The goal of the NextGen Cardiovascular, Muscle & Metabolism Science Seminar is to highlight transdisciplinary precision research taking place in cardiovascular, muscle and metabolism fields; provide opportunities for collaboration among researchers to build their own research efforts; and promote clinical/researcher activity across the University of Missouri System and our partners.

For questions about this event, please reach out to Mackenzie Lynch.

“New Strategies for Predicting Protein Interactions and Applications to Structure-Based Drug Design”

Speaker: Xiaoqin Zou, Ph.D., Professor, Physics and Biochemistry, College of Agriculture, Food & Natural Resources, University of Missouri

Date: Sept. 9, 2024, noon-1 p.m.

Location: Tom and Linda Atkins Family Seminar Room, Roy Blunt NextGen Precision Health building 

Description

Proteins and their interactions with small chemical compounds (i.e., ligands) and other partners play critical roles in cellular functions. The ability to predict the structures of proteins bound with partners is important for understanding protein functions and for designing therapeutic interventions. However, this proves to be a daunting task due to the system's vast degrees of freedom. In this talk, I will present our recent studies on predicting protein-ligand and protein-peptide complex structures. The methods integrate information-driven modeling with physical chemistry-based computational modeling of flexible interaction modes. The methods have been systematically and extensively tested, and the results will be presented. I will also discuss our recent applications of the methods to structure-based therapeutic design.

About the Speaker

Xiaoqin Zou received her bachelor of science from Wuhan University and her Ph.D. from the University of California, San Diego. She is a professor at Mizzou, holding joint appointments in the Department of Physics, Department of Biochemistry, Dalton Cardiovascular Research Center and Institute of Data Science and Bioinformatics. Her research group focuses on developing novel computational methods to model protein interactions and aims to make far-reaching impacts on understanding underlying protein functions and on designing therapeutic interventions. Her research is highly interdisciplinary, integrating physics-based methods with bioinformatics-based and machine learning methods. Her group also closely collaborates with experimentalists on drug development for the treatment of cardiovascular arrhythmias, antibiotic resistance and cancer. She is a former NSF CAREER Award recipient and a current NIH MIRA grant recipient. She is an AAAS fellow and an American Physical Society fellow. Her team has been ranked as one of the top teams in the highly competitive international competitions on protein-protein and protein-ligand structure prediction.