Discovering new antiretroviral compounds in «Big Data» chemical space of the SAVI library

Savosina P.I.1 , Stolbov L.A.1, Druzhilovskiy D.S.1, Filimonov D.A.1, Nicklaus M.C.2, Poroikov V.V.1

1. Institute of Biomedical Chemistry, Moscow, Russia
2. Chemical Biology Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, Maryland, United States
Section: Bioinformatics and Chemoinformatics
DOI: 10.18097/PBMC20196502073      PubMed Id: 30950810
Year: 2019  Volume: 65  Issue: 2  Pages: 73-79
Despite significant advances in the application of highly active antiretroviral therapy, the development of new drugs for the treatment of HIV infection remains an important task because the existing drugs do not provide a complete cure, cause serious side effects and lead to the emergence of resistance. In 2015, a consortium of American and European scientists and specialists launched a project to create the SAVI (Synthetically Accessible Virtual Inventory) library. Its 2016 version of over 283 million structures of new easily synthesizable organic molecules, each annotated with a proposed synthetic route, were generated in silico for the purpose of searching for safer and more potent pharmacological substances. We have developed an algorithm for comparing large chemical databases (DB) based on the representation of structural formulas in SMILES codes, and evaluated the possibility of detecting new antiretroviral compounds in the SAVI database. After analyzing the intersection of SAVI with 97 million structures of the PubChem database, we found that only a small part of the SAVI (~0.015%) is represented in PubChem, which indicates a significant novelty of this virtual library. However, among those structures, 632 compounds tested for anti-HIV activity were detected, 41 of which had the desired activity. Thus, our studies for the first time demonstrated that SAVI is a promising source for the search for new anti-HIV compounds.
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Keywords: “Big Data”, SAVI, PubChem, new drug-like compounds, antiretroviral activity, PASS prediction

Savosina, P. I., Stolbov, L. A., Druzhilovskiy, D. S., Filimonov, D. A., Nicklaus, M. C., Poroikov, V. V. (2019). Discovering new antiretroviral compounds in «Big Data» chemical space of the SAVI library. Biomeditsinskaya Khimiya, 65(2), 73-79.
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