[Discovering new antiretroviral compounds in "Big Data" chemical space of the SAVI library]

Biomed Khim. 2019 Feb;65(2):73-79. doi: 10.18097/PBMC20196502073.
[Article in Russian]

Abstract

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.

Nesmotria na znachitel'nye uspekhi v primenenii vysokoaktivnoĭ antiretrovirusnoĭ terapii, razrabotka novykh preparatov dlia lecheniia VICh-infektsii ostaetsia aktual'noĭ, poskol'ku sushchestvuiushchie lekarstvennye sredstva ne obespechivaiut polnogo izlecheniia ot VICh-infektsii, vyzyvaiut ser'eznye pobochnye éffekty i privodiat k vozniknoveniiu rezistentnosti. V 2015 godu konsortsiumom amerikanskikh i evropeĭskikh uchenykh i spetsialistov nachat proekt po sozdaniiu biblioteki SAVI (Synthetically Accessible Virtual Inventory), v ramkakh kotorogo bylo sgenerirovano in silico svyshe 283 mln. struktur novykh legko-sinteziruemykh organicheskikh molekul s tsel'iu poiska sredi nikh bolee bezopasnykh i éffektivnykh farmakologicheskikh veshchestv. My razrabotali algoritm sravneniia bol'shikh khimicheskikh baz dannykh (BD) na osnove predstavleniia strukturnykh formul v formate SMILES i otsenili vozmozhnosti vyiavleniia v BD SAVI novykh antiretrovirusnykh soedineniĭ. Proanalizirovav peresechenie SAVI s 97 mln. struktur BD PubChem, my obnaruzhili, chto lish' malaia chast' SAVI (~0,015%) predstavlena v PubChem, chto svidetel'stvuet o znachitel'noĭ novizne étoĭ virtual'noĭ biblioteki. Odnako, sredi étikh struktur bylo vyiavleno 632 soedineniia, protestirovannykh na anti-VICh aktivnost', iz kotorykh 41 obladali iskomoĭ aktivnost'iu. Takim obrazom, nashi issledovaniia vpervye prodemonstrirovali, chto SAVI iavliaetsia perspektivnym istochnikom dlia poiska novykh anti-VICh soedineniĭ.

Keywords: PASS prediction; PubChem; SAVI; antiretroviral activity; new drug-like compounds.

MeSH terms

  • Algorithms
  • Anti-Retroviral Agents / pharmacology*
  • Big Data*
  • Databases, Chemical*
  • Drug Discovery*
  • HIV Infections
  • Humans

Substances

  • Anti-Retroviral Agents