Machine learning techniques applied to the drug design and discovery of new antivirals: a brief look over the past decade

Mateus Sá Magalhães Serafim; Valtair Severino dos Santos; Jadson Castro Gertrudes; Vinícius Gonçalves Maltarollo; Káthia M. Honório

doi:10.1080/17460441.2021.1918098

May 7, 2021Expert Opinion on Drug Discovery

Machine learning techniques applied to the drug design and discovery of new antivirals: a brief look over the past decade

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Key Points

This review examines the application of machine learning in the design and discovery of new antivirals over the past decade.
Reviewed classical and recent machine learning techniques for antiviral discovery.
Analyzed the role of new algorithms and improvements in existing approaches.
Discussed case studies, including SARS-CoV-2, to illustrate advancements.
Machine learning significantly enhances the identification of antiviral candidates.
Promising results from virtual screening and drug repurposing were noted.
Ongoing improvements in algorithms continue to yield better therapeutic solutions.

Implication

Review explores how machine learning enhances antiviral drug discovery, highlighting implications for future treatments.

Abstract

: 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.

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Cite This Study

Serafim et al. (2021) studied this question.

synapsesocial.com/papers/6a6151fd6795803b713f64e1 https://doi.org/10.1080/17460441.2021.1918098

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Machine learning techniques applied to the drug design and discovery of new antivirals: a brief look over the past decade

Key Points

Implication

Abstract

Discussion

Cite This Study

Machine learning techniques applied to the drug design and discovery of new antivirals: a brief look over the past decade

Key Points

Implication

Abstract

Discussion

Cite This Study

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