Hybrid In Silico Approach Reveals Novel Inhibitors of Multiple SARS-CoV-2 Variants.
ACS Pharmacol Transl Sci
; 4(5): 1675-1688, 2021 Oct 08.
Article
in English
| MEDLINE | ID: covidwho-1450269
Preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
ABSTRACT
The National Center for Advancing Translational Sciences (NCATS) has been actively generating SARS-CoV-2 high-throughput screening data and disseminates it through the OpenData Portal (https//opendata.ncats.nih.gov/covid19/). Here, we provide a hybrid approach that utilizes NCATS screening data from the SARS-CoV-2 cytopathic effect reduction assay to build predictive models, using both machine learning and pharmacophore-based modeling. Optimized models were used to perform two iterative rounds of virtual screening to predict small molecules active against SARS-CoV-2. Experimental testing with live virus provided 100 (â¼16% of predicted hits) active compounds (efficacy > 30%, IC50 ≤ 15 µM). Systematic clustering analysis of active compounds revealed three promising chemotypes which have not been previously identified as inhibitors of SARS-CoV-2 infection. Further investigation resulted in the identification of allosteric binders to host receptor angiotensin-converting enzyme 2; these compounds were then shown to inhibit the entry of pseudoparticles bearing spike protein of wild-type SARS-CoV-2, as well as South African B.1.351 and UK B.1.1.7 variants.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Type of study:
Prognostic study
/
Systematic review/Meta Analysis
Topics:
Variants
Language:
English
Journal:
ACS Pharmacol Transl Sci
Year:
2021
Document Type:
Article
Affiliation country:
Acsptsci.1c00176
Similar
MEDLINE
...
LILACS
LIS