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Substrate-Driven Mapping of the Degradome by Comparison of Sequence Logos

Sequence logos are frequently used to illustrate substrate preferences and specificity of proteases. Here, we employed the compiled substrates of the MEROPS database to introduce a novel metric for comparison of protease substrate preferences. The constructed similarity matrix of 62 proteases can be...

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Autores principales: Fuchs, Julian E., von Grafenstein, Susanne, Huber, Roland G., Kramer, Christian, Liedl, Klaus R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3828135/
https://www.ncbi.nlm.nih.gov/pubmed/24244149
http://dx.doi.org/10.1371/journal.pcbi.1003353
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author Fuchs, Julian E.
von Grafenstein, Susanne
Huber, Roland G.
Kramer, Christian
Liedl, Klaus R.
author_facet Fuchs, Julian E.
von Grafenstein, Susanne
Huber, Roland G.
Kramer, Christian
Liedl, Klaus R.
author_sort Fuchs, Julian E.
collection PubMed
description Sequence logos are frequently used to illustrate substrate preferences and specificity of proteases. Here, we employed the compiled substrates of the MEROPS database to introduce a novel metric for comparison of protease substrate preferences. The constructed similarity matrix of 62 proteases can be used to intuitively visualize similarities in protease substrate readout via principal component analysis and construction of protease specificity trees. Since our new metric is solely based on substrate data, we can engraft the protease tree including proteolytic enzymes of different evolutionary origin. Thereby, our analyses confirm pronounced overlaps in substrate recognition not only between proteases closely related on sequence basis but also between proteolytic enzymes of different evolutionary origin and catalytic type. To illustrate the applicability of our approach we analyze the distribution of targets of small molecules from the ChEMBL database in our substrate-based protease specificity trees. We observe a striking clustering of annotated targets in tree branches even though these grouped targets do not necessarily share similarity on protein sequence level. This highlights the value and applicability of knowledge acquired from peptide substrates in drug design of small molecules, e.g., for the prediction of off-target effects or drug repurposing. Consequently, our similarity metric allows to map the degradome and its associated drug target network via comparison of known substrate peptides. The substrate-driven view of protein-protein interfaces is not limited to the field of proteases but can be applied to any target class where a sufficient amount of known substrate data is available.
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spelling pubmed-38281352013-11-16 Substrate-Driven Mapping of the Degradome by Comparison of Sequence Logos Fuchs, Julian E. von Grafenstein, Susanne Huber, Roland G. Kramer, Christian Liedl, Klaus R. PLoS Comput Biol Research Article Sequence logos are frequently used to illustrate substrate preferences and specificity of proteases. Here, we employed the compiled substrates of the MEROPS database to introduce a novel metric for comparison of protease substrate preferences. The constructed similarity matrix of 62 proteases can be used to intuitively visualize similarities in protease substrate readout via principal component analysis and construction of protease specificity trees. Since our new metric is solely based on substrate data, we can engraft the protease tree including proteolytic enzymes of different evolutionary origin. Thereby, our analyses confirm pronounced overlaps in substrate recognition not only between proteases closely related on sequence basis but also between proteolytic enzymes of different evolutionary origin and catalytic type. To illustrate the applicability of our approach we analyze the distribution of targets of small molecules from the ChEMBL database in our substrate-based protease specificity trees. We observe a striking clustering of annotated targets in tree branches even though these grouped targets do not necessarily share similarity on protein sequence level. This highlights the value and applicability of knowledge acquired from peptide substrates in drug design of small molecules, e.g., for the prediction of off-target effects or drug repurposing. Consequently, our similarity metric allows to map the degradome and its associated drug target network via comparison of known substrate peptides. The substrate-driven view of protein-protein interfaces is not limited to the field of proteases but can be applied to any target class where a sufficient amount of known substrate data is available. Public Library of Science 2013-11-14 /pmc/articles/PMC3828135/ /pubmed/24244149 http://dx.doi.org/10.1371/journal.pcbi.1003353 Text en © 2013 Fuchs et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Fuchs, Julian E.
von Grafenstein, Susanne
Huber, Roland G.
Kramer, Christian
Liedl, Klaus R.
Substrate-Driven Mapping of the Degradome by Comparison of Sequence Logos
title Substrate-Driven Mapping of the Degradome by Comparison of Sequence Logos
title_full Substrate-Driven Mapping of the Degradome by Comparison of Sequence Logos
title_fullStr Substrate-Driven Mapping of the Degradome by Comparison of Sequence Logos
title_full_unstemmed Substrate-Driven Mapping of the Degradome by Comparison of Sequence Logos
title_short Substrate-Driven Mapping of the Degradome by Comparison of Sequence Logos
title_sort substrate-driven mapping of the degradome by comparison of sequence logos
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3828135/
https://www.ncbi.nlm.nih.gov/pubmed/24244149
http://dx.doi.org/10.1371/journal.pcbi.1003353
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