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Nancy M. Amato, Guang Song, "Using Motion Planning to Map Protein Folding Landscapes and Analyze Folding Kinetics of Known Native Structures," Technical Report, TR01-001, Parasol Laboratory, Department of Computer Science, Texas A&M University, Oct 2001.
Technical Report(ps, pdf, abstract)

We present a novel approach for studying the kinetics of protein folding. The framework has evolved from a robotics motion planning technique called probabilistic roadmap methods (prms) that has been applied in many diverse fields with great success. In our previous work, we applied this method to study protein folding pathways of several small proteins and obtained some very encouraging results. In this paper, we describe how we applied our motion planning framework to the study of protein folding kinetics. In particular, we present a refined version of our motion planning 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.