Millisecond Timescale, Atomistic Protein Folding Simulations Yield a Network Theory for Protein Folding

Abstract

Understanding protein folding is a classic grand challenge in molecular biophysics; a solution for which could have immediate medical benefits, particularly for protein misfolding diseases like Alzheimer's. Molecular Dynamics (MD) simulations have the potential to provide quantitative models of protein folding but, unfortunately, this potential has yet to be fully realized due to the need to capture long-timescale transitions at atomic resolution. Taking advantage of a new theory for molecular kinetics and the computational power of Graphics Processing Units (GPUs), however, we are now able to reach millisecond timescales at atomic resolution (one million times longer than conventional simulations). But, how can one use these simulations to gain insight? We present a novel network theory which is capable of quantitative prediction of the native states and folding timescales for the villin headpiece and NTL9, which fold on microsecond and millisecond timescales respectively. Furthermore, it leads to experimentally testable hypotheses about the nature of protein free energy landscapes and how proteins fold so quickly. We also reduce these concepts to simpler and more fundamental, humanly comprehensible networks that capture the essence of molecular kinetics and reproduce qualitative phenomena like apparent two-state folding. Models at both the quantitative and qualitative levels are crucial for gaining an intuition for molecular kinetics and for ultimately answering the general question of “how do proteins fold?”