Year: 2026
Type: review
Abstract: Molecular simulations have been central to our understanding of how enzymes work, and the ongoing explosion of artificial intelligence/ML (AI/ML) approaches is greatly expanding the scope of problems that can be addressed using simulations. The speed of development of the field is tremendous, with the near-constant development of new approaches and successful applications. This review aims to give a higher-level overview of four key areas where AI/ML approaches are significantly transforming computational enzymology (both understanding and design), specifically (1) enzyme discovery and functional annotation, (2) kinetic parameter prediction, (3) understanding of protein dynamics and enzyme reaction mechanisms, and (4) decoding protein allostery. We also discuss some of the outstanding technical challenges in this research space, and efforts being made to overcome them.
Institutions: Georgia Institute of Technology, Lund University
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $4,360
OpenAlex ID: W7224682361