CaverDock: A Molecular Docking-Based Tool to Analyse Ligand Transport through Protein Tunnels and Channels.

A new interesting article has been published in Bioinformatics. 2019 May 11. pii: btz386. doi: 10.1093/bioinformatics/btz386. and titled:

CaverDock: A Molecular Docking-Based Tool to Analyse Ligand Transport through Protein Tunnels and Channels.

Authors of this article are:

Vavra O, Filipovic J, Plhak J, Bednar D, Marques SM, Brezovsky J, Stourac J, Matyska L, Damborsky J.

A summary of the article is shown below:

MOTIVATION: Protein tunnels and channels are key transport pathways that allow ligands to pass between proteins’ external and internal environments. These functionally important structural features warrant detailed attention. It is difficult to study the ligand binding and unbinding process experimentally, while molecular dynamics simulations can be time-consuming and computationally demanding.RESULTS: CaverDock is a new software tool for analysing the ligand passage through the biomolecules. The method uses the optimised docking algorithm of AutoDock Vina for ligand placement docking and implements a parallel heuristic algorithm to search the space of possible trajectories. The duration of the simulations takes from minutes to a few hours. Here we describe the implementation of the method and demonstrate CaverDock’s usability by: i) comparison of the results with other available tools, ii) determination of the robustness with large ensembles of ligands and iii) the analysis and comparison of the ligand trajectories in engineered tunnels. Thorough testing confirms that CaverDock is applicable for the fast analysis of ligand binding and unbinding in fundamental enzymology and protein engineering.AVAILABILITY: User guide and binaries for Ubuntu are freely available for non-commercial use at https://loschmidt.chemi.muni.cz/caverdock/. The web implementation is available at https://loschmidt.chemi.muni.cz/caverweb/. The source code is available on request.SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.© The Author(s) (2019). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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