Probability Grid Monte Carlo provides a new method for predicting all-atom protein conformations from C coordinates. Most of the previous methods  use database searches to find conformations for several consecutive residues which match the configuration of the C coordinates being used as a template. The PGMC method, in contrast, uses probabilities for individual residues to guide Monte Carlo searches. The method produces results as good as or better than the previously published methods for the protein flavodoxin. In general, backbone conformations are modeled accurately to within 0.6 Å rms deviation from the crystal structure. Most of the error comes at the C-terminal ends and in turns, while the extended secondary structures, helices and sheets are modeled much better, with a typical rms deviation of 0.3 Å or better. Sidechain conformations are not modeled as accurately. Sidechain rms deviations over 2.0 Å can be expected for large proteins where the computational cost of optimizing all sidechains concurrently is very large. The sidechain deviation for the small protein crambin was much better, averaging 1.87 Å for 25 models. Overall rms deviations are typically better than 2.0 Å, and depend primarily upon the amount of time spent optimizing the sidechain conformations.
The PGMC C Builder is an extremely fast, automatic method. For proteins the size of crambin, both the backbone and sidechain can be modeled accurately in less than 20 minutes on a standard workstation. This may enable the method to be used for evaluating numerous possible C conformations, such as those generated from a lattice-base protein folding simulation. To this end, a simple C forcefield has been developed which enables lattice conformations to be smoothed, thereby providing a template for the C Builder.