Combinatorial Statistical Mechanics of Protein Folding

University Of California San Francisco, San Francisco CA

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Abstract

We propose to develop statistical mechanical theory for protein stability and folding kinetics. Lattice models are unrealistically simplified All- atom simulations don't explore enough conformation space. We propose a graph theoretic (GT) approach that covers conformational space broadly, yet can be used with many different models, including anatomically detailed ones. We are calculating partition functions, so: enthalpies, entropies, heat capacities of folding, m-values for denaturants, pH and salt-induced transitions, transitions to molten globules, thermal factors, and hydrogen exchange protection factors. What is novel here is a proper treatment of the density of states essential for any microscopic theory of stability and kinetics. We are also treating folding kinetics, which we aim to apply to realistic models and specific proteins, including lysozyme, cytochrome C, ribonuclease, and others. Ultimately, understanding the fluctuations and other non-native states of proteins will be essential for predicting protein function and mechanism.