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Elsevier

Machine Learning in Enzymology

  • 1st Edition, Volume 742 - January 10, 2027
  • Latest edition
  • Editors: Qiang Cui, David Christianson, Wenjun Xie, Karen N. Allen
  • Language: English

This volume surveys cutting-edge machine learning–based approaches for the study of enzyme catalysis, dynamics, and design. It brings together computational and experimental appro… Read more

Description

This volume surveys cutting-edge machine learning–based approaches for the study of enzyme catalysis, dynamics, and design. It brings together computational and experimental approaches that integrate molecular simulation, machine learning, and high-throughput data to interrogate enzymatic catalysis at multiple scales. The chapters in the volume highlight how data-driven frameworks complement physics-based models to advance mechanistic understanding and enable rational enzyme engineering.

Key features

  • Discussion of cutting-edge machine learning approaches for both computational and experimental studies of enzymes.
  • Integration of physics-based simulations with data-driven models to characterize enzymatic mechanisms.
  • Methodological frameworks for enzyme discovery and rational protein engineering.

Readership

Researchers in the areas of computational and experimental enzymology, protein and enzyme engineering.

Table of contents

1. Inferring conformational equilibria from sparse experimental data

2. TBD

3. Gaussian Process Regression and DeepMD models for simulating solution-phase and enzyme reactions

4. Modern Computational Enzymology Methods for Nucleic Acid Catalysis

5. Capturing Transition States of Enzyme Dynamics

6. Deep learning approaches for identifying the reaction coordinates and mechanisms of enzyme catalysis

7. Methods of walking in path space as applied to chemical reactions in enzymes

8. TBD

9. Using large language models for enzyme kinetics data extraction

10. Multidimensional Mechanistic Profiling at Scale with High-Throughput Enzymology

11. TBD

12. Using CLEAN for new enzyme discovery

13. Using EZSpecificity to expand the substrate border.

14. GeoEvoBuilder-Driven Enzyme Engineering with Enhanced Activity and Thermostability

Product details

  • Edition: 1
  • Latest edition
  • Volume: 742
  • Published: January 10, 2027
  • Language: English

About the editors

QC

Qiang Cui

Qiang Cui is a Professor of Chemistry at Boston University and also affiliated with Departments of Physics and Biomedical Engineering. He received B.S. in Chemical Physics from the University of Science and Technology of China in 1993, and Ph. D. in Theoretical Chemistry in 1997 from Emory University under the tutelage of Professor Keiji Morokuma. He conducted postdoctoral research with Professor Martin Karplus at Harvard University and, in 2001, moved to the University of Wisconsin, Madison as an assistant professor of Chemistry. After spending seventeen years in Madison, he moved back to Boston in 2018. His current research interest includes quantum chemistry and statistical mechanics and their application to various chemical, biological and materials problems.
Affiliations and expertise
Professor of Chemistry, Boston University, USA

DC

David Christianson

After completing studies for the A.B., A.M., and Ph.D. degrees in chemistry at Harvard University, David W. Christianson joined the faculty of the University of Pennsylvania, where he is currently the Roy and Diana Vagelos Professor in Chemistry and Chemical Biology. At Penn, Christianson’s research focuses on the structural and chemical biology of the zinc-dependent histone deacetylases as well as enzymes of terpene biosynthesis. His research accomplishments have been recognized by several awards, including the Pfizer Award in Enzyme Chemistry and the Repligen Award in Chemistry of Biological Processes from the American Chemical Society, a Guggenheim Fellowship, and the Elizabeth S. and Richard M. Cashin Fellowship from the Radcliffe Institute for Advanced Study at Harvard University. Christianson is also a dedicated classroom teacher, and his accomplishments in this regard have been recognized by the Lindback Award for Distinguished Teaching at Penn and a Rhodes Trust Inspirational Educator Award from Oxford University. Christianson has also held visiting professorships in the Department of Biochemistry at Cambridge University and the Department of Chemistry and Chemical Biology at Harvard University. Christianson has served with Prof. Anna Pyle as Co-Editor-in-Chief of Methods in Enzymology since 2015.

Affiliations and expertise
University of Pennsylvania, USA

WX

Wenjun Xie

Wenjun Xie is an Assistant Professor of Medicinal Chemistry at the University of Florida. He received his B.S. degree in chemistry and statistics in 2012 and his Ph.D. in physical chemistry in 2017 from Peking University, where he conducted research under the supervision of Professor Yiqin Gao. He subsequently completed postdoctoral training with Professor Bin Zhang at the Massachusetts Institute of Technology and Professor Arieh Warshel at the University of Southern California. His current research focuses on the development of artificial intelligence and computational chemistry approaches to understand enzyme catalysis and evolution.
Affiliations and expertise
Assistant Professor of Medicinal Chemistry, University of Florida, USA

KA

Karen N. Allen

Dr. Karen N. Allen works at the Department of Chemistry of the Boston University, the Metcalf Center for Science and Engineering
Affiliations and expertise
Department of Chemistry, Metcalf Center for Science and Engineering, Boston University, Boston, MA, USA