Author:
Zhang Jintao,Lushington Gerald H,Huan Jun
Abstract
Abstract
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.
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology
Cited by
17 articles.
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