An Algorithm for Simultaneous Backbone Threading and Side-Chain Packing

Abstract

To utilize fully all available information in protein structure prediction, including both backbone and side-chain structures, we present a novel algorithm for solving a generalized threading problem. In this problem we consider simultaneous backbone threading and side-chain packing during the process of a protein structure prediction. For a given query protein sequence and a template structure, our goal is to find a threading alignment between the query sequence and the template structure, along with a rotamer assignment for each side-chain of the query protein, which optimizes an energy function that combines a backbone threading energy and a side-chain packing energy. This highly computationally challenging problem is solved through first formulating this problem as a graph-based optimization problem. Various graph-theoretic techniques are employed to achieve the computational efficiency to make our algorithm practically useful, which takes advantage of a number of special properties of the graph representing this generalized threading problem. The overall framework of our algorithm is a dynamic programming algorithm implemented on an optimal tree decomposition of the graph representation of our problem. By using various additional heuristic techniques such as dead-end elimination, we have demonstrated that our algorithm can solve a generalized threading problem within a practically acceptable amount of time and space, the first of its kind.

Explicit Orientation Dependence in Empirical Potentials and Its Significance to Side-Chain Modeling

“…Main-chain and side-chain states are tightly coupled; if one is not in its native state, neither will the other. Thus, the ultimate way to solve this problem is to refine the main-chain and side-chain simultaneously 43,44. There is another issue of causality between the main-chain and side-chain conformations.…”