Parameters for the Generalized Born Model Consistent with RESP Atomic Partial Charge Assignment Protocol

Abstract

Here we report a set of new parameters for the generalized Born (GB) model consistent with the RESP atomic partial charge assignment protocol. Effective atomic radii and screen factors as parameters have been obtained through genetic algorithm optimization in the parameter space to minimize the differences between the calculated and experimental solvation free energies. Here, the calculated solvation free energies are based on a GB model using partial charges fitted from the electrostatic potentials based on the 6-31G* basis set with the nonelectrostatic contributions to the free energy of solvation modeled in terms of the solvent accessible surface area (SASA). The mean unsigned error in the solvation free energies calculated by the GB/surface area calculations using the final parameters of the 328 neutral molecules in the training set is 0.85 kcal/mol, and for the 30 charged molecules the value is 4.36 kcal/mol. The refined parameters were then applied to predict the solvation free energies of 44 neutral or charged organic molecules and 15 proteins, and reliable results were obtained for both organic molecules and proteins. For the 36 neutral organic molecules in the test set, our parameters incurred an unsigned mean error of 0.73 kcal/mol, and for the eight charged molecules in the test set, our parameters incurred an unsigned mean error of 3.65 kcal/mol. For the 44 organic molecules, the performance of the GB/SA model based on our new parameters was much better than Possion-Boltzmann (PB)/SA and GB/SA based on Jayaram's parameters. For the 15 proteins randomly selected from the Protein Data Bank, the calculated results from GB/SA based on our new parameters also gave consistent results with those from PB/SA and were much better than GB/SA based on Jayaram's parameters. This model might be widely applied in molecules dynamics, protein folding, molecular docking, free energy calculations, and conformation analysis. Moreover, we are now supplying a program to help AMBER users apply our new parameters to their MD simulations.