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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical
Society
2016
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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. |
format | Online Article Text |
id | pubmed-4926231 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | American Chemical
Society |
record_format | MEDLINE/PubMed |
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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