Identification of novel therapeutics for tuberculosis combining cheminformatics,

Ekins, Sean

Abstract

This Small Business Technology Transfer Phase I project entitled """"""""Identification of novel therapeutics for tuberculosis combining cheminformatics, diverse databases and logic-based pathway analysis"""""""" describes the development of software that will facilitate new drug discovery efforts for Mycobacterium tuberculosis (TB). The amount of research performed on TB compared with other known pharmaceutical targets (cancer, heart disease, diabetes etc.) is limited primarily to disparate academic groups and small groups in big drug companies. There is no repository of global knowledge on TB that could assist in drug development efforts. We propose to develop a prototype system to facilitate new drug discovery efforts for TB using novel logical inference techniques developed by scientists at SRI International, which would be linked with knowledge which has been assembled by the curation of diverse biological data types and computational prediction by Collaborative Drug Discovery (CDD). This tool will be used to aid the Identification of novel therapeutics for Tuberculosis by combining cheminformatics, diverse databases and logic-based pathway analysis. It will represent a synergistic computational tool for hypotheses testing, knowledge sharing, data archiving, data mining and drug discovery. We expect a combined product would have considerable impact on TB research enabling further experimental validation of hypotheses in phase II. As TB is one of the world's deadliest diseases the value of our proposal would be high. The societal impact would be the ability to mine the deposited data, search for new potential targets and lead molecules and bring the data and researchers to a single centralized location.

Public Health Relevance

We propose to develop a prototype system to facilitate new drug discovery efforts for TB using novel logical inference techniques developed by scientists at SRI International, which would be linked with knowledge which has been assembled by the curation of diverse biological data types and computational prediction by Collaborative Drug Discovery (CDD). This tool will be used to aid the Identification of Novel Therapeutics for Tuberculosis by combining Cheminformatics, Diverse Databases and Logic-based Pathway Analysis. It will represent a synergistic computational tool for hypotheses testing, knowledge sharing, data archiving, data mining and drug discovery.