COARSE-GRAINED MODELING OF PROTEIN STRUCTURE, DYNAMICS AND PROTEIN-PROTEIN INTERACTIONS

Abstract

Theoretical prediction of protein structures and dynamics is essential for understanding the molecular basis of drug action, metabolic and signaling pathways in living cells, designing new technologies in the life science and material sciences. We developed and validated a novel multiscale methodology for the study of protein folding processes including flexible docking of proteins and peptides. The new modeling technique starts from coarse-grained large-scale simulations, followed by selection of the most plausible final structures and intermediates and, finally, by an all-atom rectification of the obtained structures. Except for the most basic bioinformatics tools, the entire computational methodology is based on the models and algorithms developed in our lab. The coarse grained simulations are based on a high-resolution lattice representation of protein structures, a knowledge based statistical force field and efficient Monte Carlo dynamics schemes, including Replica Exchange algorithms. This paper focuses on the description of the coarse-grained CABS model and its selected applications.