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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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2
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Ng CL, Lim TS, Choong YS. Application of Computational Techniques in Antibody Fc-Fused Molecule Design for Therapeutics. Mol Biotechnol 2024; 66:568-581. [PMID: 37742298 DOI: 10.1007/s12033-023-00885-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 08/23/2023] [Indexed: 09/26/2023]
Abstract
Since the advent of hybridoma technology in the year 1975, it took a decade to witness the first approved monoclonal antibody Orthoclone OKT39 (muromonab-CD3) in the year 1986. Since then, continuous strides have been made to engineer antibodies for specific desired effects. The engineering efforts were not confined to only the variable domains of the antibody but also included the fragment crystallizable (Fc) region that influences the immune response and serum half-life. Engineering of the Fc fragment would have a profound effect on the therapeutic dose, antibody-dependent cell-mediated cytotoxicity as well as antibody-dependent cellular phagocytosis. The integration of computational techniques into antibody engineering designs has allowed for the generation of testable hypotheses and guided the rational antibody design framework prior to further experimental evaluations. In this article, we discuss the recent works in the Fc-fused molecule design that involves computational techniques. We also summarize the usefulness of in silico techniques to aid Fc-fused molecule design and analysis for the therapeutics application.
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Affiliation(s)
- Chong Lee Ng
- Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia, Minden, Penang, Malaysia
| | - Theam Soon Lim
- Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia, Minden, Penang, Malaysia
| | - Yee Siew Choong
- Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia, Minden, Penang, Malaysia.
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3
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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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4
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Del C Reyes-Vázquez N, de la Rosa LA, Morales-Landa JL, García-Fajardo JA, García-Cruz MÁ. Phytochemical content and potential health applications of pecan [Carya illinoinensis (Wangenh) K. Koch] nutshell. Curr Top Med Chem 2022; 22:150-167. [PMID: 34986772 DOI: 10.2174/1568026622666220105104355] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Revised: 11/11/2021] [Accepted: 11/22/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND The pecan nutshell contains phytochemicals with various biological activities that are potentially useful in the prevention or treatment of diseases such as cancer, diabetes, and metabolic imbalances associated with heart diseases. OBJECTIVE To update this topic by means of a literature review and include those that contribute to the knowledge of the chemical composition and biological activities of pecan nutshell, particularly of those related to the therapeutic potential against some chronic degenerative diseases associated with oxidative stress. METHOD Exhaustive and detailed review of the existing literature using electronic databases. CONCLUSION The pecan nutshell is a promising natural product with pharmaceutical uses in various diseases. However, additional research related to the assessment of efficient extraction methods and characterization, particularly the evaluation of the mechanisms of action in new in vivo models, is necessary to confirm these findings and development of new drugs with therapeutic use.
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Affiliation(s)
- Nohemí Del C Reyes-Vázquez
- Centro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco A. C. Subsede Noreste. 66629 Apodaca-66629, Nuevo León, México
| | - Laura A de la Rosa
- Departamento de Ciencias Químico Biológicas. Instituto de Ciencias Biomédicas. Universidad Autónoma de Ciudad Juárez. Ciudad Juárez-32310, Chihuahua, México
| | - Juan Luis Morales-Landa
- Centro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco A. C. Subsede Noreste. 66629 Apodaca-66629, Nuevo León, México
- Centro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco A. C. Subsede Noreste. 66629 Apodaca-66629, Nuevo León, México
| | - Jorge Alberto García-Fajardo
- Centro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco A. C. Subsede Noreste. 66629 Apodaca-66629, Nuevo León, México
| | - Miguel Ángel García-Cruz
- Facultad de Ciencias Biológicas, Universidad Autónoma de Nuevo León, San Nicolás de los Garza-66450, Nuevo León, México
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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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6
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Visualizing protein structures - tools and trends. Biochem Soc Trans 2021; 48:499-506. [PMID: 32196545 DOI: 10.1042/bst20190621] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2020] [Revised: 03/01/2020] [Accepted: 03/04/2020] [Indexed: 02/06/2023]
Abstract
Molecular visualization is fundamental in the current scientific literature, textbooks and dissemination materials. It provides an essential support for presenting results, reasoning on and formulating hypotheses related to molecular structure. Tools for visual exploration of structural data have become easily accessible on a broad variety of platforms thanks to advanced software tools that render a great service to the scientific community. These tools are often developed across disciplines bridging computer science, biology and chemistry. This mini-review was written as a short and compact overview for scientists who need to visualize protein structures and want to make an informed decision which tool they should use. Here, we first describe a few 'Swiss Army knives' geared towards protein visualization for everyday use with an existing large user base, then focus on more specialized tools for peculiar needs that are not yet as broadly known. Our selection is by no means exhaustive, but reflects a diverse snapshot of scenarios that we consider informative for the reader. We end with an account of future trends and perspectives.
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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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8
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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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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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10
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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: 76] [Impact Index Per Article: 19.0] [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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11
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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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12
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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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13
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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: 16] [Impact Index Per Article: 3.2] [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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14
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Ferina J, Daggett V. Visualizing Protein Folding and Unfolding. J Mol Biol 2019; 431:1540-1564. [PMID: 30840846 DOI: 10.1016/j.jmb.2019.02.026] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2018] [Revised: 02/14/2019] [Accepted: 02/18/2019] [Indexed: 12/27/2022]
Abstract
Protein folding/unfolding is a complicated process that defies high-resolution characterization by experimental methods. As an alternative, atomistic molecular dynamics simulations are now routinely employed to elucidate and magnify the accompanying conformational changes and the role of solvent in the folding process. However, the level of detail necessary to map the process at high spatial-temporal resolution provides an overwhelming amount of data. As more and better tools are developed for analysis of these large data sets and validation of the simulations, one is still left with the problem of visualizing the results in ways that provide insight into the folding/unfolding process. While viewing and interrogating static crystal structures has become commonplace, more and different approaches are required for dynamic, interconverting, unfolding, and refolding proteins. Here we review a variety of approaches, ranging from straightforward to complex and unintuitive for multiscale analysis and visualization of protein folding and unfolding.
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Affiliation(s)
- Jennifer Ferina
- Department of Bioengineering, Box 355013, University of Washington, Seattle, WA 98195-5013, USA
| | - Valerie Daggett
- Department of Bioengineering, Box 355013, University of Washington, Seattle, WA 98195-5013, USA.
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15
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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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