Advances in computational biophysics depend critically on the development of accurate effective potentials and powerful sampling methods to traverse the rugged energy landscapes that govern protein folding, binding, and fitness. I will review work in my lab over the last several years concerning the construction of all-atom implicit solvent effective potentials [1] for proteins and multi-scale methods for simulating their allostery, binding, and folding [2,3,4]. The Analytical Generalized Born Non-Polar (AGBNP) model is an analytical implicit solvent model we have developed for modeling solvated proteins and small molecules. I will discuss some recent results with AGBNP2 to model the thermodynamics of binding in host-guest systems.References[1] Gallicchio, E., K. Paris, and R.M. Levy. AGBNP2 Implicit Solvent Model. J. Chem. Theory & Comp., 5, 2544-2564 (2009).[2] Deng, N., W. Zheng, E. Gallicchio, and R.M. Levy. Insights into the Dynamics of HIV-1 Protease: a Kinetic Network Model Constructed from Atomistic Simulations. J. Am. Chem. Soc., 133, 9387-9394 (2011) doi.10.1021/ja2008032[3] Gallicchio, E., and R.M. Levy. Advances in all atom sampling methods for modeling protein-ligand binding affinities. Current Opinion in Structural Biology, 21, 161-166 (2011) doi.10.1016/j.sbi.2011.01.010[4] Zheng, W., E. Gallicchio, N. Deng, M. Andrec, and R.M. Levy. Kinetic Network Study of the Diversity and Temperature Dependence of TRP-Cage Folding Pathways: Combining Transition Path Theory with Stochastic Simulations. J. Phys. Chem. B, 115, 1512-1523 (2011) doi.10.1021/jp1089596

Exploring landscapes for protein allostery, binding, and folding: Implicit solvent effective potentials, replica exchange dynamics, and kinetic network models

244th National Meeting (2012)

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