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Identification and Validation of Targets of Phenotypic High Throughput Screening

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R41AI108003-01
Agency Tracking Number: R41AI108003
Amount: $255,221.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: NIAID
Solicitation Number: PA12-089
Timeline
Solicitation Year: 2013
Award Year: 2013
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
1633 Bayshore Hwy, Suite 342
BURLINGAME, CA -
United States
DUNS: 149823846
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 SEAN EKINS
 (215) 687-1320
 sekins@collaborativedrug.com
Business Contact
 SEAN EKINS
Phone: (215) 687-1320
Email: sekins@collaborativedrug.com
Research Institution
 SRI INTERNATIONAL
 
333 RAVENSWOOD AVE
MENLO PARK, CA 94025-3493
United States

 () -
 Domestic Nonprofit Research Organization
Abstract

DESCRIPTION (provided by applicant): Identification and Validation of Targets of Phenotypic High Throughput Screening Hits for Chagas Disease Project Summary Nearly 10 million people in Latin America are infected with the eukaryotic parasite Trypanosoma cruzi, the causative agent of Chagas disease. The World Health Organization (WHO) classifies Chagas disease as a neglected tropical disease, but Chagas disease is gaining recognition as an emerging infection in the United States where an estimated 300,000 people may be infected. Unfortunately, there are no FDA approved treatments for Chagas disease and treatments used outside the U.S. have toxic side effects. New therapeutics for Chagas disease are desperately needed. However, few promising drug candidates have advanced to the clinic and the existing drug development pipeline lacks target diversity. In order to facilitate and catalyze the identification of novel therapeutics for Chagas disease, Collaborative Drug Discovery and SRI propose to develop and validate a new combined computational- systems biology approach that predicts metabolic enzyme targets of phenotypic screening hits. The proposed methodology will be developed and validated for Chagas disease (Phase I) and expanded to develop a prototype research tool to support target prediction and validation for phenotypic screening hits from multiple diseases (Phase II). More specifically, in Phase I CDD and SRI will (i) develop a novel approach that using computational methods to identify parasite metabolites structurally mimicked by high throughput screening (HTS) hits and bioinformatics analyses of metabolic pathways to ultimately predict the target of hits, (ii) apply the approach to HTS hits for Chagas disease compiled from over 300,000 compounds tested against T. cruzi in the literature and public HTS datasets compiled in CDD's public database, and (iii) conduct preliminary experiments to validate predicted target-compound pairs. In Phase II, CDD and SRI will conduct more extensive experimental validationof predictions and apply the drug target prediction methodologies to additional neglected tropical diseases to demonstrate the broader utility of the approach. Ultimately, CDD will develop a software module that automates workflow and facilitates sharingof bioinformatics and chemiformatic data between CDD's software platform and external bioinformatics databases such as the SRI BioCyc database. This module is one of a suite of proposed modules addressing aspects of the drug discovery process that will beintegrated and commercialized along with CDD's existing drug discovery software platform. PUBLIC HEALTH RELEVANCE PUBLIC HEALTH RELEVANCE: Nearly 10 million people in Latin America and 300,000 people in the United States are believed to be infected with the eukaryotic parasite Trypanosoma cruzi, the causative agent of Chagas disease; new drugs to treat Chagas disease are desperately needed. In order to identify novel drug targets for Chagas disease and accelerate drug development, Collaborative Drug Discovery (CDD) and SRI propose to develop a computational approach to help scientists predict the drug targets of small molecules that kill the parasite. These methods will eventually be expanded to predict novel drug targets for multiple diseases andserve as the basis for a software module that can be commercialized through CDD's existing drug discovery software.

* Information listed above is at the time of submission. *

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