Year: 2024
Type: review
Abstract: In the past several years there has been rapid adoption of artificial intelligence (AI) and machine learning (ML) tools for drug discovery. In this Microperspective, we comment on recent AI/ML applications to the discovery of allosteric modulators, focusing on breakthroughs with AlphaFold, structure-based drug discovery (SBDD), and medicinal chemistry applications. We discuss how these technologies are facilitating drug discovery and the remaining challenges to identify allosteric binding sites and ligands.
Source: ACS Medicinal Chemistry Letters
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4402079130