Biological and Medicinal Chemistry

A machine learning platform to estimate anti-SARS-CoV-2 activities

Abstract

Strategies for drug discovery and repositioning are an urgent need with respect to COVID-19. Here we present "REDIAL-2020", a suite of computational models for estimating small molecule activities in a range of SARS-CoV-2 related assays. Models were trained using publicly available, high throughput screening data and by employing different descriptor types and various machine learning strategies. Here we describe the development and the usage of eleven models spanning across the areas of viral entry, viral replication, live virus infectivity, in vitro infectivity and human cell toxicity. REDIAL-2020 is available as a web application through the DrugCentral web portal (http://drugcentral.org/Redial). In addition, the web-app provides similarity search results that display the most similar molecules to the query, as well as associated experimental data. REDIAL-2020 can serve as a rapid online tool for identifying active molecules for COVID-19 treatment.


Version notes

This is latest version at the time of publication acceptance in NMI.

Content

Thumbnail image of REDIAL_manuscriptV12.docx.pdf

Supplementary material

Thumbnail image of REDIAL-SI_figures11B.docx.pdf
REDIAL-SI figures11B.docx
Thumbnail image of REDIAL-SI_tablesV10.xlsx
REDIAL-SI tablesV10

Supplementary weblinks