Exploring peptide energy landscapes: a test of force fields and implicit solvent models.
A biased Monte Carlo-minimization/annealing conformational search was used to characterize five descriptions of the energy landscape for each of three model systems: the 20-residue "trp-cage" miniprotein, the 20-residue "BS1" peptide, and the 17-residue "U(1-17)T9D" peptide. The EEF1 and SASA energy landscapes were studied as well as those defined by using the GB/ACE implicit water model with one of three protein force fields: CHARMM19, CHARMM22, and CHARMM22/CMAP. The lowest-energy structures of the trp-cage and BS1 peptides found for the EEF1 landscape have main-chain root-mean-square deviations (rmsds) from the respective NMR structures of less than 2 A; for U(1-17)T9D, the deviation is less than 3 A using EEF1. The main-chain rmsd of the minimum-energy trp-cage conformation obtained for the GB/ACE/CHARMM22/CMAP landscape is less than 1 A. However, this energy function strongly favored helical structures for the two peptides shown by NMR to form beta-sheet structures. Brief annealing of the system following main-chain conformational changes was found to enhance the exploration of low-energy states. The thousands of simulations reported here suggest that the prediction of protein structure might be improved by the simultaneous use of a CMAP-like description of the main chain and an EEF1-like description of the solvent.
Steinbach
Peter J
PJ
Center for Molecular Modeling, National Institutes of Health, DHHS, Bethesda, Maryland 20892-5624, USA. steinbac@helix.nih.gov
D003198:Computer Simulation; D008956:Models, Chemical; D009010:Monte Carlo Method; D010455:Peptides / Q000032:analysis / Q000737:chemistry*; D011487:Protein Conformation; D012997:Solvents / Q000737:chemistry
D010455:Peptides; D012997:Solvents