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      CABS-dock standalone: a toolbox for flexible protein–peptide docking

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          Abstract

          Summary

          CABS-dock standalone is a multiplatform Python package for protein–peptide docking with backbone flexibility. The main feature of the CABS-dock method is its ability to simulate significant backbone flexibility of the entire protein–peptide system in a reasonable computational time. In the default mode, the package runs a simulation of fully flexible peptide searching for a binding site on the surface of a flexible protein receptor. The flexibility level of the molecules may be defined by the user. Furthermore, the CABS-dock standalone application provides users with full control over the docking simulation from the initial setup to the analysis of results. The standalone version is an upgrade of the original web server implementation—it introduces a number of customizable options, provides support for large-sized systems and offers a framework for deeper analysis of docking results.

          Availability and implementation

          CABS-dock standalone is distributed under the MIT licence, which is free for academic and non-profit users. It is implemented in Python and Fortran. The CABS-dock standalone source code, wiki with documentation and examples of use and installation instructions for Linux, macOS and Windows are available in the CABS-dock standalone repository at https://bitbucket.org/lcbio/cabsdock.

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          Most cited references12

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          Rosetta FlexPepDock web server—high resolution modeling of peptide–protein interactions

          Peptide–protein interactions are among the most prevalent and important interactions in the cell, but a large fraction of those interactions lack detailed structural characterization. The Rosetta FlexPepDock web server (http://flexpepdock.furmanlab.cs.huji.ac.il/) provides an interface to a high-resolution peptide docking (refinement) protocol for the modeling of peptide–protein complexes, implemented within the Rosetta framework. Given a protein receptor structure and an approximate, possibly inaccurate model of the peptide within the receptor binding site, the FlexPepDock server refines the peptide to high resolution, allowing full flexibility to the peptide backbone and to all side chains. This protocol was extensively tested and benchmarked on a wide array of non-redundant peptide–protein complexes, and was proven effective when applied to peptide starting conformations within 5.5 Å backbone root mean square deviation from the native conformation. FlexPepDock has been applied to several systems that are mediated and regulated by peptide–protein interactions. This easy to use and general web server interface allows non-expert users to accurately model their specific peptide–protein interaction of interest.
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            CABS-dock web server for the flexible docking of peptides to proteins without prior knowledge of the binding site

            Protein–peptide interactions play a key role in cell functions. Their structural characterization, though challenging, is important for the discovery of new drugs. The CABS-dock web server provides an interface for modeling protein–peptide interactions using a highly efficient protocol for the flexible docking of peptides to proteins. While other docking algorithms require pre-defined localization of the binding site, CABS-dock does not require such knowledge. Given a protein receptor structure and a peptide sequence (and starting from random conformations and positions of the peptide), CABS-dock performs simulation search for the binding site allowing for full flexibility of the peptide and small fluctuations of the receptor backbone. This protocol was extensively tested over the largest dataset of non-redundant protein–peptide interactions available to date (including bound and unbound docking cases). For over 80% of bound and unbound dataset cases, we obtained models with high or medium accuracy (sufficient for practical applications). Additionally, as optional features, CABS-dock can exclude user-selected binding modes from docking search or to increase the level of flexibility for chosen receptor fragments. CABS-dock is freely available as a web server at http://biocomp.chem.uw.edu.pl/CABSdock.
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              Protein–peptide docking: opportunities and challenges

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                Author and article information

                Contributors
                Role: Associate Editor
                Journal
                Bioinformatics
                Bioinformatics
                bioinformatics
                Bioinformatics
                Oxford University Press
                1367-4803
                1367-4811
                15 October 2019
                13 March 2019
                13 March 2019
                : 35
                : 20
                : 4170-4172
                Affiliations
                [1 ] Biological and Chemical Research Centre , Faculty of Chemistry, University of Warsaw, Warsaw, Poland
                [2 ]Faculty of Physics, University of Warsaw , Warsaw, Poland
                [3 ] College of Inter-Faculty Individual Studies in Mathematics and Natural Sciences, University of Warsaw , Warsaw, Poland
                Author notes
                To whom correspondence should be addressed. sekmi@ 123456chem.uw.edu.pl
                Author information
                http://orcid.org/0000-0003-1832-4364
                http://orcid.org/0000-0001-7623-0935
                Article
                btz185
                10.1093/bioinformatics/btz185
                6792116
                30865258
                03af0038-2e69-4057-923a-05e5295526bf
                © The Author(s) 2019. Published by Oxford University Press.

                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
                : 22 November 2018
                : 30 January 2019
                : 12 March 2019
                Page count
                Pages: 3
                Funding
                Funded by: National Science Centre 10.13039/501100004281
                Award ID: MAESTRO2014/14/A/ST6/00088
                Categories
                Applications Notes
                Structural Bioinformatics

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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