This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Keywords to describe research content: Macromolecular crowding effects, confinement effects, protein stability and folding dynamics Keywords to describe computational methods used: Monte Carlo simulations, Brownian Dynamics, Metropolis algorithm, multi-histogram and replica-exchange methods Abstract: Motivated by the fact that inside a cell the environment surrounding a protein molecule is crowded with biological macromolecules, we shall carry out numerical simulation to investigate the effects of macromolecular crowding and confinement on protein stability and folding kinetics. Since all-atom explicit-solvent calculations are still too time-consuming at the present time, we shall use reduced models of protein in our simulations, for example, the HP lattice models and bead models. We shall calculate the thermodynamic properties of a protein chain in the presence of hundreds or more of crowders, assuming that no specific interactions exist between the protein of interest and the crowder molecules. Theoretical treatments based on statistical thermodynamics predict the mere presence of these crowder molecules affects the stability and kinetic properties of protein and the effects depend on both the number of crowders and the size of crowders. Interesting thermodynamic properties to calculate include heat capacity, the average radius of cyration, and the average energy of the protein chain as a function of temperature. In particular, we are interested in obtain the melting temperature of the folding-unfolding transition from the heat capacity calculations. To calculate the heat capacity, the Monte Carlo procedure based on the Metropolis algorithm will be used. Furthermore, Brownian dynamics should be used to treat the motions of the protein molecule and the crowders inside the virtual box with periodic boundary conditions. To overcome the serious problems due to trapping by local minima or intermediate conformations, we shall use both the multi-histogram and the replica-exchange methods. Furthermore, to study how folding dynamics are affected by the presence of crowders, we shall also calculate folding tiem and unfolding time by the mean first passage time methods. All the methods and techniques discussed above can also be applied for the study of the confinement effects on protein stability and dynamics, for instance, a protein molecule encapsulated in a cavity of a biosensor. Here we are interested in studying how melting temperature varies with the box size. Theories predict and preliminary results based on the HP lattice model confirm that melting temperature increases when box size decreases. As in the crowding simulations, we shall also study folding and unfolding rates in the confinement study.
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