Jennifer Kung
Senior Scientist Denali Therapeutics Inc.
Jennifer Kung is a Senior Scientist in Structural Biology at Denali Therapeutics, where she applies advanced structural biology approaches to support the discovery and development of innovative therapeutics. Prior to joining Denali, she was a Postdoctoral Research Fellow in Structural Biology at Genentech, working under the mentorship of J. Sudhamsu. Jennifer earned her PhD in Biophysics from the University of California, San Francisco, conducting research in the laboratory of Natalia Jura focused on the structural and mechanistic understanding of cell signaling proteins. With over a decade of experience, she brings deep expertise in protein structure, molecular mechanisms, and therapeutic discovery.
Seminars
- Leveraging structural data to design protein engineering strategy
- Using HDX MS & crystallography to understand impact of mutations on conformational dynamics
- Employing computational modeling to interrogate effects of mutations on enzyme stability
Structural biology can provide powerful insights into molecular recognition and binding, but its greatest value comes when those insights are generated early enough and applied broadly enough to influence drug design. As discovery teams increasingly seek to use structures to improve not only binding but also stability, expression, and developability, the challenge is creating workflows that translate structural information into better molecules. Join structural biologists, medicinal chemists, computational scientists, and drug discovery leaders as they discuss how to maximise the impact of SBDD on candidate progression by:
- Bringing structural information earlier into discovery, examining how delays between chemistry and structural data can limit decision making and how teams can prioritize structures that have the greatest potential to influence molecular design
- Translating structural insights into broader molecular optimization, exploring how structural information can be used to improve affinity and binding while also informing stability, expression, and developability
- Connecting structure-guided design with candidate progression, discussing how structural and computational insights can be incorporated into hit prioritization, lead optimization, and candidate selection to deliver better molecules more efficiently
