Finding Correlations in Functionally Equivalent Proteins by Integrating Automated and Visual Data Exploration

Abstract

The analysis of alignments of functionally equivalent proteins can reveal regularities such as correlated positions or residue patterns which are important to ensure a specific fold and various cellular functions. Many approaches are found in the literature which try to identify correlated positions to predict the residues that are close to each other in the three-dimensional folded structure. However, the quality of the predictions remains disappointing. One of the problems is that the statistical correlation measures that were used cannot do justice to the underlying complex biological and physicochemical realities. In this paper we evaluate the biological requirements for a correlation measure and explain why a completely automatic approach is unlikely to succeed. We then propose a novel and flexible criteria for correlation of residue positions in protein sequences, which can be optimized for different requirements. To apply this definition we developed the tool VisAlign that combines an automatic calculation of correlations with an interactive visualization. This allows the user to visually explore alternative alignments and thereby conveniently test various hypothesis and to detect regularities in the aligned sequences