First Name
Zhongyue
Middle Name
Last Name
Yang
Organization
Vanderbilt University
Job Title
Email
zhongyue.yang@vanderbilt.edu
Research Summary
My research group focuses on integrating first-principles simulation and data-driven modeling to automatically evaluate, understand, and design functional biomolecules for catalytic and biomedical applications.
Research Description
Protein engineering holds immense promise in shaping the future of biomedicine and biotechnology. This review focuses on our ongoing development of Mutexa, a computational ecosystem designed to enable "intelligent protein engineering". In this vision, researchers can seamlessly acquire sequences of protein variants with desired functions as biocatalysts, therapeutic peptides, and diagnostic proteins by interacting with a computational machine, similar to how we use Amazon Alexa in these days. The technical foundation of Mutexa has been established through the development of database that integrates enzyme structures with their respective functions (e.g., IntEnzyDB), workflow software packages that enable high-throughput protein modeling (e.g., EnzyHTP and LassoHTP), and scoring functions that map the sequence-structure-function relationship of proteins (e.g., EnzyKR and DeepLasso). We will showcase the applications of these tools in benchmarking the convergence conditions of enzyme functional descriptors across mutants, investigating protein electrostatics and cavity distributions in SAM-dependent methyltransferases, and understanding the role of non-electrostatic dynamic effects in enzyme catalysis. Finally, we will conclude by addressing the future steps and challenges in our endeavor to develop new Mutexa applications that facilitate the selection of beneficial mutants in enzyme engineering.
Research Keywords
Multiscale simulations, protein engineering, quantum chemistry, machine learning
Working with Rosetta Since
2021