Ryan Lee Hayes
Assistant Professor
The Henry Samueli School of Engineering
The Henry Samueli School of Engineering
B.S., Point Loma Nazarene University, 2007, Physics and Music
M.S., University of California San Diego, 2012, Physics
Ph.D., Rice University, 2015, Physics
M.S., University of California San Diego, 2012, Physics
Ph.D., Rice University, 2015, Physics
Email: rhayes1@uci.edu
University of California, Irvine
416F Engineering Tower
Mail Code: 2580
Irvine, CA 92697
416F Engineering Tower
Mail Code: 2580
Irvine, CA 92697
Research Interests
Protein Design, Molecular Dynamics, Alchemical Free Energy Calculations, Statistical Mechanics
Appointments
Postdoc University of Michigan 2015-2022
Research Abstract
Protein design is useful in many applications, including medicine, biocatalysis, and biotechnology. Gaps persist between experimental design methods that require some initial level of function, physical computational methods like Rosetta that suffer from low accuracy, and deep learning methods that provide less physical insight and tunability. Alchemical free energy methods have been widely successful in computer-aided drug design for their rigorous physical basis and high accuracy, but are too computationally expensive for widespread use in protein design. Lambda dynamics is a highly scalable alchemical free energy method that is uniquely well-suited for computational protein design due to its ability to characterize mutations at many sites simultaneously.
The Hayes lab develops of lambda dynamics for protein design and drug design problems. We use lambda dynamics together with powerful emerging deep learning techniques such as RFdiffusion and ProteinMPNN to design proteins for various applications with experimental collaborators. Current applications include redox enzyme design, therapeutic antibody or binder design, therapeutic protease design, and de novo design.
The Hayes lab develops of lambda dynamics for protein design and drug design problems. We use lambda dynamics together with powerful emerging deep learning techniques such as RFdiffusion and ProteinMPNN to design proteins for various applications with experimental collaborators. Current applications include redox enzyme design, therapeutic antibody or binder design, therapeutic protease design, and de novo design.
Short Biography
Ryan Hayes is an assistant professor in the department of Chemical and Biomolecular Engineering at the University of California Irvine. His research focuses on developing methods to enable protein design with lambda dynamics, but has also encompasses working with colleagues to apply lambda dynamics to computer-aided drug design. He holds a B.S. in physics and music from Point Loma Nazarene University in San Diego, and completed his Ph.D. with José Onuchic at UCSD and Rice University, where he learned to apply molecular simulation techniques to RNA and protein folding, and developed his longstanding interest in protein design. His postdoctoral training was at the University of Michigan with Charlie Brooks, where he began developing lambda dynamics for protein design.
Link to this profile
https://faculty.uci.edu/profile/?facultyId=7345
https://faculty.uci.edu/profile/?facultyId=7345
Last updated
01/07/2026
01/07/2026