DESCRIPTION (provided by applicant): Advances in computational hardware and molecular modeling techniques have revolutionized our ability to simulate electrostatic interactions which play a fundamental role in the stability, structure, folding and function of bio-molecules. Currently, the continuum electrostatic description based upon the Poisson- Boltzmann Equation (PBE) offers the best combination of modeling fidelity and computational cost. While very large bio-molecular assemblies such as ribosomes, containing hundreds of thousands of atoms, have been successfully solved using PBE solvers, major difficulties are encountered when these solvers are incorporated into molecular dynamics (MD) and energy minimization (EM) codes. Impaired accuracy of predicted electrostatic field at molecular surfaces destabilizes MD simulations and hinders convergence in EM computations. The proposed effort will provide new computational tools to accurately and efficiently predict the required electrostatic properties near the molecular surface. Previous technology, notably a novel adaptive Cartesian grid structure that maximizes computational performance for large-scale bio-molecules, will be modified to achieve high accuracy at the surface. The resulting computational tool should prove invaluable to: (i) MD and EM calculations by efficiently providing high fidelity, PBE-quality electrostatic energy gradients and (ii) researchers interested in relating electrostatic surface properties (e.g., potential and induced charge) to bio-molecular function.