Looking at enzymes from the inside out: the proximity of catalytic residues to the molecular centroid can be used for detection of active sites and enzyme-ligand interfaces.
Analysis of the distances of the exposed residues in 175 enzymes from the centroids of the molecules indicates that catalytic residues are very often found among the 5% of residues closest to the enzyme centroid. This property of catalytic residues is implemented in a new prediction algorithm (named EnSite) for locating the active sites of enzymes and in a new scheme for re-ranking enzyme-ligand docking solutions. EnSite examines only 5% of the molecular surface (represented by surface dots) that is closest to the centroid, identifying continuous surface segments and ranking them by their area size. EnSite ranks the correct prediction 1-4 in 97% of the cases in a dataset of 65 monomeric enzymes (rank 1 for 89% of the cases) and in 86% of the cases in a dataset of 176 monomeric and multimeric enzymes from all six top-level enzyme classifications (rank 1 in 74% of the cases). Importantly, identification of buried or flat active sites is straightforward because EnSite "looks" at the molecular surface from the inside out. Detailed examination of the results indicates that the proximity of the catalytic residues to the centroid is a property of the functional unit, defined as the assembly of domains or chains that form the active site (in most cases the functional unit corresponds to a single whole polypeptide chain). Using the functional unit in the prediction further improves the results. The new property of active sites is also used for re-evaluating enzyme-inhibitor unbound docking results. Sorting the docking solutions by the distance of the interface to the centroid of the enzyme improves remarkably the ranks of nearly correct solutions compared to ranks based on geometric-electrostatic-hydrophobic complementarity scores.
Ben-Shimon
Avraham
A
Department of Biological Chemistry, Weizmann Institute of Science, Rehovot 76100, Israel.
Eisenstein
Miriam
M
D000465:Algorithms; D001426:Bacterial Proteins / Q000737:chemistry; D001665:Binding Sites; D002384:Catalysis; D020134:Catalytic Domain; D016000:Cluster Analysis; D019992:Databases as Topic; D030562:Databases, Protein; D004798:Enzymes / Q000737:chemistry*; D008024:Ligands; D008958:Models, Molecular; D011485:Protein Binding; D011487:Protein Conformation; D015202:Protein Engineering; D017434:Protein Structure, Tertiary; D040901:Proteomics / Q000379:methods; D012997:Solvents; D055672:Static Electricity
D001426:Bacterial Proteins; D004798:Enzymes; D008024:Ligands; D012997:Solvents