title: Evaluating CASP4 predictions with physical energy functions.
abstract: Physical energy scoring functions based on implicit solvation models are tested by evaluating predictions from the most recent CASP4 competition. The best performing scoring functions are identified along with the best protocol for preparing structures before energies are evaluated. Ranking of structures with the best scoring functions is compared across CASP4 targets to establish when physical scoring functions can be expected to reliably distinguish structures that are most similar to the native fold in a set of misfolded or unfolded protein conformations. The results are used to interpret previous studies where scoring functions were tested on the standard decoy sets by Park, Levitt, and Baker. We show that the best physical scoring functions can be applied successfully in automated consensus scoring applications where a single best conformation has to be selected from a set of structures from different sources. Finally, the potential for better protein structure scoring functions is discussed with a suggestion for an empirically parameterized linear combination of energy components.
authors.affiliation: Department of Molecular Biology, TPC6, The Scripps Research Institute, La Jolla, California 92037, USA.
authors.forename: Michael
authors.initials: M
authors.lastname: Feig
authors.forename: Charles L
authors.initials: CL
authors.lastname: Brooks
mesh_terms: D000818:Animals; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D020539:Sequence Analysis, Protein / Q000379:methods*; D012997:Solvents / Q000737:chemistry
chemical_list: D011506:Proteins; D012997:Solvents