Getting to Know the Neighbours with GTM: The Case of Antiviral Compounds.
Alexey A OrlovEvgeny V KhvatovAlexander A KoruchekovAnastasia A NikitinaAnastasia D ZolotarevaAnastasia A EletskayaLiubov I KozlovskayaVladimir A PalyulinDragos HorvathDmitry I OsolodkinAlexandre VarnekPublished in: Molecular informatics (2019)
Recent outbreaks of dangerous viral infections, such as Ebola virus disease, Zika fever, etc., are forcing the search for new antiviral compounds. Preferably, such compounds should possess broad-spectrum antiviral activity, as the development of drugs for the treatment of dozens of viral infections lacking specific treatment would require significant resources. Antiviral activity data present in public resources are very sparse and further investigation of structure-activity relationships is necessary. One of the strategies could be the investigation of chemical space around known active compounds and assessment of activity against closely related viruses in order to fill in the antiviral activity matrix. Here we present an investigation of antiviral activity using universal maps built with generative topographic mapping (GTM) algorithm. The GTM-based maps were used to find commercially available compounds in close proximity to already known compounds with anti-flaviviral and anti-enteroviral activities. Selected compounds were then assessed in cell-based assays against tick-borne encephalitis virus (TBEV) and a panel of enteroviruses. This approach allowed us to identify 23 new compounds showing anti-TBEV activity with EC50 values in micromolar and submicromolar range.