Development of accurate and efficient models for biological molecules

The abnormal expression or function of biological molecules, such as nucleic acids, proteins, or other small organic molecules, lead to the majority of diseases. Consequently, understanding the structure and function of these molecules through modeling can provide insight and perhaps suggest treatment for diseases. However, biologically relevant molecular phenomenon can vary vastly in the nature of their interactions and different classes of models are required to accommodate for this diversity. The objective of this thesis is to develop models for small molecules, amino acid peptides, and nucleic acids. A physical polarizable molecular mechanics model is described to accurately represent small molecules and single atom ions and applied to predict experimentally measurable thermodynamic properties such as hydration and binding free energies. A novel physical coarse-grain model based on Gay-Berne potentials and electrostatic multipoles has been developed for short peptides. The fraction of residues that adopt the alpha-helix conformation agrees with all-atom molecule dynamics results. Finally, a statistically-derived model based on sequence comparative sequence alignments is developed and applied to improve folding accuracy of RNA molecules.