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      PDBsum extras: SARS‐CoV‐2 and AlphaFold models

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          Abstract

          The PDBsum web server provides structural analyses of the entries in the Protein Data Bank (PDB). Two recent additions are described here. The first is the detailed analysis of the SARS‐CoV‐2 virus protein structures in the PDB. These include the variants of concern, which are shown both on the sequences and 3D structures of the proteins. The second addition is the inclusion of the available AlphaFold models for human proteins. The pages allow a search of the protein against existing structures in the PDB via the Sequence Annotated by Structure (SAS) server, so one can easily compare the predicted model against experimentally determined structures. The server is freely accessible to all at http://www.ebi.ac.uk/pdbsum.

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          Highly accurate protein structure prediction with AlphaFold

          John Jumper, Richard Evans, Alexander Pritzel … (2021)
          Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort 1 – 4 , the structures of around 100,000 unique proteins have been determined 5 , but this represents a small fraction of the billions of known protein sequences 6 , 7 . Structural coverage is bottlenecked by the months to years of painstaking effort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the three-dimensional structure that a protein will adopt based solely on its amino acid sequence—the structure prediction component of the ‘protein folding problem’ 8 —has been an important open research problem for more than 50 years 9 . Despite recent progress 10 – 14 , existing methods fall far short of atomic accuracy, especially when no homologous structure is available. Here we provide the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14) 15 , demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other methods. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm. AlphaFold predicts protein structures with an accuracy competitive with experimental structures in the majority of cases using a novel deep learning architecture.
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            Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

            S Altschul (1997)
            The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSI-BLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.
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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/.
              Article 0 comments Cited 2465 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Roman A. Laskowski:
                ORCID: https://orcid.org/0000-0001-5528-0087
                roman@ebi.ac.uk
                Journal
                Journal ID (nlm-ta): Protein Sci
                Journal ID (iso-abbrev): Protein Sci
                Journal ID (doi): 10.1002/(ISSN)1469-896X
                Journal ID (publisher-id): PRO
                Title: Protein Science : A Publication of the Protein Society
                Publisher: John Wiley & Sons, Inc. (Hoboken, USA )
                ISSN (Print): 0961-8368
                ISSN (Electronic): 1469-896X
                Publication date (Electronic): 24 November 2021
                Publication date PMC-release: 24 November 2021
                Electronic Location Identifier: 10.1002/pro.4238
                Affiliations
                [ 1 ] European Molecular Biology Laboratory European Bioinformatics Institute (EMBL‐EBI), Wellcome Trust Genome Campus Cambridge
                Author notes
                [*] [* ] Correspondence

                Roman A. Laskowski, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL‐EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.

                Email: roman@ 123456ebi.ac.uk

                Author information
                https://orcid.org/0000-0001-5528-0087
                https://orcid.org/0000-0003-0824-4096
                Article
                Publisher ID: PRO4238
                DOI: 10.1002/pro.4238
                PMC ID: 8662102
                PubMed ID: 34779073
                SO-VID: 653bc7bc-0462-4d2c-b354-e94be1ced048
                Copyright © © 2021 The Authors. Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society.
                License:

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                Date revision received : 07 November 2021
                Date received : 07 October 2021
                Date accepted : 09 November 2021
                Page count
                Figures: 4, Tables: 0, Pages: 7, Words: 3701
                Categories
                Subject: Tools for Protein Science
                Subject: Tools for Protein Science
                Custom metadata
                source-schema-version-number 2.0
                edited-state corrected-proof
                details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.9 mode:remove_FC converted:10.12.2021

                ScienceOpen disciplines: Biochemistry
                Keywords: 3d protein structure,alphafold,pdb,pdbsum,protein database,protein structure analysis,sars‐cov‐2,schematic diagrams
                Data availability:
                ScienceOpen disciplines: Biochemistry
                Keywords: 3d protein structure, alphafold, pdb, pdbsum, protein database, protein structure analysis, sars‐cov‐2, schematic diagrams

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