Yaxia Yuan
استادیار · Computer-Aided Drug Discovery
University of Texas Health Science Center at San Antonioمعرفی
Dr. Yaxia Yuan is an Assistant Professor in the Department of Biochemistry & Structural Biology at the University of Texas Health Science Center at San Antonio (UTHSCSA). She serves as Associate Director of the Center for Innovative Drug Discovery (CIDD) and Director of the Computer-Aided Drug Discovery (CADD) Core. Her research focuses on computational drug discovery methodologies, including algorithm development for PROTEOLYSIS TARGETING CHIMERA (PROTAC) design and applications in oncology, longevity, and neurodegenerative diseases. Dr. Yuan earned her B.Sc. and Ph.D. from Peking University, followed by postdoctoral training at the University of Kentucky.
Her research interests span targeted protein degradation (PROTACs), synthetic high-density lipoprotein (HDL) therapies, and development of inhibitors for cancer-related targets such as BCL-XL, JNK1, and PELP1. Her work integrates structural biology, molecular modeling, and medicinal chemistry to advance drug discovery pipelines. Key contributions include dual BCL-XL/BCL-2 degraders, computational HDL designs for sepsis treatment, and structure-based discovery of mPGES-1 inhibitors for anti-inflammatory therapies.
- Education:
- B.Sc., Peking University, China
- Ph.D., Peking University, China
- Professional Roles:
- Associate Director, CIDD
- Director, CADD Core
Dr. Yuan's publications emphasize innovation in drug design strategies, including dynamic scoring methods (DyScore) and multi-target ligand approaches. Her work bridges computational modeling with experimental validation to address unmet medical needs in cancer, sepsis, and neurodegenerative disorders. Ongoing projects focus on optimizing PROTAC efficacy, elucidating molecular mechanisms of HIV-1 Tat protein interactions with dopamine transporters, and developing next-generation anti-inflammatory agents.
Labs/Teams: Her research is conducted through the CIDD and CADD Core facilities, which provide advanced structural and computational resources for collaborative drug discovery initiatives.
