title: A kernel for open source drug discovery in tropical diseases.
abstract: BACKGROUND
  Conventional patent-based drug development incentives work badly for the developing world, where commercial markets are usually small to non-existent. For this reason, the past decade has seen extensive experimentation with alternative R&D institutions ranging from private-public partnerships to development prizes. Despite extensive discussion, however, one of the most promising avenues-open source drug discovery-has remained elusive. We argue that the stumbling block has been the absence of a critical mass of preexisting work that volunteers can improve through a series of granular contributions. Historically, open source software collaborations have almost never succeeded without such "kernels".
  
  
  RESULTS
  HERE, WE USE A COMPUTATIONAL PIPELINE FOR: (i) comparative structure modeling of target proteins, (ii) predicting the localization of ligand binding sites on their surfaces, and (iii) assessing the similarity of the predicted ligands to known drugs. Our kernel currently contains 143 and 297 protein targets from ten pathogen genomes that are predicted to bind a known drug or a molecule similar to a known drug, respectively. The kernel provides a source of potential drug targets and drug candidates around which an online open source community can nucleate. Using NMR spectroscopy, we have experimentally tested our predictions for two of these targets, confirming one and invalidating the other.
  
  
  CONCLUSIONS
  The TDI kernel, which is being offered under the Creative Commons attribution share-alike license for free and unrestricted use, can be accessed on the World Wide Web at http://www.tropicaldisease.org. We hope that the kernel will facilitate collaborative efforts towards the discovery of new drugs against parasites that cause tropical diseases.
authors.affiliation: Structural Genomics Unit, Bioinformatics and Genomics Department, Centro de Investigación Príncipe Felipe, Valencia, Spain.
authors.forename: Leticia
authors.initials: L
authors.lastname: Ortí
authors.forename: Rodrigo J
authors.initials: RJ
authors.lastname: Carbajo
authors.forename: Ursula
authors.initials: U
authors.lastname: Pieper
authors.forename: Narayanan
authors.initials: N
authors.lastname: Eswar
authors.forename: Stephen M
authors.initials: SM
authors.lastname: Maurer
authors.forename: Arti K
authors.initials: AK
authors.lastname: Rai
authors.forename: Ginger
authors.initials: G
authors.lastname: Taylor
authors.forename: Matthew H
authors.initials: MH
authors.lastname: Todd
authors.forename: Antonio
authors.initials: A
authors.lastname: Pineda-Lucena
authors.forename: Andrej
authors.initials: A
authors.lastname: Sali
authors.forename: Marc A
authors.initials: MA
authors.lastname: Marti-Renom
mesh_terms: D000977:Antiparasitic Agents / Q000737:chemistry* / Q000494:pharmacology*; D003198:Computer Simulation; D055808:Drug Discovery / Q000379:methods*; D006801:Humans; D008958:Models, Molecular; D012984:Software; D014330:Tropical Medicine / Q000379:methods*
chemical_list: D000977:Antiparasitic Agents