Abstract: The ability to discriminate native structures from computer-generated misfolded ones is key to predicting the three-dimensional structure of a protein from its amino acid sequence. Here we describe an assessment of semiempirical methods for discriminating native protein structures from decoy models. The discrimination of decoys entails an analysis of a large number of protein structures and provides a large-scale validation of quantum mechanical methods and their ability to accurately model proteins. We combine our analysis of semiempirical methods with a comparison of an AMBER force field to discriminate decoys in conjunction with a continuum solvent model. Protein decoys provide a rigorous and reliable benchmark for the evaluation of scoring functions, not only in their ability to accurately identify native structures but also to be computationally tractable to sample a large set of non-native models.

Authors: Andrew M. Wollacott and Kenneth M. Merz, Jr.

Reference: Journal of Chemical Theory and Computation. 2007, ASAP Article. (see link for full paper).

Abstract: Here we describe the development of a classical force field parameter set to reproduce the geometry of proteins minimized at the semiempirical quantum mechanical level. The overall goal of the development of this new force field is to provide an inexpensive, yet reliable, method to arrive at geometries that are more consistent with a semiempirical treatment of protein structures. Since the minimization of a large number of protein structures at the semiempirical level can become cost-prohibitive, a "preminimization" with an appropriately parametrized classical treatment could potentially lead to more computationally efficient methods for studying protein structures through semiempirical means. Here we demonstrate that this force field allows for more rapid and stable geometry optimizations at the semiempirical level and can aid in the adoption of quantum mechanical calculations for large biological systems.

Authors: Andrew M. Wollacott and Kenneth M. Merz, Jr.

Reference: J. Chem. Theory Comput. 2006, 2(4), 1070-1077. (see link for full paper).