The Computational Structural Biology Section draws on multidisciplinary advances to decipher the mechanisms and pharmacology of oncogenic proteins and their signaling at the detailed molecular level.
Our work is based on the concept of the free energy landscape. The landscape describes protein molecules as consisting of ensembles of conformations, whose relative populations determine function.
The section pioneered the dynamic free energy landscape, conformational selection, and population shift as an alternative to the induced-fit textbook model to explain molecular recognition and allosteric regulation. Our ideas were validated by experiments.
We extended the ensemble model to catalysis, oncogenic activation, and mechanisms of inhibition, contributing to extraordinary advancements in understanding structure, function, and gain-of-function. Our innovative perspective clarifies observations, and makes predictions, aiming to deepen understanding of experimental and clinical observations.
The section focuses on Ras proteins, their oncogenic activators, including tyrosine kinases, and downstream pathways, including PI3K, PTEN, and MAPK (B-Raf/KSR/MEK).