Structural clusters of evolutionary trace residues are statistically significant and common in proteins.

摘要: Given the massive increase in number of new sequences and structures, a critical problem is how to integrate these raw data into meaningful biological information. One approach, Evolutionary Trace, or ET, uses phylogenetic information rank residues protein sequence by evolutionary importance then maps those ranked at top onto representative structure. If form structural clusters, they can identify functional surfaces such as involved molecular recognition. Now that examples have shown ET binding sites focus mutational studies on their relevant determinants, we ask whether method be improved so applicable large scale. To address this question, introduce treatment gaps resulting from insertions deletions, which streamlines selection used input. We also objective statistics assess significance total clusters size largest one. As result novel gaps, performance improves measurably. find evolutionarily privileged are significant 5% level 45 out 46 (98%) proteins drawn variety classes functions. In 37 38 for protein-ligand complex available, dominant cluster contacts ligand. conclude spatial clustering important general phenomenon, consistent with cooperative nature determine structure function. practice, results suggest applied scale fraction structures databank (PDB). This approach combining obtain detailed insights basis function should prove valuable context Structural Genomics Initiative.