【第５回　統合バイオイブニングセミナーセミナー】

In this lecture I will present background and recent developments in protein theory that provide a unified statistical-mechanical view of protein folding and evolution. First we will discuss the physical and statistical requirements for protein sequences to fold cooperatively into a stable unique conformations - an "energy gap criterion". Next, based on this criterion we present a mean-field picture of protein evolution which provides insights on how protein sequences were discovered in the process of natural selection. These ideas provide guidance in building models of real proteins which remain tractable by modern computational methods but which retain most key features of protein energetics such that native structures retain their key property of being global energy minima. These energetic schemes are combined with novel Monte-Carlo simulations of protein folding in which all heavy atoms are represented as interacting hard spheres of various sizes corresponding to their van-der-Waals radii. Simulations of this model result in folding to the native structures with near X-ray accuracy. By recording many folding events over over a wide range of temperatures a possible microscopically detailed folding mechanism for several small proteins obtained, using novel graph-theoretical analysis to identify robust invariant features of folding process. Further, using a novel computational approach (Pfold analysis) we were able to fully characterize Transition State Ensemble of a number of proteins providing detailed predictions that can be further tested by experiments. These results present a "proof-of-principle" for the possibility of a solution of protein folding problem at an all-atom level, provided that one has a realistic all-atom potential energy function that correctly favors the native state

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