Simbios Talk by Greg Bowman, Stanford University, November 11, 2009

Title: Markov state models: A network theory for molecular kinetics reveals the nature of protein free energy landscapes

Understanding molecular kinetics, and particularly protein folding, is a classic grand challenge in molecular biophysics. Network models, such as Markov State Models (MSMs), are one potential solution to this problem. Indeed, MSMs have recently yielded quantitative agreement with experimentally derived structures and folding timescales for specific systems. However, to truly deserve the title “theory”, these networks must provide an intuition for molecular kinetics that leads to experimentally testable hypotheses. Here we use existing MSMs for the villin headpiece and NTL9, which were constructed from atomistic simulations, to accomplish this goal. In addition, we provide simpler, humanly comprehensible networks that capture the essence of molecular kinetics and reproduce qualitative phenomena like apparent two-state folding. Together, these models provide an intuition for the free energy landscapes that govern molecular kinetics.