Author
Congratulations to Galen for being selected as a Beckman Scholar
Sep. 21, 2025—Beckman Scholars Program helps stimulate, encourage, and support research activities by talented, full-time undergraduate students who are pursuing their studies at accredited four-year colleges and universities located in the United States of America. (Left to right: Prof. John Yang, Galen Wei, and Xinchun Ran). Note: Xinchun serves as the graduate student mentor for Galen.
Farewell Party for Dr. Elsa Ding and Yinjie Zhong
Sep. 21, 2025—It’s sad to say goodbye, and we wish them the best in their future career!
Thank you Bill for visiting us!
Sep. 21, 2025—Prof. William Jorgensen visited us from Yale!
Thank you Sharon for visiting us!
Sep. 21, 2025—Prof. Sharon Hammes-Schiffer visited us from Princeton. Our former undergraduate trainee Matthew Tremblay is currently working with Prof. Hammes-Schiffer as a graduate student.
Thank you Nate for visiting us!
Sep. 21, 2025—Prof. Nathan DeYonker visited us from U. Memphis.
EnzyHTP: A High-Throughput Computational Platform for Enzyme Modeling
Sep. 21, 2025—EnzyHTP is a holistic platform that allows high-throughput molecular simulation of enzymes. The large-scale collection of molecular simulation data presents a significant challenge due to complex demands. To build an enzyme model appropriate for simulations, multiple hierarchies of structural definitions and treatments must be established such as protein stoichiometry, binding site, predicting amino acid protonation...
Entropic Path Sampling
Sep. 21, 2025—Entropic path sampling (EPS) was developed by our group as a trajectory-based protocol to quantify how configurational entropy varies along a reaction path, especially after the transition state, by harvesting ensembles of snapshots from quasiclassical direct-dynamics trajectories, slicing them into structural windows (e.g., by forming-bond length), and computing entropy with an internal-coordinate, histogram-based estimator using...
Deep Learning Models for Protein Function Prediction
Sep. 21, 2025—EnzyKR and DeepLasso illustrate how task-specific neural architectures, grounded in physical constraints (activation barriers, topology) and trained on structure- or library-scale data, can deliver actionable predictions for enzyme selectivity and RiPP bioactivity in real design workflows. EnzyKR. EnzyKR is a chirality-aware deep learning framework for stereoselective biocatalysis. It uses a classifier–regressor pipeline that first identifies...