therefore represent an important drug targeting class. Advances in X-ray crystallography and cryo-electron microscopy (cryo-EM) have provided multiple static structures of GPCRs in complex with various signaling partners. However, GPCR functionality is largely determined by their flexibility and ability to transition between distinct structural conformations. Due to this dynamic nature, a static snapshot does not fully explain the complexity of GPCR signal transduction. Molecular dynamics (MD) simulations offer the opportunity to simulate the structural motions of biological processes at atomic resolution. Thus, this technique can incorporate the missing information on protein flexibility into experimentally solved structures. Here, we review the contribution of MD simulations to complement static structural data and to improve our understanding of GPCR physiology and pharmacology, as well as the challenges that still need to be overcome to reach the full potential of this technique.
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Affiliation(s)
- Mariona Torrens-Fontanals
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)—Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), 08003 Barcelona, Spain; (M.T.-F.); (T.M.S.); (D.A.-G.); (A.M.-P.); (B.M.-L.)
| | - Tomasz Maciej Stepniewski
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)—Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), 08003 Barcelona, Spain; (M.T.-F.); (T.M.S.); (D.A.-G.); (A.M.-P.); (B.M.-L.)
- InterAx Biotech AG, PARK innovAARE, 5234 Villigen, Switzerland
- Faculty of Chemistry, Biological and Chemical Research Centre, University of Warsaw, 02-093 Warsaw, Poland
| | - David Aranda-García
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)—Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), 08003 Barcelona, Spain; (M.T.-F.); (T.M.S.); (D.A.-G.); (A.M.-P.); (B.M.-L.)
| | - Adrián Morales-Pastor
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)—Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), 08003 Barcelona, Spain; (M.T.-F.); (T.M.S.); (D.A.-G.); (A.M.-P.); (B.M.-L.)
| | - Brian Medel-Lacruz
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)—Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), 08003 Barcelona, Spain; (M.T.-F.); (T.M.S.); (D.A.-G.); (A.M.-P.); (B.M.-L.)
| | - Jana Selent
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)—Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), 08003 Barcelona, Spain; (M.T.-F.); (T.M.S.); (D.A.-G.); (A.M.-P.); (B.M.-L.)
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27
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Rodríguez-Espigares I, Torrens-Fontanals M, Tiemann JKS, Aranda-García D, Ramírez-Anguita JM, Stepniewski TM, Worp N, Varela-Rial A, Morales-Pastor A, Medel-Lacruz B, Pándy-Szekeres G, Mayol E, Giorgino T, Carlsson J, Deupi X, Filipek S, Filizola M, Gómez-Tamayo JC, Gonzalez A, Gutiérrez-de-Terán H, Jiménez-Rosés M, Jespers W, Kapla J, Khelashvili G, Kolb P, Latek D, Marti-Solano M, Matricon P, Matsoukas MT, Miszta P, Olivella M, Perez-Benito L, Provasi D, Ríos S, R Torrecillas I, Sallander J, Sztyler A, Vasile S, Weinstein H, Zachariae U, Hildebrand PW, De Fabritiis G, Sanz F, Gloriam DE, Cordomi A, Guixà-González R, Selent J. GPCRmd uncovers the dynamics of the 3D-GPCRome. Nat Methods 2020; 17:777-787. [PMID: 32661425 DOI: 10.1038/s41592-020-0884-y] [Citation(s) in RCA: 84] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Accepted: 05/29/2020] [Indexed: 11/08/2022]
Abstract
G-protein-coupled receptors (GPCRs) are involved in numerous physiological processes and are the most frequent targets of approved drugs. The explosion in the number of new three-dimensional (3D) molecular structures of GPCRs (3D-GPCRome) over the last decade has greatly advanced the mechanistic understanding and drug design opportunities for this protein family. Molecular dynamics (MD) simulations have become a widely established technique for exploring the conformational landscape of proteins at an atomic level. However, the analysis and visualization of MD simulations require efficient storage resources and specialized software. Here we present GPCRmd (http://gpcrmd.org/), an online platform that incorporates web-based visualization capabilities as well as a comprehensive and user-friendly analysis toolbox that allows scientists from different disciplines to visualize, analyze and share GPCR MD data. GPCRmd originates from a community-driven effort to create an open, interactive and standardized database of GPCR MD simulations.
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Affiliation(s)
- Ismael Rodríguez-Espigares
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute-Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
| | - Mariona Torrens-Fontanals
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute-Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
| | - Johanna K S Tiemann
- Institute of Medical Physics and Biophysics, Charite University Medicine Berlin, Berlin, Germany
- Institute of Medical Physics and Biophysics, Medical University Leipzig, Leipzig, Sachsen, Germany
| | - David Aranda-García
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute-Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
| | - Juan Manuel Ramírez-Anguita
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute-Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
| | - Tomasz Maciej Stepniewski
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute-Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
| | - Nathalie Worp
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute-Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
| | - Alejandro Varela-Rial
- Computational Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park, Barcelona, Spain
- Acellera, Barcelona, Spain
| | - Adrián Morales-Pastor
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute-Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
| | - Brian Medel-Lacruz
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute-Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
| | - Gáspár Pándy-Szekeres
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
| | - Eduardo Mayol
- Laboratori de Medicina Computacional, Unitat de Bioestadistica, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Toni Giorgino
- Biophysics Institute, National Research Council of Italy, Milan, Italy
- Department of Biosciences, University of Milan, Milan, Italy
| | - Jens Carlsson
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Xavier Deupi
- Laboratory of Biomolecular Research, Paul Scherrer Institute (PSI), Villigen PSI, Switzerland
- Condensed Matter Theory Group, PSI, Villigen PSI, Switzerland
| | - Slawomir Filipek
- Faculty of Chemistry, Biological and Chemical Research Centre, University of Warsaw, Warsaw, Poland
| | - Marta Filizola
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - José Carlos Gómez-Tamayo
- Laboratori de Medicina Computacional, Unitat de Bioestadistica, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Angel Gonzalez
- Laboratori de Medicina Computacional, Unitat de Bioestadistica, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Hugo Gutiérrez-de-Terán
- Department of Cell and Molecular Biology, Uppsala University, Biomedical Center, Uppsala, Sweden
| | - Mireia Jiménez-Rosés
- Laboratori de Medicina Computacional, Unitat de Bioestadistica, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Willem Jespers
- Department of Cell and Molecular Biology, Uppsala University, Biomedical Center, Uppsala, Sweden
| | - Jon Kapla
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - George Khelashvili
- Department of Physiology and Biophysics, Weill Cornell Medical College of Cornell University, New York, NY, USA
- Institute for Computational Biomedicine, Weill Cornell Medical College of Cornell University, New York, NY, USA
| | - Peter Kolb
- Department of Pharmaceutical Chemistry, Philipps-University Marburg, Marburg, Germany
| | - Dorota Latek
- Faculty of Chemistry, Biological and Chemical Research Centre, University of Warsaw, Warsaw, Poland
| | - Maria Marti-Solano
- Department of Pharmaceutical Chemistry, Philipps-University Marburg, Marburg, Germany
- MRC Laboratory of Molecular Biology, Cambridge, UK
| | - Pierre Matricon
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Minos-Timotheos Matsoukas
- Laboratori de Medicina Computacional, Unitat de Bioestadistica, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
- Department of Pharmacy, University of Patras, Patras, Greece
| | - Przemyslaw Miszta
- Faculty of Chemistry, Biological and Chemical Research Centre, University of Warsaw, Warsaw, Poland
| | - Mireia Olivella
- Laboratori de Medicina Computacional, Unitat de Bioestadistica, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Laura Perez-Benito
- Laboratori de Medicina Computacional, Unitat de Bioestadistica, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Davide Provasi
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Santiago Ríos
- Laboratori de Medicina Computacional, Unitat de Bioestadistica, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Iván R Torrecillas
- Laboratori de Medicina Computacional, Unitat de Bioestadistica, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Jessica Sallander
- Department of Cell and Molecular Biology, Uppsala University, Biomedical Center, Uppsala, Sweden
| | - Agnieszka Sztyler
- Faculty of Chemistry, Biological and Chemical Research Centre, University of Warsaw, Warsaw, Poland
| | - Silvana Vasile
- Department of Cell and Molecular Biology, Uppsala University, Biomedical Center, Uppsala, Sweden
| | - Harel Weinstein
- Department of Physiology and Biophysics, Weill Cornell Medical College of Cornell University, New York, NY, USA
- Institute for Computational Biomedicine, Weill Cornell Medical College of Cornell University, New York, NY, USA
| | - Ulrich Zachariae
- Computational Biology, School of Life Sciences, University of Dundee, Dundee, UK
- Physics, School of Science and Engineering, University of Dundee, Dundee, UK
| | - Peter W Hildebrand
- Institute of Medical Physics and Biophysics, Charite University Medicine Berlin, Berlin, Germany
- Institute of Medical Physics and Biophysics, Medical University Leipzig, Leipzig, Sachsen, Germany
- Berlin Institute of Health, Berlin, Germany
| | - Gianni De Fabritiis
- Computational Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park, Barcelona, Spain
- Acellera, Barcelona, Spain
| | - Ferran Sanz
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute-Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
| | - David E Gloriam
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
| | - Arnau Cordomi
- Laboratori de Medicina Computacional, Unitat de Bioestadistica, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Ramon Guixà-González
- Laboratory of Biomolecular Research, Paul Scherrer Institute (PSI), Villigen PSI, Switzerland.
- Condensed Matter Theory Group, PSI, Villigen PSI, Switzerland.
| | - Jana Selent
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute-Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain.
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28
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Joseph NN, Roy RN, Steitz TA. Molecular dynamics analysis of Mg 2+ -dependent cleavage of a pistol ribozyme reveals a fail-safe secondary ion for catalysis. J Comput Chem 2020; 41:1345-1352. [PMID: 32091136 DOI: 10.1002/jcc.26179] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2019] [Accepted: 01/19/2020] [Indexed: 11/08/2022]
Abstract
Pistol ribozymes comprise a class of small, self-cleaving RNAs discovered via comparative genomic analysis. Prior work in the field has probed the kinetics of the cleavage reaction, as well as the influence of various metal ion cofactors that accelerate the process. In the current study, we performed unbiased and unconstrained molecular dynamics simulations from two current high-resolution pistol crystal structures, and we analyzed trajectory data within the context of the currently accepted ribozyme mechanistic framework. Root-mean-squared deviations, radial distribution functions, and distributions of nucleophilic angle-of-attack reveal insights into the potential roles of three magnesium ions with respect to catalysis and overall conformational stability of the molecule. A series of simulation trajectories containing in silico mutations reveal the relatively flexible and partially interchangeable roles of two particular magnesium ions within solvated hydrogen-bonding distances from the catalytic center.
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Affiliation(s)
- Newlyn N Joseph
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, USA, New Haven, Connecticut.,University of Connecticut School of Medicine, Farmington, Connecticut
| | - Raktim N Roy
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, USA, New Haven, Connecticut.,Department of Integrative Structural and Computational Biology, The Scripps Research Institute, Jupiter, Florida
| | - Thomas A Steitz
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, USA, New Haven, Connecticut
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29
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Hildebrand PW, Rose AS, Tiemann JK. Bringing Molecular Dynamics Simulation Data into View. Trends Biochem Sci 2019; 44:902-913. [DOI: 10.1016/j.tibs.2019.06.004] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2019] [Revised: 06/05/2019] [Accepted: 06/12/2019] [Indexed: 12/14/2022]
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Pacheco S, Kaminsky JC, Kochnev IK, Durrant JD. PCAViz: An Open-Source Python/JavaScript Toolkit for Visualizing Molecular Dynamics Simulations in the Web Browser. J Chem Inf Model 2019; 59:4087-4092. [PMID: 31580061 PMCID: PMC6849643 DOI: 10.1021/acs.jcim.9b00703] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
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Molecular dynamics (MD) simulations
reveal molecular motions at
atomic resolution. Recent advances in high-performance computing now
enable microsecond-long simulations capable of sampling a wide range
of biologically relevant events. But the disk space required to store
an MD trajectory increases with simulation length and system size,
complicating collaborative sharing and visualization. To overcome
these limitations, we created PCAViz, an open-source toolkit for sharing
and visualizing MD trajectories via the web browser. PCAViz includes
two components: the PCAViz Compressor, which compresses and saves
simulation data; and the PCAViz Interpreter, which decompresses the
data in users’ browsers and feeds it to any of several browser-based
molecular-visualization libraries (e.g., 3Dmol.js, NGL Viewer, etc.).
An easy-to-install WordPress plugin enables “plug-and-play”
trajectory visualization. PCAViz will appeal to a broad audience of
researchers and educators. The source code is available at http://durrantlab.com/pcaviz/, and the WordPress plugin is available via the official WordPress
Plugin Directory.
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Affiliation(s)
- Sayuri Pacheco
- Department of Biological Sciences , University of Pittsburgh , Pittsburgh , Pennsylvania 15260 , United States
| | - Jesse C Kaminsky
- Department of Biological Sciences , University of Pittsburgh , Pittsburgh , Pennsylvania 15260 , United States
| | - Iurii K Kochnev
- Department of Biological Sciences , University of Pittsburgh , Pittsburgh , Pennsylvania 15260 , United States
| | - Jacob D Durrant
- Department of Biological Sciences , University of Pittsburgh , Pittsburgh , Pennsylvania 15260 , United States
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Abraham M, Apostolov R, Barnoud J, Bauer P, Blau C, Bonvin AMJJ, Chavent M, Chodera J, Čondić-Jurkić K, Delemotte L, Grubmüller H, Howard RJ, Jordan EJ, Lindahl E, Ollila OHS, Selent J, Smith DGA, Stansfeld PJ, Tiemann JKS, Trellet M, Woods C, Zhmurov A. Sharing Data from Molecular Simulations. J Chem Inf Model 2019; 59:4093-4099. [PMID: 31525920 DOI: 10.1021/acs.jcim.9b00665] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Given the need for modern researchers to produce open, reproducible scientific output, the lack of standards and best practices for sharing data and workflows used to produce and analyze molecular dynamics (MD) simulations has become an important issue in the field. There are now multiple well-established packages to perform molecular dynamics simulations, often highly tuned for exploiting specific classes of hardware, each with strong communities surrounding them, but with very limited interoperability/transferability options. Thus, the choice of the software package often dictates the workflow for both simulation production and analysis. The level of detail in documenting the workflows and analysis code varies greatly in published work, hindering reproducibility of the reported results and the ability for other researchers to build on these studies. An increasing number of researchers are motivated to make their data available, but many challenges remain in order to effectively share and reuse simulation data. To discuss these and other issues related to best practices in the field in general, we organized a workshop in November 2018 ( https://bioexcel.eu/events/workshop-on-sharing-data-from-molecular-simulations/ ). Here, we present a brief overview of this workshop and topics discussed. We hope this effort will spark further conversation in the MD community to pave the way toward more open, interoperable, and reproducible outputs coming from research studies using MD simulations.
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Affiliation(s)
- Mark Abraham
- Science for Life Laboratory, Department of Applied Physics , KTH Royal Institute of Technology , Box 1031, SE-171 21 Solna , Sweden
| | - Rossen Apostolov
- PDC Center for High Performance Computing, School of Electrical Engineering and Computer Science , KTH Royal Institute of Technology , 114 28 Stockholm , Sweden
| | | | - Paul Bauer
- Science for Life Laboratory, Department of Applied Physics , KTH Royal Institute of Technology , Box 1031, SE-171 21 Solna , Sweden
| | - Christian Blau
- Science for Life Laboratory, Department of Applied Physics , KTH Royal Institute of Technology , Box 1031, SE-171 21 Solna , Sweden
| | | | | | - John Chodera
- Computational and Systems Biology Program , Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center , New York , New York 10065 , United States
| | - Karmen Čondić-Jurkić
- Computational and Systems Biology Program , Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center , New York , New York 10065 , United States.,Open Force Field Consortium , https://openforcefield.org/consortium/
| | - Lucie Delemotte
- Science for Life Laboratory, Department of Applied Physics , KTH Royal Institute of Technology , Box 1031, SE-171 21 Solna , Sweden
| | - Helmut Grubmüller
- Max Planck Institute for Biophysical Chemistry , 37077 Goettingen , Germany
| | - Rebecca J Howard
- Science for Life Laboratory, Department of Applied Physics , KTH Royal Institute of Technology , Box 1031, SE-171 21 Solna , Sweden.,Science for Life Laboratory, Department of Biochemistry and Biophysics , Stockholm University , Box 1031, SE-171 21 Solna , Sweden
| | - E Joseph Jordan
- Science for Life Laboratory, Department of Biochemistry and Biophysics , Stockholm University , Box 1031, SE-171 21 Solna , Sweden
| | - Erik Lindahl
- Science for Life Laboratory, Department of Applied Physics , KTH Royal Institute of Technology , Box 1031, SE-171 21 Solna , Sweden.,Science for Life Laboratory, Department of Biochemistry and Biophysics , Stockholm University , Box 1031, SE-171 21 Solna , Sweden
| | - O H Samuli Ollila
- Institute of Biotechnology , University of Helsinki , 00100 Helsinki , Finland
| | - Jana Selent
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute (IMIM) & Department of Experimental and Health Sciences , Pompeu Fabra University , 08002 Barcelona , Spain
| | - Daniel G A Smith
- The Molecular Sciences Software Institute , Blacksburg , Virginia 24060 , United States
| | | | - Johanna K S Tiemann
- Institute of Medical Physics and Biophysics, Faculty of Medicine , University Leipzig , Leipzig 04107 , Germany
| | - Mikael Trellet
- Faculty of Science , Utrecht University , Bijvoet Center, Utrecht , The Netherlands
| | | | - Artem Zhmurov
- Science for Life Laboratory, Department of Applied Physics , KTH Royal Institute of Technology , Box 1031, SE-171 21 Solna , Sweden
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32
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Liu X, Xu X, Hilger D, Aschauer P, Tiemann JKS, Du Y, Liu H, Hirata K, Sun X, Guixà-González R, Mathiesen JM, Hildebrand PW, Kobilka BK. Structural Insights into the Process of GPCR-G Protein Complex Formation. Cell 2019; 177:1243-1251.e12. [PMID: 31080070 DOI: 10.1016/j.cell.2019.04.021] [Citation(s) in RCA: 112] [Impact Index Per Article: 22.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Revised: 02/25/2019] [Accepted: 04/09/2019] [Indexed: 11/17/2022]
Abstract
The crystal structure of the β2-adrenergic receptor (β2AR) bound to the G protein adenylyl cyclase stimulatory G protein (Gs) captured the complex in a nucleotide-free state (β2AR-Gsempty). Unfortunately, the β2AR-Gsempty complex does not provide a clear explanation for G protein coupling specificity. Evidence from several sources suggests the existence of a transient complex between the β2AR and GDP-bound Gs protein (β2AR-GsGDP) that may represent an intermediate on the way to the formation of β2AR-Gsempty and may contribute to coupling specificity. Here we present a structure of the β2AR in complex with the carboxyl terminal 14 amino acids from Gαs along with the structure of the GDP-bound Gs heterotrimer. These structures provide evidence for an alternate interaction between the β2AR and Gs that may represent an intermediate that contributes to Gs coupling specificity.
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Affiliation(s)
- Xiangyu Liu
- Beijing Advanced Innovation Center for Structural Biology, Tsinghua-Peking Joint Center for Life Sciences, School of Medicine, Tsinghua University, Beijing 100084, China.
| | - Xinyu Xu
- Beijing Advanced Innovation Center for Structural Biology, Tsinghua-Peking Joint Center for Life Sciences, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Daniel Hilger
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Philipp Aschauer
- Institute for Molecular Bioscience, University of Graz, Humboldtstrasse 50/3, 8010 Graz, Austria
| | - Johanna K S Tiemann
- Institute of Medical Physics and Biophysics, Charité Medical University Berlin, Berlin 10117, Germany; Institute of Medical Physics and Biophysics, Faculty of Medicine, University Leipzig, Leipzig 04107, Germany
| | - Yang Du
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Hongtao Liu
- Beijing Advanced Innovation Center for Structural Biology, Tsinghua-Peking Joint Center for Life Sciences, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Kunio Hirata
- Advanced Photon Technology Division, Research Infrastructure Group, SR Life Science Instrumentation Unit, RIKEN/SPring-8 Center, 1-1-1 Kouto Sayo-cho Sayo-gun, Hyogo 679-5148, Japan; Precursory Research for Embryonic Science and Technology (PRESTO), Japan Science and Technology Agency, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012, Japan
| | - Xiaoou Sun
- Beijing Advanced Innovation Center for Structural Biology, Tsinghua-Peking Joint Center for Life Sciences, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Ramon Guixà-González
- Institute of Medical Physics and Biophysics, Charité Medical University Berlin, Berlin 10117, Germany
| | - Jesper M Mathiesen
- Department of Drug Design and Pharmacology, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen 2100, Denmark
| | - Peter W Hildebrand
- Institute of Medical Physics and Biophysics, Charité Medical University Berlin, Berlin 10117, Germany; Institute of Medical Physics and Biophysics, Faculty of Medicine, University Leipzig, Leipzig 04107, Germany
| | - Brian K Kobilka
- Beijing Advanced Innovation Center for Structural Biology, Tsinghua-Peking Joint Center for Life Sciences, School of Medicine, Tsinghua University, Beijing 100084, China; Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, USA.
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33
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Dubbeldam D, Vreede J, Vlugt TJH, Calero S. Highlights of (bio-)chemical tools and visualization software for computational science. Curr Opin Chem Eng 2019. [DOI: 10.1016/j.coche.2019.02.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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34
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HTMoL: full-stack solution for remote access, visualization, and analysis of molecular dynamics trajectory data. J Comput Aided Mol Des 2018; 32:869-876. [DOI: 10.1007/s10822-018-0141-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Accepted: 08/01/2018] [Indexed: 10/28/2022]
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