Protein folding: computational approaches to an exponential-time problem
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We present a novel approach for studying the kinetics of protein folding. The framework has evolved from robotics motion planning techniques called probabilistic roadmap methods (prms) that have been applied in many diverse fields with great success. In our previous work, we used a Prm-based technique to study protein folding pathways of several small proteins and obtained encouraging results. In this paper, we describe how our motion planning framework can be used to study protein folding kinetics. In particular, we present a refined version of our Prm-based framework and describe how it can be used to produce potential energy landscapes, free energy landscapes, and many folding pathways all from a single roadmap which is computed in a few hours on a desktop PC. Results are presented for 14 proteins. Our ability to produce large sets of unrelated folding pathways may potentially provide crucial insight into some aspects of folding kinetics, such as proteins that exhibit both two-state and three-state kinetics, that are not captured by other theoretical techniques.