Computer-aided drug design in seeking viral capsid modulators

• Published in: Drug discovery today 2023-06, Vol.28 (6), p.103581-103581, Article 103581
• Main Authors: Zhao, Shujie, Zhang, Xujie, da Silva-Júnior, Edeildo Ferreira, Zhan, Peng, Liu, Xinyong
• Format: Article
• Language: English
• Subjects: Antiviral Agents - chemistry; Antiviral Agents - pharmacology; CADD; Capsid; capsid modulators; Computer-Aided Design; Drug Design; Drug Discovery; HBV; HIV-1; HRV; virtual screening
• ISSN: 1359-6446; 1878-5832
• DOI: 10.1016/j.drudis.2023.103581

[Display omitted] •Viral capsids, as essential structural proteins, are promising antiviral targets.•CADD approach such as virtual screening successfully applied in seeking viral capsid modulators.•AI such as deep learning will be a useful tool in the development of capsid modulators. Approved or licensed antiviral drugs have limited applications because of their drug resistance and severe adverse effects. By contrast, by stabilizing or destroying the viral capsid, compounds known as capsid modulators prevent viral replication by acting on new targets and, therefore, overcoming the problem of clinical drug resistance. For example, computer-aided drug design (CADD) methods, using strategies based on structures of biological targets (structure-based drug design; SBDD), such as docking, molecular dynamics (MD) simulations, and virtual screening (VS), have provided opportunities for fast and effective development of viral capsid modulators. In this review, we summarize the application of CADD in the discovery, optimization, and mechanism prediction of capsid-targeting small molecules, providing new insights into antiviral drug discovery modalities.