Solute energy based REMD : developments and applications to prion protein misfold predictions

Molecular dynamics (MD) simulations have increasingly contributed to the understanding of biomolecular processes, allowing for predictions of thermodynamic and structural properties. Unfortunately, the holy grail of protein structure prediction was soon found to be severely hampered by the very rugged free energy surface of proteins, with small relative free energies separating native, folded protein conformations from unfolded states. These multiple minima frequently trap present-day protein MD simulations permanently. In order to allow the simulation to escape minima and explore wider portions of conformational space, enhanced sampling techniques were developed. One of the most popular ones, replica exchange molecular dynamics (REMD), is based on multiple parallel MD simulations that are performed with replicas of a system at increasing temperatures T1, T2, etc. Periodic Monte Carlo exchange moves are attempted, aiming to allow conformations to exchange temperature ensembles with a probability that depends on their potential energy and temperature difference. Thus, conformations are simulated at all temperatures and escape local minima with the kinetic energy provided at higher temperatures, while Boltzmann distributions are generated at all temperatures. REMD has been successful in ab-initio folding of a variety of small peptides and proteins (up to 20-30 residues). However, with larger proteins, the overlap of potential energy distributions diminishes, since the potential energy and its fluctuation scale with fkBT, respectively with √fkBT, where f is the number of degrees of freedom of the system, kB Boltzmann's constant and T the temperature. Consequently, the related Monte Carlo exchange probability and number of exchanges in a simulation are also diminished. This is generally compensated by choosing smaller temperature intervals between replicas and thereby increasing the number of necessary replicas (as well as the computational cost of the simulation) to cover a given temperature range. An additional problem relates to explicit solvent simulations, in which solvent to solvent interactions account for the largest part of the total potential energy. Consequently, explicit solvent REMD simulations almost exclusively sample solvent degrees of freedom. These two limitations have lead to the development of REMD protocols for large explicit solvent systems that are based on exchange probabilities computed with subsystem (e.g. protein only) potential energy functions, allowing for a targeted sampling of protein degrees of freedom and a reduction of the computational effort. In this thesis, this approximation is tested by implementing its simplest variation that entirely neglects solvent-solvent interaction as a new REMD protocol termed REM Dpe (Chapter 2). Possible REMD limitations for large explicit solvent systems are tested (Chapter 3) with REM Dpe, which is further applied to perform a thorough and comparative investigation of prion (Chapter