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      Mol* Viewer: modern web app for 3D visualization and analysis of large biomolecular structures

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          Abstract

          Large biomolecular structures are being determined experimentally on a daily basis using established techniques such as crystallography and electron microscopy. In addition, emerging integrative or hybrid methods (I/HM) are producing structural models of huge macromolecular machines and assemblies, sometimes containing 100s of millions of non-hydrogen atoms. The performance requirements for visualization and analysis tools delivering these data are increasing rapidly. Significant progress in developing online, web-native three-dimensional (3D) visualization tools was previously accomplished with the introduction of the LiteMol suite and NGL Viewers. Thereafter, Mol* development was jointly initiated by PDBe and RCSB PDB to combine and build on the strengths of LiteMol (developed by PDBe) and NGL (developed by RCSB PDB). The web-native Mol* Viewer enables 3D visualization and streaming of macromolecular coordinate and experimental data, together with capabilities for displaying structure quality, functional, or biological context annotations. High-performance graphics and data management allows users to simultaneously visualise up to hundreds of (superimposed) protein structures, stream molecular dynamics simulation trajectories, render cell-level models, or display huge I/HM structures. It is the primary 3D structure viewer used by PDBe and RCSB PDB. It can be easily integrated into third-party services. Mol* Viewer is open source and freely available at https://molstar.org/.

          Graphical Abstract

          Graphical Abstract

          Overview of the large array of entities and systems that can be visualized and be manipulated with by the Mol* Viewer.

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          Most cited references38

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          The Protein Data Bank.

          The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans for the future development of the resource.
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            UniProt: the universal protein knowledgebase in 2021

            (2020)
            Abstract The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this article, we describe significant updates that we have made over the last two years to the resource. The number of sequences in UniProtKB has risen to approximately 190 million, despite continued work to reduce sequence redundancy at the proteome level. We have adopted new methods of assessing proteome completeness and quality. We continue to extract detailed annotations from the literature to add to reviewed entries and supplement these in unreviewed entries with annotations provided by automated systems such as the newly implemented Association-Rule-Based Annotator (ARBA). We have developed a credit-based publication submission interface to allow the community to contribute publications and annotations to UniProt entries. We describe how UniProtKB responded to the COVID-19 pandemic through expert curation of relevant entries that were rapidly made available to the research community through a dedicated portal. UniProt resources are available under a CC-BY (4.0) license via the web at https://www.uniprot.org/.
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              Pfam: The protein families database in 2021

              Abstract The Pfam database is a widely used resource for classifying protein sequences into families and domains. Since Pfam was last described in this journal, over 350 new families have been added in Pfam 33.1 and numerous improvements have been made to existing entries. To facilitate research on COVID-19, we have revised the Pfam entries that cover the SARS-CoV-2 proteome, and built new entries for regions that were not covered by Pfam. We have reintroduced Pfam-B which provides an automatically generated supplement to Pfam and contains 136 730 novel clusters of sequences that are not yet matched by a Pfam family. The new Pfam-B is based on a clustering by the MMseqs2 software. We have compared all of the regions in the RepeatsDB to those in Pfam and have started to use the results to build and refine Pfam repeat families. Pfam is freely available for browsing and download at http://pfam.xfam.org/.
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                Author and article information

                Contributors
                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                02 July 2021
                06 May 2021
                06 May 2021
                : 49
                : W1
                : W431-W437
                Affiliations
                CEITEC - Central European Institute of Technology, Masaryk University , Brno 625 00, Czech Republic
                National Centre for Biomolecular Research, Faculty of Science, Masaryk University , Brno 602 00, Czech Republic
                Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL–EBI), Wellcome Genome Campus , Hinxton CB10 1SD, UK
                Research Collaboratory for Structural Bioinformatics (RCSB), San Diego Supercomputer Center, University of California San Diego , San Diego, CA 92093-0743, USA
                Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL–EBI), Wellcome Genome Campus , Hinxton CB10 1SD, UK
                CEITEC - Central European Institute of Technology, Masaryk University , Brno 625 00, Czech Republic
                National Centre for Biomolecular Research, Faculty of Science, Masaryk University , Brno 602 00, Czech Republic
                Department of Physical Chemistry, Faculty of Science, Palacký University Olomouc , Olomouc 771 46, Czech Republic
                Department of Physical Chemistry, Faculty of Science, Palacký University Olomouc , Olomouc 771 46, Czech Republic
                Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL–EBI), Wellcome Genome Campus , Hinxton CB10 1SD, UK
                Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), Institute for Quantitative Biomedicine and Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey , Piscataway, NJ 08854-8076, USA
                Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey , New Brunswick, NJ 08903-2681, USA
                Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), San Diego Supercomputer Center and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego , San Diego, CA 92093-0654, USA
                CEITEC - Central European Institute of Technology, Masaryk University , Brno 625 00, Czech Republic
                National Centre for Biomolecular Research, Faculty of Science, Masaryk University , Brno 602 00, Czech Republic
                Research Collaboratory for Structural Bioinformatics (RCSB), San Diego Supercomputer Center, University of California San Diego , San Diego, CA 92093-0743, USA
                Author notes
                To whom correspondence should be addressed. Tel: +1 858 405 2667; Email: asr.moin@ 123456gmail.com
                Author information
                https://orcid.org/0000-0002-0682-3089
                https://orcid.org/0000-0003-3576-0387
                https://orcid.org/0000-0002-9043-7665
                https://orcid.org/0000-0002-3840-8760
                https://orcid.org/0000-0001-9472-2589
                https://orcid.org/0000-0003-3393-3010
                https://orcid.org/0000-0002-8439-5964
                https://orcid.org/0000-0002-2487-9713
                https://orcid.org/0000-0002-2780-4901
                https://orcid.org/0000-0002-0893-5551
                Article
                gkab314
                10.1093/nar/gkab314
                8262734
                33956157
                01ff97bb-0b9f-4d5d-85c4-d60c2f3cad09
                © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 26 April 2021
                : 12 April 2021
                : 23 February 2021
                Page count
                Pages: 7
                Funding
                Funded by: Ministry of Education, Youth and Sports of the Czech Republic;
                Award ID: LM2018131
                Funded by: European Regional Development Fund, DOI 10.13039/501100008530;
                Award ID: CZ.02.1.01/0.0/0.0/16_013/0001777
                Funded by: European Molecular Biology Laboratory, DOI 10.13039/100013060;
                Funded by: European Bioinformatics Institute, DOI 10.13039/100012116;
                Funded by: Wellcome Trust, DOI 10.13039/100010269;
                Award ID: 104948
                Funded by: National Science Foundation, DOI 10.13039/100000001;
                Award ID: DBI-1832184
                Funded by: National Institutes of Health, DOI 10.13039/100000002;
                Award ID: R01GM133198
                Funded by: U.S. Department of Energy, DOI 10.13039/100000015;
                Award ID: DE-SSC0019749
                Categories
                AcademicSubjects/SCI00010
                Web Server Issue

                Genetics
                Genetics

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