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Protease Inhibitors in View of Peptide Substrate Databases

[Image: see text] 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 a...

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Autores principales: Waldner, Birgit J., Fuchs, Julian E., Schauperl, Michael, Kramer, Christian, Liedl, Klaus R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2016
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4926231/
https://www.ncbi.nlm.nih.gov/pubmed/27247997
http://dx.doi.org/10.1021/acs.jcim.6b00064
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author Waldner, Birgit J.
Fuchs, Julian E.
Schauperl, Michael
Kramer, Christian
Liedl, Klaus R.
author_facet Waldner, Birgit J.
Fuchs, Julian E.
Schauperl, Michael
Kramer, Christian
Liedl, Klaus R.
author_sort Waldner, Birgit J.
collection PubMed
description [Image: see text] 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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spelling pubmed-49262312016-07-01 Protease Inhibitors in View of Peptide Substrate Databases Waldner, Birgit J. Fuchs, Julian E. Schauperl, Michael Kramer, Christian Liedl, Klaus R. J Chem Inf Model [Image: see text] 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. American Chemical Society 2016-06-01 2016-06-27 /pmc/articles/PMC4926231/ /pubmed/27247997 http://dx.doi.org/10.1021/acs.jcim.6b00064 Text en Copyright © 2016 American Chemical Society This is an open access article published under a Creative Commons Attribution (CC-BY) License (http://pubs.acs.org/page/policy/authorchoice_ccby_termsofuse.html) , which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.
spellingShingle Waldner, Birgit J.
Fuchs, Julian E.
Schauperl, Michael
Kramer, Christian
Liedl, Klaus R.
Protease Inhibitors in View of Peptide Substrate Databases
title Protease Inhibitors in View of Peptide Substrate Databases
title_full Protease Inhibitors in View of Peptide Substrate Databases
title_fullStr Protease Inhibitors in View of Peptide Substrate Databases
title_full_unstemmed Protease Inhibitors in View of Peptide Substrate Databases
title_short Protease Inhibitors in View of Peptide Substrate Databases
title_sort protease inhibitors in view of peptide substrate databases
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4926231/
https://www.ncbi.nlm.nih.gov/pubmed/27247997
http://dx.doi.org/10.1021/acs.jcim.6b00064
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