Fully automated virtual screening pipeline of FDA-approved drugs using Caver Web
| Authors | |
|---|---|
| Year of publication | 2022 |
| Type | Article in Periodical |
| Magazine / Source | Computational and Structural Biotechnology Journal |
| MU Faculty or unit | |
| Citation | |
| web | https://www.sciencedirect.com/science/article/pii/S2001037022005244?via%3Dihub |
| Doi | http://dx.doi.org/10.1016/j.csbj.2022.11.031 |
| Keywords | Caver; CaverDock; FDA-approved drug; Channel; Tunnel; Virtual screening; Web |
| Attached files | |
| Description | 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 limitations, 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 calculation 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 virtual 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, making 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. |
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