Getting to Know the Neighbours with GTM: The Case of Antiviral Compounds

Abstract

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.

Examination of molecular space and feasible structures of bioactive components of humic substances by FTICR MS data mining in ChEMBL database

“…TBEV is the leading cause of arbovirus infections in Europe and Russia 3 . Several small molecule classes were suggested as the starting compounds for the development of TBEV reproduction inhibitors 4–13 . However, none of them were developed as drug candidates and there is still a need for new anti-TBEV compounds.…”

A Chemographic Audit of Anti-Coronavirus Structure-Activity Information from Public Databases (ChEMBL)

“…(their common denominator is the fragment-like size). This comparative mapping can serve as a departure point to "repurpose" [7,9] some of the members of the large antiviral sets which share the…”

A Chemographic Audit of anti‐Coronavirus Structure‐activity Information from Public Databases (ChEMBL)

“…Large efforts have been made recently in order to curate and analyze antiviral chemical space, [7][8][9] as well as to validate the applicability of machine learning methods for the discovery of new antiviral compounds. [10] The data on activity of closely related viruses were proven to be informative enough for the guided discovery of hit compounds against a particular virus.…”

“…[10] The data on activity of closely related viruses were proven to be informative enough for the guided discovery of hit compounds against a particular virus. [7] For example, the data on activity against flaviviruses extracted from ViralChEMBL [8] projected onto Universal Maps (UMs) of chemical space built by generative topographic mapping (GTM) method were successfully used to discover new compounds with activity against tick-borne encephalitis virus, although only few data points were available for this virus. [7] Chemography [11] provides a computer-generated, human-readable framework ("map") in which chemical compounds can be located -ideally, by positioning similar molecules close to each other.…”

“…[7] For example, the data on activity against flaviviruses extracted from ViralChEMBL [8] projected onto Universal Maps (UMs) of chemical space built by generative topographic mapping (GTM) method were successfully used to discover new compounds with activity against tick-borne encephalitis virus, although only few data points were available for this virus. [7] Chemography [11] provides a computer-generated, human-readable framework ("map") in which chemical compounds can be located -ideally, by positioning similar molecules close to each other. Molecules, typically represented by high-dimensional descriptor vectors, are pro-jected on such maps by means of some dimensionality reduction techniques.…”