Building proteins from C alpha coordinates using the dihedral probability grid Monte Carlo method.
Dihedral probability grid Monte Carlo (DPG-MC) is a general-purpose method of conformational sampling that can be applied to many problems in peptide and protein modeling. Here we present the DPG-MC method and apply it to predicting complete protein structures from C alpha coordinates. This is useful in such endeavors as homology modeling, protein structure prediction from lattice simulations, or fitting protein structures to X-ray crystallographic data. It also serves as an example of how DPG-MC can be applied to systems with geometric constraints. The conformational propensities for individual residues are used to guide conformational searches as the protein is built from the amino-terminus to the carboxyl-terminus. Results for a number of proteins show that both the backbone and side chain can be accurately modeled using DPG-MC. Backbone atoms are generally predicted with RMS errors of about 0.5 A (compared to X-ray crystal structure coordinates) and all atoms are predicted to an RMS error of 1.7 A or better.
Mathiowetz
A M
AM
Materials and Molecular Simulation Center, Beckman Institute (139-74), California Institute of Technology, Pasadena 91125, USA.
Goddard
W A
WA
D000596:Amino Acids / Q000737:chemistry; D003198:Computer Simulation; D018360:Crystallography, X-Ray; D016208:Databases, Factual; D008432:Mathematical Computing; D008958:Models, Molecular; D009010:Monte Carlo Method; D010940:Plant Proteins / Q000737:chemistry; D011336:Probability; D011487:Protein Conformation; D017433:Protein Structure, Secondary
D000596:Amino Acids; D010940:Plant Proteins; C024934:crambin protein, Crambe abyssinica