Empirical modifications to the Amber/OPLS potential for predicting the solution conformations of cyclic peptides by vacuum calculations.

BACKGROUND: Peptides have ubiquitous roles in all biological systems and are thus of interest in both basic and applied research. The rational design of bioactive peptides could be greatly enhanced by an efficient method for accurately predicting the conformations that these molecules can adopt in solution. As a design process inevitably requires testing numerous molecules, an efficient method would require the calculations to be performed in vacuum. RESULTS: Attempts to predict the conformations of cyclic peptides using a simulated annealing protocol with the Amber/OPLS potential in vacuum resulted, not unexpectedly, in overly packed, non-native conformations. We therefore empirically modified the potential by several cycles of structure prediction and function refinement until a good fit between experimental and predicted conformations was obtained. Three major modifications to the potential were required in order to reproduce the solution structures of cyclic peptides: explicit torsional energies for the peptide backbone torsional angles; explicit hydrogen-bonding energies for backbone hydrogen bonds; and a penalty for close approaches between uncharged and charged atoms. CONCLUSIONS: Using the modified potential, we predicted the solution conformations of cyclic peptides in the size range of 5-10 residues with reasonable accuracy.

Coupling the folding of homologous proteins.

The empirical observation that homologous proteins fold to similar structures is used to enhance the capabilities of an ab initio algorithm to predict protein conformations. A penalty function that forces homologous proteins to look alike is added to the potential and is employed in the coupled energy optimization of several homologous proteins. Significant improvement in the quality of the computed structures (as compared with the computational folding of a single protein) is demonstrated and discussed.

Simultaneous and coupled energy optimization of homologous proteins: a new tool for structure prediction.

BACKGROUND: Homology-based modeling and global optimization of energy are two complementary approaches to prediction of protein structures. A combination of the two approaches is proposed in which a novel component is added to the energy and forces similarity between homologous proteins. RESULTS: The combination was tested for two families: pancreatic hormones and homeodomains. The simulated lowest-energy structure of the pancreatic hormones is a reasonable approximation to the native fold. The lowest-energy structure of the homeodomains has 80% of the native contacts, but the helices are not packed correctly. The fourth lowest energy structure of the homeodomains has the correct helix packing (RMS 5.4 A and 82% of the correct contacts). Optimizations of a single protein of the family yield considerably worse structures. CONCLUSIONS: Use of coupled homologous proteins in the search for the native fold is more successful than the folding of a single protein in the family.