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  • Open Access

Collaborative approaches for Target ID in neglected diseases: identifying new antimalarial targets

  • 1,
  • 2,
  • 3,
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  • 3,
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Malaria Journal201413 (Suppl 1) :P54

https://doi.org/10.1186/1475-2875-13-S1-P54

  • Published:

Keywords

  • Malaria
  • Antimalarial Drug
  • Lead Optimization
  • Global Health Problem
  • Phenotypic Screening

Malaria is a global health problem that causes significant mortality and morbidity, with more than 1 million deaths per year caused by P. falciparum. Most antimalarial drugs face decreased efficacy due to the spread of resistance. Most of the current compounds used for malaria treatment share related mechanisms of action so, there is an urgent need to identify new tractable targets to enable next generation of antimalarial drugs.

The malaria drug discovery community has embraced phenotypic screening approaches as the strategy of choice for the generation of novel chemical starting points for Lead Optimization programs. Determining the mode of action for novel whole cell hits remains a challenge, but new technologies, including genetics, chemoinformatics and proteomics are proving successful.

A chemical proteomics platform aimed at identifying antimalarial targets has been established. This platform is supported by The Bill & Melinda Gates Foundation and encompasses chemical probe synthesis, biological material preparation, pull down experiments and LC-MS protein-lead family characterization for chemical families of interest. Candidate scaffolds to be investigated through this platform are selected based on their biological profile by a join Steering Committee constituted by both GSK and BMGF members.

Authors’ Affiliations

(1)
DDW Malaria DPU GSK, Tres Cantos, Madrid, Spain
(2)
Cellzome GSK, Heidelberg, Germany
(3)
R&D Platform Technology & Science, North Carolina, USA
(4)
The Bill and Melinda Gates Foundation, Seattle, USA

Copyright

© Lafuente et al; licensee BioMed Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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