Analogy-based protein structure prediction: III. Optimizing the combination of the substitution matrix and pseudopotentials used to align protein sequences with spatial structures

Abstract

A general and fast method for maximizing the “recognition ability” of a linear combination of an arbitrary number of various methods used to recognize protein structures and produce sequence-to-structure alignments for the structurally analogous proteins is described. It is shown that, at a low level of sequence similarity, the optimal combination of methods displays a significantly higher recognition ability than each method alone; the leading role in this combination is played by (1) pseudopotentials of long-range interactions, (2) matrices of secondary structure similarity, and (3) amino acid substitution matrices. In the case of a high sequence similarity, substitution matrices play the leading and practically the sole role in the optimal combination, although the addition of pseudopotentials of long-range interactions and matrices of secondary structure similarity somewhat increases the recognition ability of the combined method.