Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

Virtual Screening of Potential Anticancer Drugs based on Microbial Products

Version 1 : Received: 23 February 2021 / Approved: 23 February 2021 / Online: 23 February 2021 (15:59:19 CET)

How to cite: Pinto, G.; Hendrikse, N.; Stourac, J.; Damborsky, J.; Bednar, D. Virtual Screening of Potential Anticancer Drugs based on Microbial Products. Preprints 2021, 2021020529 (doi: 10.20944/preprints202102.0529.v1). Pinto, G.; Hendrikse, N.; Stourac, J.; Damborsky, J.; Bednar, D. Virtual Screening of Potential Anticancer Drugs based on Microbial Products. Preprints 2021, 2021020529 (doi: 10.20944/preprints202102.0529.v1).

Abstract

The development of microbial products for cancer treatment has been in the spotlight in recent years. In order to accelerate the lengthy and expensive drug development process, in silico screening tools are systematically employed, especially during the initial discovery phase. Moreover, considering the steadily increasing number of molecules approved by authorities for commercial use, there is a demand for faster methods to repurpose such drugs. Here we present a review on virtual screening web tools, publicly available databases of molecular targets and libraries of ligands, with the aim to facilitate the discovery of potential anticancer drugs based on microbial products. We provide an entry-level step-by-step description of the workflow for virtual screening of microbial metabolites with known protein targets, as well as two practical examples using freely available web tools. The first case presents a virtual screening study of drugs developed from microbial products using Caver Web, a web tool that performs docking along a tunnel. The second case comprises a comparative analysis between a healthy isocitrate dehydrogenase 1, a mutant that results in cancer, using the recently developed web tool PredictSNPOnco. In summary, this review provides the basic and essential background information necessary for virtual screening experiments, which may accelerate the discovery of novel anticancer drugs.

Supplementary and Associated Material

Keywords

Caver Web; databases; libraries; microbial products; PredictSNPonco; molecular docking; molecular targets; mutations; treatment; virtual screening; web tools

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