Computational Modeling of Biomolecular Systems: Insights Into Protein Dynamics, Free Energy and Peptide/Ligand Binding
The opening of the 21st century has been marked as a generation of biological science. Nowadays, the understanding of the sequence and structure of biomolecules is growing rapidly. And researchers from multiple disciplines, chemistry, physics and computational science in particular, are making significant contributions to modern biology and drug discovery. The state-of-the-art techniques of computational chemistry and molecular modeling can be applied to study a wide range of chemical and biological systems of interest. This enables us to study structural details at the atomic level and obtain chemical/biological information which is not available by experimental measurements. This dissertation project focused on modeling the recognition mechanisms of biomolecules and their conjugated ligands. Multiple computational techniques, such as molecular dynamics simulation, entropy and free energy calculation were applied. The model systems included signaling domains (FHA, BRCT and WW domain), kinase (p38 kinase) and HIV protease. The details of the dynamics, interactions and correlations of domain-phosphopeptide systems were discovered. The free energy calculation, mining minima algorithm, was performed to study detailed conformational changes of kinase-ligand systems and predict protein-ligand binding energies. In addition, the association process of protein and ligand, which requires large simulation time scales, was also investigated. This project studies the details of protein-peptide/ligand binding and provides clues for further structure-based biomolecule/drug design.