Fully automated virtual screening pipeline of FDA-approved drugs using Caver Web

被引:1
|
作者
Musil, Milos [1 ,2 ,3 ,4 ]
Jezik, Andrej [1 ,2 ,3 ,4 ]
Jankujova, Marie [1 ,2 ,3 ]
Stourac, Jan [1 ,2 ,3 ]
Galgonek, Jakub [5 ]
Eyrilmez, Saltuk Mustafa [1 ,2 ]
Vondrasek, Jiri [5 ]
Damborsky, Jiri [1 ,2 ,3 ]
Bednar, David [1 ,2 ,3 ]
机构
[1] Masaryk Univ, Dept Expt Biol, Loschmidt Labs, Brno, Czech Republic
[2] Masaryk Univ, ECETOX, Brno, Czech Republic
[3] St Annes Univ Hosp Brno, Int Clin Res Ctr, Brno, Czech Republic
[4] Brno Univ Technol, Fac Informat Technol, Brno, Czech Republic
[5] Inst Organ Chem & Biochem CAS, Prague, Czech Republic
关键词
Caver; CaverDock; FDA -approved drug; Channel; Tunnel; Virtual screening; Web; ABIRATERONE; INHIBITION; DISCOVERY; MUTATIONS; MECHANISM; DATABASE; SERVER; DRAFT;
D O I
10.1016/j.csbj.2022.11.031
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Protein tunnels are essential in transporting small molecules into the active sites of enzymes. Tunnels' geometrical and physico-chemical properties influence the transport process. The tunnels are attractive hot spots for protein engineering and drug development. However, studying the ligand binding and unbinding using experimental techniques is challenging, while in silico methods come with their limita-tions, especially in the case of resource-demanding virtual screening pipelines. Caver Web 1.2 is a new version of the web server combining the capabilities for the detection of protein tunnels with the calcu-lation of the ligand trajectories. The new version of the Caver Web server was expanded with the ability to fetch novel ligands from the Integrated Database of Small Molecules and with the fully automated vir-tual screening pipeline allowing for the fast evaluation of the predefined set of over 4,300 currently approved drugs. The virtual screening pipeline is accompanied by a comprehensive user interface, mak-ing it a viable service for the broader spectrum of companies and the academic user community. The web server is freely available for academic use at https://loschmidt.chemi.muni.cz/caverweb.(c) 2022 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY license (http://creativecommons. org/licenses/by/4.0/).
引用
收藏
页码:6512 / 6518
页数:7
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