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      Electrostatic Switching Controls Channel Dynamics of the Sensor Protein VirB10 in A. tumefaciens Type IV Secretion System

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          Abstract

          Type IV secretion systems are large nanomachines assembled across the bacterial cell envelope for effector translocation and conjugation. VirB10 traverses the inner and outer membranes, sensing cellular signals for coordinating the conformational switch for pilus biogenesis and/or secretion. Mutations uncoupling secretion from pilus biogenesis were identified in Agrobacterium tumefaciens VirB10 including a gating defect mutation G272R that made VirB10 unresponsive to intracellular ATP, causing unregulated secretion of VirE2 in a contact-independent manner. Comparative long-timescale molecular dynamics of the wild type and G272R mutant of the A. tumefaciens VirB10 CTD tetradecamer reveals how the G272R mutation locks the oligomer in a rigid conformation by swapping the ionic interactions between the loops from the β-barrel close to the inner leaflet of the outer membrane. This electrostatic switching changes the allosteric communication pathway from the extracellular loop to the base of the barrel, suggesting that the local conformational dynamics in the loops can gate information across VirB10.

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          Algorithm 97: Shortest path

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            Clustal Omega, accurate alignment of very large numbers of sequences.

            Clustal Omega is a completely rewritten and revised version of the widely used Clustal series of programs for multiple sequence alignment. It can deal with very large numbers (many tens of thousands) of DNA/RNA or protein sequences due to its use of the mBED algorithm for calculating guide trees. This algorithm allows very large alignment problems to be tackled very quickly, even on personal computers. The accuracy of the program has been considerably improved over earlier Clustal programs, through the use of the HHalign method for aligning profile hidden Markov models. The program currently is used from the command line or can be run on line.
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              Scalable Algorithms for Molecular Dynamics Simulations on Commodity Clusters

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                Author and article information

                Journal
                ACS Omega
                ACS Omega
                ao
                acsodf
                ACS Omega
                American Chemical Society
                2470-1343
                04 February 2020
                25 February 2020
                : 5
                : 7
                : 3271-3281
                Affiliations
                []School of Biological and Chemical Sciences, Queen Mary University of London , Mile End Road, London E1 4NS, United Kingdom
                []Department of Pharmaceutical and Biological Chemistry, University College London School of Pharmacy , WC1N 1AX London, United Kingdom
                [§ ]Department of Biological Sciences, University of Idaho , C/O IRIC 333, 875 Perimeter MS 1122, Moscow, Idaho 83844-1122, United States
                []Centre for Biomarker Research, School of Applied Sciences, University of Huddersfield , HD1 3DH Huddersfield, United Kingdom
                []Department of Biochemistry & Cellular and Molecular Biology Department, University of Tennessee-Knoxville , Knoxville, Tennessee 37996, United States
                Author notes
                [* ]E-mail: v.darbari@ 123456qmul.ac.uk . Tel: +44 (0) 20 7882 6360 (V.C.D.).
                [* ]E-mail: shozeb.haider@ 123456ucl.ac.uk . Tel: +44 (0) 20 7753 5883 (S.H.).
                Article
                10.1021/acsomega.9b03313
                7045316
                32118142
                100d52fa-19af-4f7d-944f-8d87a65859b3
                Copyright © 2020 American Chemical Society

                This is an open access article published under an ACS AuthorChoice License, which permits copying and redistribution of the article or any adaptations for non-commercial purposes.

                History
                : 07 October 2019
                : 20 January 2020
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