Computer Simulations of Protein Folding and Evolution

Computer simulations for investigating protein folding and evolution are presented. In chapter 1, an all-atom model with a knowledge-based potential is used to study the folding kinetics of Formin-Binding protein. We study the folding kinetics by performing Monte Carlo simulations. We examine the order of formation of two beta-hairpins, the folding mechanism of each individual beta-hairpin, and transition state ensemble (TSE) and compare our results with experimental data and previous computational studies. Further, a rigorous Pfold analysis is used to obtain representative samples of the TSEs showing good quantitative agreement between experimental and simulated phi values

Probing the free energy landscape of the FBP28WW domain using multiple techniques

The free-energy landscape of a small protein, the FBP 28 WW domain, has been explored using molecular dynamics (MD) simulations with alternative descriptions of the molecule. The molecular models used range from coarse-grained to all-atom with either an implicit or explicit treatment of the solvent. Sampling of conformation space was performed using both conventional and temperature-replica exchange MD simulations. Experimental chemical shifts and NOEs were used to validate the simulations, and experimental values both for validation and as restraints. This combination of different approaches has provided insight into the free energy landscape and barriers encountered by the protein during folding and enabled the characterization of native, denatured and transition states which are compatible with the available experimental data. All the molecular models used stabilize well defined native and denatured basins; however, the degree of agreement with the available experimental data varies. While the most detailed, explicit solvent model predicts the data reasonably accurately, it does not fold despite a simulation time 10 times that of the experimental folding time. The less detailed models performed poorly relative to the explicit solvent model: an implicit solvent model stabilizes a ground state which differs from the experimental native state, and a structure-based model underestimates the size of the barrier between the two states. The use of experimental values both as restraints, and to extract structures from unfolding simulations, result in conformations which, although not necessarily true transition states, appear to share the geometrical characteristics of transition state structures. In addition to characterizing the native, transition and denatured states of this particular system in this work, the advantages and limitations of using varying levels of representation are discussed