This application addresses broad Challenge Area (06) Enabling Technologies and specific Challenge Topic, 06-GM-103: Development of predictive methods for molecular structure, recognition, and ligand interaction. Biomedical computation has become a powerful tool for understanding biological properties and function. The goal of computational biology is to make quantitative predictions of biochemical processes with chemical accuracy, i.e., to within one kcal/mol for absolute quantities and 1 kcal/mol for relative quantities. This is a daunting task in view of the complexity and size of biomolecular systems in a cellular environment, and we are still far from achieving this important goal. At the heart of molecular calculation is the potential energy function that describes intermolecular interactions in the system, and often it is the accuracy of the potential energy surface that determines the reliability of the simulation results. Although the current molecular mechanics force fields have been very successful in biomolecular modeling thanks to tremendous efforts in parameterization in the past forty years, the functional forms have hardly changed since the late 1960s. In this project, we propose to develop an electronic structure-based quantum mechanical force field, called the explicit polarization (X-Pol) potential, for obtaining the potential energy surfaces of biomolecular systems containing proteins. This represents a major paradigm change, going beyond the current classical models to the quantum mechanical realm of biomedical computing. The X-Pol potential is based on a hierarchy of approximations that can be developed using semiempirical or ab initio molecular orbital theory or density functional theory. The feasibility of such an explicit quantum mechanical force field has been demonstrated. The proposed research offers a great opportunity for a quantum leap in improving computational accuracy in biomedical simulation, and the computational tools developed in this work will be of general importance to protein engineering and inhibitor design. PUBLIC HEALT RELEVANCE: Biomedical computation has become a powerful tool for understanding biological properties and function. The research described in this proposal aims at the development of a novel computational approach that represents a paradigm change in the way that we describe intermolecular interactions and it is expected to significantly increase the accuracy of computational results. This in turn can help design inhibitors and engineer specialized proteins for biomedical and industrial applications.