The contrasting properties of conservation and correlated phylogeny in protein functional residue prediction

Background: Amino acids responsible for structure, core function or specificity may be inferred from multiple protein sequence alignments where a limited set of residue types are tolerated. The rise in available protein sequences continues to increase the power of techniques based on this principle. Results: A new algorithm, SMERFS, for predicting protein functional sites from multiple sequences alignments was compared to 14 conservation measures and to the MINER algorithm. Validation was performed on an automatically generated dataset of 1457 families derived from the protein interactions database SNAPPI-DB, and a smaller manually curated set of 148 families. The best performing measure overall was Williamson property entropy, with ROC0.1 scores of 0.0087 and 0.0114 for domain and small molecule contact prediction, respectively. The Lancet method performed worse than random on protein-protein interaction site prediction (ROC0.1 score of 0.0008). The SMERFS algorithm gave similar accu...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Jonathan R. Manning, Emily R. Jefferson, Geoffrey J. Barton
• Keywords: BMCBI 2008, MINER Algorithm, Protein Sequences, Williamson Property Entropy