Cited by 118Computational Drug Discovery MethodsMachine Learning in Materials ScienceSARS-CoV-2 and COVID-19 Research

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De Novo Design of New Chemical Entities for SARS-CoV-2 Using Artificial Intelligence

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Bung, Navneet, Krishnan, Sowmya R, Bulusu, Gopalakrishnan, Roy, Arijit·2021·Future Medicinal Chemistry

DOI 10.4155/fmc-2020-0262PMC PMC7888348

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Abstract

Background: The novel coronavirus SARS-CoV-2 has severely affected the health and economy of several countries. Multiple studies are in progress to design novel therapeutics against the potential target proteins in SARS-CoV-2, including 3CL protease, an essential protein for virus replication. Materials & methods: In this study we employed deep neural network-based generative and predictive models for de novo design of small molecules capable of inhibiting the 3CL protease. The generative model was optimized using transfer learning and reinforcement learning to focus around the chemical space corresponding to the protease inhibitors. Multiple physicochemical property filters and virtual screening score were used for the final screening. Conclusion: We have identified 33 potential compounds as ideal candidates for further synthesis and testing against SARS-CoV-2.

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Authors: Bung, N., Krishnan, S. R., Bulusu, G., & Roy, A.
Affiliations: Tata Consultancy Services (India) (IN)
Corresponding author: Bulusu, Gopalakrishnan
Roy, Arijit
ORCID: Bung, Navneet
Krishnan, Sowmya R
Bulusu, Gopalakrishnan
Roy, Arijit
Venue: Future Medicinal Chemistry
Publisher: Informa UK Limited
Published: 2021-02-16
Volume: 13
Issue: 6
Pages: 575-585
ISSN: 1756-8919 (ISSN-L)
1756-8927
DOI: 10.4155/fmc-2020-0262
PMC: PMC7888348
OpenAlex: W3090171308
Cited by: 118
References: 58
Citations by year: 2026: 9 · 2025: 11 · 2024: 17 · 2023: 13 · 2022: 24 · 2021: 29
FWCI: 10.81
Type: journal article
Language: en
Open access: green
doi.org
Licence: cc-by-nc-nd
Locations: Future Medicinal Chemistry (publishedVersion)
ChemRxiv (acceptedVersion, cc-by-nc-nd)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
Royal College of Surgeons in Ireland (submittedVersion, cc-by-nc-nd)
Topics: Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
Keywords: SARS-CoV-2, main protease, Mpro inhibitors, de novo drug design, generative models, deep neural network, transfer learning, reinforcement learning, virtual screening, antiviral agents
MeSH terms: COVID-19, SARS-CoV-2, Coronavirus 3C Proteases, COVID-19 Drug Treatment, Antiviral Agents, Artificial Intelligence, Humans, Ligands, Protease Inhibitors, Drug Design, Drug Discovery, Molecular Docking Simulation

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