A novel method for identification of local conformational changes in proteins

TL;DR

This paper introduces a new D2 coding method that encodes protein backbone conformations into a 16-letter alphabet, enabling effective identification of local conformational changes and outperforming existing methods in accuracy.

Contribution

The novel D2 coding approach provides an intuitive, clustering-free way to detect local conformational changes in proteins, improving correlation with dihedral angle variations.

Findings

D2 codes better correlate with dihedral angle changes than other methods.

D2 coding accurately captures local conformational changes in HIV-1 protease mutants.

The method reliably distinguishes differences between NMR models of protein mutants.

Abstract

Motivation: Proteins are known to undergo conformational changes in the course of their functions. The changes in conformation are often attributable to a small fraction of residues within the protein. Therefore identification of these variable regions is important for an understanding of protein function. Results: We propose a novel method for identification of local conformational changes in proteins. In our method, backbone conformations are encoded into a sequence of letters from a 16-letter alphabet (called D2 codes) to perform structural comparison. Since we do not use clustering analysis to encode local structures, the D2 codes not only provides a intuitively understandable description of protein structures, but also covers wide varieties of distortions. This paper shows that the D2 codes are better correlated with changes in the dihedral angles than a structural alphabet and a secondary structure description. In the case of the N37S mutant of HIV-1 protease, local conformational changes were captured by the D2 coding method more accurately than other methods. The D2 coding also provided a reliable representation of the difference between NMR models of an HIV-1 protease mutant.