Machine learning techniques applied to the drug design and discovery of new antivirals: a brief look over the past decade.
Expert Opin Drug Discov
; 16(9): 961-975, 2021 09.
Article
in English
| MEDLINE | ID: covidwho-1219967
ABSTRACT
Introduction:
Drug design and discovery of new antivirals will always be extremely important in medicinal chemistry, taking into account known and new viral diseases that are yet to come. Although machine learning (ML) have shown to improve predictions on the biological potential of chemicals and accelerate the discovery of drugs over the past decade, new methods and their combinations have improved their performance and established promising perspectives regarding ML in the search for new antivirals.Areas covered The authors consider some interesting areas that deal with different ML techniques applied to antivirals. Recent innovative studies on ML and antivirals were selected and analyzed in detail. Also, the authors provide a brief look at the past to the present to detect advances and bottlenecks in the area.Expert opinion From classical ML techniques, it was possible to boost the searches for antivirals. However, from the emergence of new algorithms and the improvement in old approaches, promising results will be achieved every day, as we have observed in the case of SARS-CoV-2. Recent experience has shown that it is possible to use ML to discover new antiviral candidates from virtual screening and drug repurposing.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Antiviral Agents
/
Drug Design
/
Machine Learning
Type of study:
Diagnostic study
/
Prognostic study
Limits:
Animals
/
Humans
Language:
English
Journal:
Expert Opin Drug Discov
Year:
2021
Document Type:
Article
Affiliation country:
17460441.2021.1918098
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