15
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      UCSF ChimeraX: Tools for structure building and analysis

      methods-article

      Read this article at

          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Advances in computational tools for atomic model building are leading to accurate models of large molecular assemblies seen in electron microscopy, often at challenging resolutions of 3–4 Å. We describe new methods in the UCSF ChimeraX molecular modeling package that take advantage of machine‐learning structure predictions, provide likelihood‐based fitting in maps, and compute per‐residue scores to identify modeling errors. Additional model‐building tools assist analysis of mutations, post‐translational modifications, and interactions with ligands. We present the latest ChimeraX model‐building capabilities, including several community‐developed extensions. ChimeraX is available free of charge for noncommercial use at https://www.rbvi.ucsf.edu/chimerax.

          Related collections

          Most cited references41

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Highly accurate protein structure prediction with AlphaFold

          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.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Basic local alignment search tool.

            A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              UCSF ChimeraX : Structure visualization for researchers, educators, and developers

              UCSF ChimeraX is the next-generation interactive visualization program from the Resource for Biocomputing, Visualization, and Informatics (RBVI), following UCSF Chimera. ChimeraX brings (a) significant performance and graphics enhancements; (b) new implementations of Chimera's most highly used tools, many with further improvements; (c) several entirely new analysis features; (d) support for new areas such as virtual reality, light-sheet microscopy, and medical imaging data; (e) major ease-of-use advances, including toolbars with icons to perform actions with a single click, basic "undo" capabilities, and more logical and consistent commands; and (f) an app store for researchers to contribute new tools. ChimeraX includes full user documentation and is free for noncommercial use, with downloads available for Windows, Linux, and macOS from https://www.rbvi.ucsf.edu/chimerax.
                Bookmark

                Author and article information

                Contributors
                tef@cgl.ucsf.edu
                Journal
                Protein Sci
                Protein Sci
                10.1002/(ISSN)1469-896X
                PRO
                Protein Science : A Publication of the Protein Society
                John Wiley & Sons, Inc. (Hoboken, USA )
                0961-8368
                1469-896X
                November 2023
                01 November 2023
                01 November 2023
                : 32
                : 11 ( doiID: 10.1002/pro.v32.11 )
                : e4792
                Affiliations
                [ 1 ] Department of Pharmaceutical Chemistry University of California San Francisco San Francisco California USA
                Author notes
                [*] [* ] Correspondence

                Thomas E. Ferrin, Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA 94143 USA.

                Email: tef@ 123456cgl.ucsf.edu

                Author information
                https://orcid.org/0000-0001-6227-0637
                Article
                PRO4792
                10.1002/pro.4792
                10588335
                37774136
                ac566844-c044-4f7e-8f15-8698466342f2
                © 2023 The Authors. Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 20 September 2023
                : 07 August 2023
                : 23 September 2023
                Page count
                Figures: 9, Tables: 1, Pages: 13, Words: 7234
                Funding
                Funded by: National Institutes of Health , doi 10.13039/100000002;
                Award ID: R24 GM141254
                Award ID: R01 GM129325
                Funded by: Chan Zuckerberg Initiative , doi 10.13039/100014989;
                Award ID: EOSS4‐0000000439
                Categories
                Tools for Protein Science
                Tools for Protein Science
                Custom metadata
                2.0
                November 2023
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.3.4 mode:remove_FC converted:20.10.2023

                Biochemistry
                alphafold,atomic model building,chimerax,cryo‐electron microscopy,protein structure prediction,refinement

                Comments

                Comment on this article