How well does a restrained electrostatic potential (RESP) model perform in calculating conformational energies of organic and biological molecules?

In this study, we present conformational energies for a molecular mechanical model (Parm99) developed for organic and biological molecules using the restrained electrostatic potential (RESP) approach to derive the partial charges. This approach uses the simple “generic” force field model (Parm94), and attempts to add a minimal number of extra Fourier components to the torsional energies, but doing so only when there is a physical justification. The results are quite encouraging, not only for the 34-molecule set that has been studied by both the highest level ab initio model (GVB/LMP2) and experiment, but also for the 55-molecule set for which high-quality experimental data are available. Considering the 55 molecules studied by all the force field models for which there are experimental data, the average absolute errors (AAEs) are 0.28 (this model), 0.52 (MM3), 0.57 (CHARMm [MSI]), and 0.43 kcal/mol (MMFF). For the 34-molecule set, the AAEs of this model versus experiment and ab initio are 0.28 and 0.27 kcal/mol, respectively. This is a lower error than found with MM3 and CHARMm, and is comparable to that found with MMFF (0.31 and 0.22 kcal/mol). We also present two examples of how well the torsional parameters are transferred from the training set to the test set. The absolute errors of molecules in the test set are only slightly larger than in the training set (differences of <0.1 kcal/mol). Therefore, it can be concluded that a simple “generic” force field with a limited number of specific torsional parameters can describe intraand intermolecular interactions, although all comparison molecules were selected from our 82-compound training set. We also show how this effective two-body ∗Permanent affiliation: Department of Chemistry, University of Warsaw, Warsaw, Poland Correspondence to: P. A. Kollman; e-mail: [email protected]; web site: http://www.amber.ucsf.edu/amber/ Contract/grant sponsor: National Institutes of Health; contract/grant numbers: IH GM-29072; NIH CA-25644, NIH GM-