title: Protease Inhibitors in View of Peptide Substrate Databases.
abstract: Protease substrate profiling has nowadays almost become a routine task for experimentalists, and the knowledge on protease peptide substrates is easily accessible via the MEROPS database. We present a shape-based virtual screening workflow using vROCS that applies the information about the specificity of the proteases to find new small-molecule inhibitors. Peptide substrate sequences for three to four substrate positions of each substrate from the MEROPS database were used to build the training set. Two-dimensional substrate sequences were converted to three-dimensional conformations through mutation of a template peptide substrate. The vROCS query was built from single amino acid queries for each substrate position considering the relative frequencies of the amino acids. The peptide-substrate-based shape-based virtual screening approach gives good performance for the four proteases thrombin, factor Xa, factor VIIa, and caspase-3 with the DUD-E data set. The results show that the method works for protease targets with different specificity profiles as well as for targets with different active-site mechanisms. As no structure of the target and no information on small-molecule inhibitors are required to use our approach, the method has significant advantages in comparison with conventional structure- and ligand-based methods.
authors.affiliation: Institute of General, Inorganic and Theoretical Chemistry, University of Innsbruck , Innrain 82, 6020 Innsbruck, Austria.
authors.forename: Birgit J
authors.initials: BJ
authors.lastname: Waldner
authors.affiliation: Institute of General, Inorganic and Theoretical Chemistry, University of Innsbruck , Innrain 82, 6020 Innsbruck, Austria.
authors.forename: Julian E
authors.initials: JE
authors.lastname: Fuchs
authors.affiliation: Institute of General, Inorganic and Theoretical Chemistry, University of Innsbruck , Innrain 82, 6020 Innsbruck, Austria.
authors.forename: Michael
authors.initials: M
authors.lastname: Schauperl
authors.affiliation: Institute of General, Inorganic and Theoretical Chemistry, University of Innsbruck , Innrain 82, 6020 Innsbruck, Austria.
authors.forename: Christian
authors.initials: C
authors.lastname: Kramer
authors.affiliation: Institute of General, Inorganic and Theoretical Chemistry, University of Innsbruck , Innrain 82, 6020 Innsbruck, Austria.
authors.forename: Klaus R
authors.initials: KR
authors.lastname: Liedl
mesh_terms: D062313:Databases, Pharmaceutical; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D008024:Ligands; D000069550:Machine Learning; D008958:Models, Molecular; D010447:Peptide Hydrolases / Q000737:chemistry / Q000378:metabolism*; D010455:Peptides / Q000378:metabolism*; D011480:Protease Inhibitors / Q000378:metabolism* / Q000494:pharmacology*; D011487:Protein Conformation; D054852:Small Molecule Libraries / Q000378:metabolism / Q000494:pharmacology; D013379:Substrate Specificity; D014584:User-Computer Interface
chemical_list: D008024:Ligands; D010455:Peptides; D011480:Protease Inhibitors; D054852:Small Molecule Libraries; D010447:Peptide Hydrolases