期刊
SEMINARS IN CANCER BIOLOGY
卷 86, 期 -, 页码 1207-1217出版社
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.semcancer.2021.07.012
关键词
Databases; Microbial products; Virtual screening; Web tools; PredictSNP Onco
类别
资金
- Czech Ministry of Education [CZ.02.1.01/0.0/0.0/16_026/0008451, CZ.02.1.01/0.0/0.0/17_043/0009632, LM2018121, LM2015047, LM2018140]
- Grant Agency of the Czech Republic [20-15915Y]
- Technology Agency of the Czech Republic [TN01000013]
- European Union's Horizon 2020 research and Innovation programme [720776, 857560]
This article discusses the use of virtual screening tools to accelerate the development of anticancer drugs based on microbial products. It provides a detailed overview of the principles, workflow, and practical applications, showing the potential to expedite the discovery of novel cancer drugs.
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, such as 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 wild type isocitrate dehydrogenase 1 and 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.
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