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Identifying Unexpected Therapeutic Targets via Chemical-Protein Interactome
Drug medications inevitably affect not only their intended protein targets but also other proteins as well. In this study we examined the hypothesis that drugs that share the same therapeutic effect also share a common therapeutic mechanism by targeting not only known drug targets, but also by inter...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2833192/ https://www.ncbi.nlm.nih.gov/pubmed/20221449 http://dx.doi.org/10.1371/journal.pone.0009568 |
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author | Yang, Lun Chen, Jian Shi, Leming Hudock, Michael P. Wang, Kejian He, Lin |
author_facet | Yang, Lun Chen, Jian Shi, Leming Hudock, Michael P. Wang, Kejian He, Lin |
author_sort | Yang, Lun |
collection | PubMed |
description | Drug medications inevitably affect not only their intended protein targets but also other proteins as well. In this study we examined the hypothesis that drugs that share the same therapeutic effect also share a common therapeutic mechanism by targeting not only known drug targets, but also by interacting unexpectedly on the same cryptic targets. By constructing and mining an Alzheimer's disease (AD) drug-oriented chemical-protein interactome (CPI) using a matrix of 10 drug molecules known to treat AD towards 401 human protein pockets, we found that such cryptic targets exist. We recovered from CPI the only validated therapeutic target of AD, acetylcholinesterase (ACHE), and highlighted several other putative targets. For example, we discovered that estrogen receptor (ER) and histone deacetylase (HDAC), which have recently been identified as two new therapeutic targets of AD, might already have been targeted by the marketed AD drugs. We further established that the CPI profile of a drug can reflect its interacting character towards multi-protein sets, and that drugs with the same therapeutic attribute will share a similar interacting profile. These findings indicate that the CPI could represent the landscape of chemical-protein interactions and uncover “behind-the-scenes” aspects of the therapeutic mechanisms of existing drugs, providing testable hypotheses of the key nodes for network pharmacology or brand new drug targets for one-target pharmacology paradigm. |
format | Text |
id | pubmed-2833192 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-28331922010-03-11 Identifying Unexpected Therapeutic Targets via Chemical-Protein Interactome Yang, Lun Chen, Jian Shi, Leming Hudock, Michael P. Wang, Kejian He, Lin PLoS One Research Article Drug medications inevitably affect not only their intended protein targets but also other proteins as well. In this study we examined the hypothesis that drugs that share the same therapeutic effect also share a common therapeutic mechanism by targeting not only known drug targets, but also by interacting unexpectedly on the same cryptic targets. By constructing and mining an Alzheimer's disease (AD) drug-oriented chemical-protein interactome (CPI) using a matrix of 10 drug molecules known to treat AD towards 401 human protein pockets, we found that such cryptic targets exist. We recovered from CPI the only validated therapeutic target of AD, acetylcholinesterase (ACHE), and highlighted several other putative targets. For example, we discovered that estrogen receptor (ER) and histone deacetylase (HDAC), which have recently been identified as two new therapeutic targets of AD, might already have been targeted by the marketed AD drugs. We further established that the CPI profile of a drug can reflect its interacting character towards multi-protein sets, and that drugs with the same therapeutic attribute will share a similar interacting profile. These findings indicate that the CPI could represent the landscape of chemical-protein interactions and uncover “behind-the-scenes” aspects of the therapeutic mechanisms of existing drugs, providing testable hypotheses of the key nodes for network pharmacology or brand new drug targets for one-target pharmacology paradigm. Public Library of Science 2010-03-08 /pmc/articles/PMC2833192/ /pubmed/20221449 http://dx.doi.org/10.1371/journal.pone.0009568 Text en Yang 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 Yang, Lun Chen, Jian Shi, Leming Hudock, Michael P. Wang, Kejian He, Lin Identifying Unexpected Therapeutic Targets via Chemical-Protein Interactome |
title | Identifying Unexpected Therapeutic Targets via Chemical-Protein Interactome |
title_full | Identifying Unexpected Therapeutic Targets via Chemical-Protein Interactome |
title_fullStr | Identifying Unexpected Therapeutic Targets via Chemical-Protein Interactome |
title_full_unstemmed | Identifying Unexpected Therapeutic Targets via Chemical-Protein Interactome |
title_short | Identifying Unexpected Therapeutic Targets via Chemical-Protein Interactome |
title_sort | identifying unexpected therapeutic targets via chemical-protein interactome |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2833192/ https://www.ncbi.nlm.nih.gov/pubmed/20221449 http://dx.doi.org/10.1371/journal.pone.0009568 |
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