Distance-dependent atomic knowledge-based force in protein fold recognition

We have recently introduced a novel model for discriminating the correctly folded proteins from well-designed decoy structures using mechanical interatomic forces. In the model, we considered a protein as a collection of springs and the force imposed to each atom was calculated by using the relation between the potential energy and the force. A mean force potential function is obtained from statistical contact preferences within the known protein structures. In this article, the interatomic forces are calculated by numerical derivation of the potential function. For assessing the knowledge-based force function we consider an optimal structure and define a score function on the 3D structure of a protein. We compare the force imposed to each atom of a protein with the corresponding atom in the optimum structure. Afterwards we assign larger scores to those atoms with the lower forces. The total score is the sum of partial scores of atoms. The optimal structure is assumed to be the one with the highest score in the dataset. Finally, several decoy sets are applied in order to evaluate the performance of our model.