This dissertation contains a couple of results on biophysics modeling and computation, ranging from solvated molecular conformation modeling to molecular solvation and binding modeling in the solvent environment.We study the solvent excluded surface in Eulerian representation, provide the surface area and enclosed volume calculation, the molecular topological analysis is also addressed. We further analyze the electrostatic for the solvated molecules with the Eulerian solvent excluded surface. We show that our surface is analytical without any numerical approximation.We study the coarse grid Poisson Boltzmann solver. Our software enables extremely accurate numerical solution to the Poisson Boltzmann equation even at very large grid spacing. As a consequence, our software provides a reliable electrostatic calculation for the solvation and protein ligand binding related problem.We study the blind solvation free energy prediction problem. A hybrid of physical and statistical protocol is proposed for highly accurate solvation free energy prediction. Furthermore, to mediate the force field parametrization influence on the solvation free energy prediction, we propose a learning to rank based solvation free energy prediction paradigm.We explore the protein ligand binding free energy prediction and docking scoring via the learning to rank approach. In which a learn to rank based scoring function is proposed for accurate protein ligand binding scoring.
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