Using information theory to search for co-evolving residues in proteins

• Published in: Bioinformatics Vol. 21; no. 22; pp. 4116 - 4124
• Main Authors: Martin, L. C., Gloor, G. B., Dunn, S. D., Wahl, L. M.
• Format: Journal Article
• Language: English
• Published: Oxford Oxford University Press 15.11.2005; Oxford Publishing Limited (England)
• Subjects: Amino Acid Sequence; Biological and medical sciences; Computational Biology - methods; Computer Simulation; Databases, Genetic; Databases, Protein; Evolution, Molecular; Fundamental and applied biological sciences. Psychology; General aspects; Genetic Linkage; Information Theory; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects); Models, Statistical; Models, Theoretical; Molecular Sequence Data; Mutation; Phylogeny; Protein Folding; Proteins - chemistry; Sensitivity and Specificity; Sequence Alignment; Sequence Analysis, Protein; Triose-Phosphate Isomerase - chemistry; Original document; Computer program; Residue; Sequence alignment; Standardization; Mutation; Phylogeny; Coevolution; Web site; Bioinformatics; Protein; Information theory
• ISSN: 1367-4803; 1460-2059; 1367-4811
• DOI: 10.1093/bioinformatics/bti671

Motivation: Some functionally important protein residues are easily detected since they correspond to conserved columns in a multiple sequence alignment (MSA). However important residues may also mutate, with compensatory mutations occurring elsewhere in the protein, which serve to preserve or restore functionality. It is difficult to distinguish these co-evolving sites from other non-conserved sites. Results: We used Mutual Information (MI) to identify co-evolving positions. Using in silico evolved MSAs, we examined the effects of the number of sequences, the size of amino acid alphabet and the mutation rate on two sources of background MI: finite sample size effects and phylogenetic influence. We then assessed the performance of various normalizations of MI in enhancing detection of co-evolving positions and found that normalization by the pair entropy was optimal. Real protein alignments were analyzed and co-evolving isolated pairs were often found to be in contact with each other. Availability: All data and program files can be found at Contact: lwahl@uwo.ca Supplementary information: