title: Cutoff lensing: predicting catalytic sites in enzymes.
abstract: Predicting function-related amino acids in proteins with unknown function or unknown allosteric binding sites in drug-targeted proteins is a task of paramount importance in molecular biomedicine. In this paper we introduce a simple, light and computationally inexpensive structure-based method to identify catalytic sites in enzymes. Our method, termed cutoff lensing, is a general procedure consisting in letting the cutoff used to build an elastic network model increase to large values. A validation of our method against a large database of annotated enzymes shows that optimal values of the cutoff exist such that three different structure-based indicators allow one to recover a maximum of the known catalytic sites. Interestingly, we find that the larger the structures the greater the predictive power afforded by our method. Possible ways to combine the three indicators into a single figure of merit and into a specific sequential analysis are suggested and discussed with reference to the classic case of HIV-protease. Our method could be used as a complement to other sequence- and/or structure-based methods to narrow the results of large-scale screenings.
authors.affiliation: Université d'Orléans, Centre de Biophysique Moléculaire, CNRS-UPR4301, Rue C. Sadron, 45071, Orléans, France.
authors.forename: Simon
authors.initials: S
authors.lastname: Aubailly
authors.affiliation: Université d'Orléans, Centre de Biophysique Moléculaire, CNRS-UPR4301, Rue C. Sadron, 45071, Orléans, France.
authors.forename: Francesco
authors.initials: F
authors.lastname: Piazza
mesh_terms: D000495:Allosteric Site; D000579:Amidinotransferases / Q000737:chemistry*; D000596:Amino Acids / Q000737:chemistry*; D001122:Arginine Kinase / Q000737:chemistry*; D020134:Catalytic Domain; D003198:Computer Simulation; D030562:Databases, Protein; D016333:HIV Protease / Q000737:chemistry*; D015497:HIV-1 / Q000737:chemistry; D006801:Humans; D015233:Models, Statistical
chemical_list: D000596:Amino Acids; D000579:Amidinotransferases; C020681:glycine amidinotransferase; D001122:Arginine Kinase; D016333:HIV Protease