Literature DB >> 31077297

CaverDock: a molecular docking-based tool to analyse ligand transport through protein tunnels and channels.

Ondrej Vavra1,2, Jiri Filipovic3, Jan Plhak3, David Bednar1,2, Sergio M Marques1,2, Jan Brezovsky1, Jan Stourac1,2, Ludek Matyska3, Jiri Damborsky1,2.   

Abstract

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 processes 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 optimized 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 AND IMPLEMENTATION: 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 upon 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 e-mail: journals.permissions@oup.com.

Mesh:

Substances:

Year:  2019        PMID: 31077297     DOI: 10.1093/bioinformatics/btz386

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  7 in total

1.  Simulation of Ligand Transport in Receptors Using CaverDock.

Authors:  Jana Hozzová; Ondřej Vávra; David Bednář; Jiří Filipovič
Journal:  Methods Mol Biol       Date:  2021

2.  Evaluation of lipase access tunnels and analysis of substance transport in comparison with experimental data.

Authors:  Jéssica Jéssi C de Melo; Jesica Ribeiro Gonçalves; Luma M de S Brandão; Ranyere L Souza; Matheus M Pereira; Álvaro S Lima; Cleide M F Soares
Journal:  Bioprocess Biosyst Eng       Date:  2022-05-18       Impact factor: 3.210

3.  Screening of world approved drugs against highly dynamical spike glycoprotein of SARS-CoV-2 using CaverDock and machine learning.

Authors:  Gaspar P Pinto; Ondrej Vavra; Sergio M Marques; Jiri Filipovic; David Bednar; Jiri Damborsky
Journal:  Comput Struct Biotechnol J       Date:  2021-05-26       Impact factor: 7.271

4.  Fast Screening of Inhibitor Binding/Unbinding Using Novel Software Tool CaverDock.

Authors:  Gaspar P Pinto; Ondrej Vavra; Jiri Filipovic; Jan Stourac; David Bednar; Jiri Damborsky
Journal:  Front Chem       Date:  2019-10-29       Impact factor: 5.221

5.  In Silico Evaluation of Enzymatic Tunnels in the Biotransformation of α-Tocopherol Esters.

Authors:  Tamara Stela Mendonça Azevedo; Lavínia Kelly Barros Silva; Álvaro Silva Lima; Matheus Mendonça Pereira; Elton Franceschi; Cleide Mara Faria Soares
Journal:  Front Bioeng Biotechnol       Date:  2022-01-21

Review 6.  Dynamics, a Powerful Component of Current and Future in Silico Approaches for Protein Design and Engineering.

Authors:  Bartłomiej Surpeta; Carlos Eduardo Sequeiros-Borja; Jan Brezovsky
Journal:  Int J Mol Sci       Date:  2020-04-14       Impact factor: 5.923

7.  Dual Substrate Specificity of the Rutinosidase from Aspergillus niger and the Role of Its Substrate Tunnel.

Authors:  Katerina Brodsky; Michal Kutý; Helena Pelantová; Josef Cvačka; Martin Rebroš; Michael Kotik; Ivana Kutá Smatanová; Vladimír Křen; Pavla Bojarová
Journal:  Int J Mol Sci       Date:  2020-08-07       Impact factor: 5.923

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.