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Protease Inhibitors in View of Peptide Substrate Databases
Author(s) -
Birgit J. Waldner,
Julian E. Fuchs,
Michael Schauperl,
Christian Krämer,
Klaus R. Liedl
Publication year - 2016
Publication title -
journal of chemical information and modeling
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.24
H-Index - 160
eISSN - 1549-960X
pISSN - 1549-9596
DOI - 10.1021/acs.jcim.6b00064
Subject(s) - protease , proteases , peptide , database , substrate (aquarium) , virtual screening , chemistry , computer science , computational biology , active site , combinatorial chemistry , biology , enzyme , biochemistry , drug discovery , ecology
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.

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