RESEARCH ARTICLE
Development of a use Case for Chemical Resource Description Framework for Acquired Immune Deficiency Syndrome Drug Discovery
Talapady Narayana Bhat*, 1, John Barkley2
Article Information
Identifiers and Pagination:
Year: 2008Volume: 2
First Page: 20
Last Page: 27
Publisher ID: TOBIOIJ-2-20
DOI: 10.2174/1875036200802010020
Article History:
Received Date: 07/04/2008Revision Received Date: 23/05/2008
Acceptance Date: 26/05/2008
Electronic publication date: 02/07/2008
Collection year: 2008
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
There is considerable interest in RDF (Resource Description Framework) as a data representation standard for the growing information technology needs of drug discovery. Though several efforts towards this goal have been reported, most of the reported efforts have focused on text-based data. Structural data of chemicals are a key component of drug discovery and molecular images may offer certain advantages over text-based representations for them. Here we discuss the steps that we used to develop and search chemical Resource Description Framework (RDF) using text and image for structures of relevant to Acquired Immune Deficiency Syndrome (AIDS). These steps are (a) acquisition of the data on drugs, (b) definition of the framework to establish RDF on drugs using commonly asked questions during a drug discovery effort, (c) annotation of the structural data on drugs into RDF using the framework established in step (b), (d) validation of the annotation methods using Semantic Web concepts and tools, (e) design and development of public Web to distribute data to the public, (f) generation and distribution of data using OWL (Web Ontology Language). This paper describes this effort, discusses our observations and announces the availability of the OWL model at the W3C Web site (http://esw.w3.org/topic/HCLS/ChemicalTaxonomiesUseCase). The style of this paper is chosen so as to cover a broad audience including structural biologists, medicinal chemists, and information technologists and at times may appear say to the obvious for certain experts. A full discussion of our method and its comparison to other published methods is beyond the scope of this publication.
