Integrating Machine Learning and Molecular Modeling for Drug Design

Integrating Machine Learning and Molecular Modeling for Drug Design
Date & Time: 
Friday, April 15, 2022 - 09:00 to 10:00
Yingkai Zhang, New York University
Hosted via Zoom

Zoom ID: 984 6384 2049
Passcode: 402887
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The overall goal of our lab is to develop and apply state-of-the-art computational tools for rational drug design. In this talk, I will present our recent advances in targeting protein-protein interactions, developing machine-learning based protein-ligand scoring functions, and advancing deep learning models in chemistry.


Yingkai Zhang is a Professor in Department of Chemistry at New York University. He received his B.S. degree in Chemistry from Nanjing University and his Ph.D. degree from Duke University. His postdoctoral research was conducted at Howard Hughes Medical Institute, University of California at San Diego. He was a recipient of the National Science Foundation CAREER Award and Maximizing Investigators' Research Award (MIRA) from National Institute of General Medical Sciences. His current research interests are integrated molecular modeling and machine learning, rational drug design to target enzymes and protein-protein interactions, and computer simulations of biomolecular systems.

Seminar Series by the NYU-ECNU Center for Computational Chemistry at NYU Shanghai