Systematic Methods for Learning Complex Mechanisms from Molecular Dynamics Simulations

ABSTRACT 

Computers and algorithms are now sufficiently powerful that many complex molecular processes can be simulated at atomic resolution.  Yet it remains challenging to describe dynamics when processes are stochastic and proceed by multiple pathways.  In this talk, I will illustrate these issues with simulations of insulin dimer dissociation, which serves as a paradigm for coupled (un)folding and (un)binding.  Then I will present recent work that we have done to advance methods for efficiently estimating kinetic statistics and systematically learning complex reaction mechanisms from molecular dynamics data.

Time and Location: 
3:30pm | Mechanical Engineering Building (MEC) Rm 205
Academic Year: 
2020
Event Date: 
Friday, February 21, 2020
Semester: 
Speaker: 
Dr. Aaron Dinner
Speaker Title: 
University of Chicago
Host: 
Professor Kateri DuBay