A significant effort has been expended in the last five decades toward theoretical and algorithmic studies in Computational Physics, Chemistry and Biology. In the last decade, the area of Deterministic Global Optimization has received a lot of attention from a variety of disciplines and this surge of interest is attributed to three main reasons. First, a large number of process engineering, computational chemistry, physics and biology problems are indeed global optimization problems. Second, existing local nonlinear optimization approaches may either fail to obtain even feasible solution or are trapped to a local optimum solution. Third, the global optimum solution may have a very different physical interpretation.

This seminar presentation contains three parts. In Part I, we will discuss briefly the mathematical modeling efforts for the proteins with focus on the potential energy and the solvation contributions. In Part II, we will present a novel deterministic global optimization framework for free energy calculations. In part III, we will focus on a rigorous approach for the tertiary structure prediction of peptides in the presence of sparse restraints that are derived from NMR experiments. Computational studies on a variety of oligopeptides will complement the theoretical advances, and demonstrate the potential applications.