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The BioAssay network and its implications to future therapeutic discovery
BACKGROUND: Despite intense investment growth and technology development, there is an observed bottleneck in drug discovery and development over the past decade. NIH started the Molecular Libraries Initiative (MLI) in 2003 to enlarge the pool for potential drug targets, especially from the “undrugga...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3226251/ https://www.ncbi.nlm.nih.gov/pubmed/21988927 http://dx.doi.org/10.1186/1471-2105-12-S5-S1 |
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author | Zhang, Jintao Lushington, Gerald H Huan, Jun |
author_facet | Zhang, Jintao Lushington, Gerald H Huan, Jun |
author_sort | Zhang, Jintao |
collection | PubMed |
description | BACKGROUND: Despite intense investment growth and technology development, there is an observed bottleneck in drug discovery and development over the past decade. NIH started the Molecular Libraries Initiative (MLI) in 2003 to enlarge the pool for potential drug targets, especially from the “undruggable” part of human genome, and potential drug candidates from much broader types of drug-like small molecules. All results are being made publicly available in a web portal called PubChem. RESULTS: In this paper we construct a network from bioassay data in PubChem, apply network biology concepts to characterize this bioassay network, integrate information from multiple biological databases (e.g. DrugBank, OMIM, and UniHI), and systematically analyze the potential of bioassay targets being new drug targets in the context of complex biological networks. We propose a model to quantitatively prioritize this druggability of bioassay targets, and literature evidence was found to confirm our prioritization of bioassay targets at a roughly 70% accuracy. CONCLUSIONS: Our analysis provide some measures of the value of the MLI data as a resource for both basic chemical biology research and future therapeutic discovery. |
format | Online Article Text |
id | pubmed-3226251 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-32262512011-11-30 The BioAssay network and its implications to future therapeutic discovery Zhang, Jintao Lushington, Gerald H Huan, Jun BMC Bioinformatics Proceedings BACKGROUND: Despite intense investment growth and technology development, there is an observed bottleneck in drug discovery and development over the past decade. NIH started the Molecular Libraries Initiative (MLI) in 2003 to enlarge the pool for potential drug targets, especially from the “undruggable” part of human genome, and potential drug candidates from much broader types of drug-like small molecules. All results are being made publicly available in a web portal called PubChem. RESULTS: In this paper we construct a network from bioassay data in PubChem, apply network biology concepts to characterize this bioassay network, integrate information from multiple biological databases (e.g. DrugBank, OMIM, and UniHI), and systematically analyze the potential of bioassay targets being new drug targets in the context of complex biological networks. We propose a model to quantitatively prioritize this druggability of bioassay targets, and literature evidence was found to confirm our prioritization of bioassay targets at a roughly 70% accuracy. CONCLUSIONS: Our analysis provide some measures of the value of the MLI data as a resource for both basic chemical biology research and future therapeutic discovery. BioMed Central 2011-07-27 /pmc/articles/PMC3226251/ /pubmed/21988927 http://dx.doi.org/10.1186/1471-2105-12-S5-S1 Text en Copyright ©2011 Zhang et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Proceedings Zhang, Jintao Lushington, Gerald H Huan, Jun The BioAssay network and its implications to future therapeutic discovery |
title | The BioAssay network and its implications to future therapeutic discovery |
title_full | The BioAssay network and its implications to future therapeutic discovery |
title_fullStr | The BioAssay network and its implications to future therapeutic discovery |
title_full_unstemmed | The BioAssay network and its implications to future therapeutic discovery |
title_short | The BioAssay network and its implications to future therapeutic discovery |
title_sort | bioassay network and its implications to future therapeutic discovery |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3226251/ https://www.ncbi.nlm.nih.gov/pubmed/21988927 http://dx.doi.org/10.1186/1471-2105-12-S5-S1 |
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