Zhongyue (John) Yang
Assistant Professor of Chemistry
SC Family Dean’s Faculty Fellow
Dr. Yang will be accepting graduate students for Fall 2025.
Born in Tianjin, China, I graduated from Nankai University with a B.S. degree in Chemistry (Po-Ling class) in 2013. I received my Ph.D. in Theoretical and Computational Chemistry at the University of California, Los Angeles in 2017. From 2018 to 2020, I was a postdoctoral scholar in the Department of Chemical Engineering at Massachusetts Institute of Technology. I started as an Assistant Professor of Chemistry at Vanderbilt in 2020.
My long-term goal is to create a computational ecosystem, Mutexa, for intelligent protein engineering. Mutexa is short for “Alexa for mutants”, and we believe that how people engineer proteins in the future should be similar to the way we use Amazon Alexa in these days – if researchers intend to obtain the sequences of protein variants with desired functions, they just need to ask for help from a computational machine. Mutexa integrates high-throughput computation, bioinformatics, quantum chemistry, multiscale simulation, and data-driven modeling to identify protein mutants that can enhance functions including enzyme catalysis, peptide therapeutics, and disease biomarker detection.
In addition to intelligent protein engineering, I am also interested in understanding the dynamic nature of fundamental chemical processes. The Yang lab envisions to establish a conceptual framework to understand entropy-mediated reactive intermediates and investigate their relevance in chemical selectivity. |
Specializations
Enzyme Catalysis Protein Engineering Physical Organic Chemistry |
Representative Publications
https://orcid.org/0000-0003-0395-6617 https://scholar.google.com/citations?user=7lJU2ukAAAAJ&hl=en |
1. Yang, Z. J.*; Shao, Q.; Jiang, Y.; Jurich, C.; Ran, X.; Juarez, R.; Yan, B.; Stull, S.; Gollu, A.; Ding, N. “Mutexa: A Computational Ecosystem for Intelligent Protein Engineering” Journal of Chemical Theory and Computation (Under Review). Doi: 10.26434/chemrxiv-2023-2cvbs.
2. Yan, B.; Ran, X.; Gollu, A.; Cheng, Z.; Zhou, X.; Chen, Y.; Yang, Z. J.* “IntEnzyDB: an Integrated Structure-Kinetics Enzymology Database” Journal of Chemical Information and Modeling, 2022, 62, 5841-5848.
3. Shao, Q.; Jiang, Y.; Yang, Z. J.* “EnzyHTP: A High-Throughput Computational Platform for Enzyme Modeling” Journal of Chemical Information and Modeling, 2022, 62, 647-655.
4. Qin, Z. X.; Tremblay, M. T.; Hong, X.; Yang, Z. J.* “Entropic Path Sampling: Computational Protocol to Evaluate Entropic Profile along a Reaction Path” Journal of Physical Chemistry Letters, 2021, 12, 10713-10719.
5. Shin, W.; Ran, X.; Wang, X.; Yang, Z. J.* “Accelerated Entropic Path Sampling with Bidirectional Generative Adversarial Network” Journal of Physical Chemistry B, 2023, 127, 4254–4260. |