Protein three-dimensional structure generation with an empirical hydrophobic penalty function.
Given current computational environments, it is worthwhile to establish amino acid residue-level functions which approximate protein folds quite well. Such functions must be the interim steps toward protein three-dimensional structure prediction. I have shown that an empirical hydrophobic penalty function of protein, derived from the number of residues in a sphere around each residue, could be utilized to distinguish the correctly folded structure from the incorrect ones. In order to assess the predictive power of the penalty function, I have generated conformations by randomly changing main chain dihedral angles, and applied the penalty function to them. If only a local region was allowed to change its conformation, native-like structures could be generated within a reasonable computational time. In global simulations, however, a considerable number of nonnative conformations, which gave as small a penalty value as that of the native protein, were found. Although some of the conformations were compact and globular, they were quite different from the native structure in that they lacked most of the secondary structures. This result shows that the penalty function alone cannot define the native structure, and that substructure information may help the penalty function to reach the correctly folded structure.
Toma
K
K
Computer Science Department, Asahi Chemical Industry Co. Ltd., Shizuoka, Japan.
D000465:Algorithms; D055598:Chemical Phenomena; D002627:Chemistry, Physical; D003198:Computer Simulation; D008958:Models, Molecular; D011487:Protein Conformation