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      Integrated Approach Including Docking, MD Simulations, and Network Analysis Highlights the Action Mechanism of the Cardiac hERG Activator RPR260243

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          Abstract

          hERG is a voltage-gated potassium channel involved in the heart contraction whose defections are associated with the cardiac arrhythmia Long QT Syndrome type 2. The activator RPR260243 (RPR) represents a possible candidate to pharmacologically treat LQTS2 because it enhances the opening of the channel. However, the molecular detail of its action mechanism remains quite elusive. Here, we address the problem using a combination of docking, molecular dynamics simulations, and network analysis. We show that the drug preferably binds at the interface between the voltage sensor and the pore, enhancing the canonical activation path and determining a whole-structure rearrangement of the channel that slightly impairs inactivation.

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          AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading.

          AutoDock Vina, a new program for molecular docking and virtual screening, is presented. AutoDock Vina achieves an approximately two orders of magnitude speed-up compared with the molecular docking software previously developed in our lab (AutoDock 4), while also significantly improving the accuracy of the binding mode predictions, judging by our tests on the training set used in AutoDock 4 development. Further speed-up is achieved from parallelism, by using multithreading on multicore machines. AutoDock Vina automatically calculates the grid maps and clusters the results in a way transparent to the user. Copyright 2009 Wiley Periodicals, Inc.
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            AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility.

            We describe the testing and release of AutoDock4 and the accompanying graphical user interface AutoDockTools. AutoDock4 incorporates limited flexibility in the receptor. Several tests are reported here, including a redocking experiment with 188 diverse ligand-protein complexes and a cross-docking experiment using flexible sidechains in 87 HIV protease complexes. We also report its utility in analysis of covalently bound ligands, using both a grid-based docking method and a modification of the flexible sidechain technique. (c) 2009 Wiley Periodicals, Inc.
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              Particle mesh Ewald: An N⋅log(N) method for Ewald sums in large systems

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                Author and article information

                Journal
                J Chem Inf Model
                J Chem Inf Model
                ci
                jcisd8
                Journal of Chemical Information and Modeling
                American Chemical Society
                1549-9596
                1549-960X
                28 July 2023
                14 August 2023
                : 63
                : 15
                : 4888-4899
                Affiliations
                []Dipartimento di Ingegneria Meccanica e Aerospaziale, Sapienza Università di Roma , via Eudossiana 18, 00184 Rome, Italy
                []Department of Pharmacy and Biotechnology, Alma Mater Studiorum−Università di Bologna , via Belmeloro 6, 40126 Bologna, Italy
                Author notes
                Author information
                https://orcid.org/0000-0002-2132-0658
                https://orcid.org/0000-0003-2735-6982
                https://orcid.org/0000-0002-3757-7802
                Article
                10.1021/acs.jcim.3c00596
                10428221
                37504578
                ee8d96dc-ef22-4b2b-b4de-dc09fb4528b2
                © 2023 The Authors. Published by American Chemical Society

                Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 19 April 2023
                Funding
                Funded by: H2020 European Research Council, doi 10.13039/100010663;
                Award ID: 803213
                Categories
                Article
                Custom metadata
                ci3c00596
                ci3c00596

                Computational chemistry & Modeling
                Computational chemistry & Modeling

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