A finding maximal clique algorithm for predicting loop of protein structure

In this paper we equate the problem of predicting the loop 3D structure in the comparative modeling to a problem of finding the maximal clique with the best weight. Each possible conformation of a residue in a loop sequence is represented as a node in a graph. Edges are then drawn between pairs of nodes that are consistent with each other. Edge and nodes are weighted according to some fixed criteria. Once the entire graph is constructed, all the maximal sets of cliques are found using an algorithm of artificial neural network models. The cliques with the best weights represent the optimal conformation of the region of loop sequence.