@article {19381286,
	title = {A kernel for open source drug discovery in tropical diseases},
	journal = {PLoS Negl Trop Dis},
	volume = {3},
	number = {4},
	year = {2009},
	note = {Orti, Leticia Carbajo, Rodrigo J Pieper, Ursula Eswar, Narayanan Maurer, Stephen M Rai, Arti K Taylor, Ginger Todd, Matthew H Pineda-Lucena, Antonio Sali, Andrej Marti-Renom, Marc A United States PLoS neglected tropical diseases PLoS Negl Trop Dis. 2009;3(4):e418. Epub 2009 Apr 21.},
	pages = {e418},
	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". METHODOLOGY/PRINCIPAL FINDINGS: 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/SIGNIFICANCE: 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.},
	url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=19381286},
	author = {Orti, L. and Carbajo, R. J. and Pieper, U. and Eswar, N. and Maurer, S. M. and Rai, A. K. and Taylor, G. and Todd, M. H. and Pineda-Lucena, A. and Sali, A. and M. A. Marti-Renom}
}
@article {19352362,
	title = {A kernel for the Tropical Disease Initiative},
	journal = {Nat Biotechnol},
	volume = {27},
	number = {4},
	year = {2009},
	note = {<p>Orti, Leticia Carbajo, Rodrigo J Pieper, Ursula Eswar, Narayanan Maurer, Stephen M Rai, Arti K Taylor, Ginger Todd, Matthew H Pineda-Lucena, Antonio Sali, Andrej Marti-Renom, Marc A P01 AI035707/AI/NIAID NIH HHS/United States P01 GM71790/GM/NIGMS NIH HHS/United States R01 GM54762/GM/NIGMS NIH HHS/United States U54 GM074945/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov{\textquoteright}t United States Nature biotechnology Nat Biotechnol. 2009 Apr;27(4):320-1.</p>},
	pages = {320-1},
	url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=19352362},
	author = {Orti, L. and Carbajo, R. J. and Pieper, U. and Eswar, N. and Maurer, S. M. and Rai, A. K. and Taylor, G. and Todd, M. H. and Pineda-Lucena, A. and Sali, A. and M. A. Marti-Renom}
}
@article {16584746,
	title = {Selective pressures at a codon-level predict deleterious mutations in human disease genes},
	journal = {J Mol Biol},
	volume = {358},
	number = {5},
	year = {2006},
	note = {Arbiza, Leonardo Duchi, Serena Montaner, David Burguet, Jordi Pantoja-Uceda, David Pineda-Lucena, Antonio Dopazo, Joaquin Dopazo, Hernan Research Support, Non-U.S. Gov{\textquoteright}t England Journal of molecular biology J Mol Biol. 2006 May 19;358(5):1390-404. Epub 2006 Mar 15.},
	pages = {1390-404},
	abstract = {Deleterious mutations affecting biological function of proteins are constantly being rejected by purifying selection from the gene pool. The non-synonymous/synonymous substitution rate ratio (omega) is a measure of selective pressure on amino acid replacement mutations for protein-coding genes. Different methods have been developed in order to predict non-synonymous changes affecting gene function. However, none has considered the estimation of selective constraints acting on protein residues. Here, we have used codon-based maximum likelihood models in order to estimate the selective pressures on the individual amino acid residues of a well-known model protein: p53. We demonstrate that the number of residues under strong purifying selection in p53 is much higher than those that are strictly conserved during the evolution of the species. In agreement with theoretical expectations, residues that have been noted to be of structural relevance, or in direct association with DNA, were among those showing the highest signals of purifying selection. Conversely, those changing according to a neutral, or nearly neutral mode of evolution, were observed to be irrelevant for protein function. Finally, using more than 40 human disease genes, we demonstrate that residues evolving under strong selective pressures (omega<0.1) are significantly associated (p<0.01) with human disease. We hypothesize that non-synonymous change on amino acids showing omega<0.1 will most likely affect protein function. The application of this evolutionary prediction at a genomic scale will provide an a priori hypothesis of the phenotypic effect of non-synonymous coding single nucleotide polymorphisms (SNPs) in the human genome.},
	keywords = {Amino Acid Sequence Amino Acid Substitution Codon/*genetics Databases, Genetic Evolution, Genetic Models, Human Humans Models, Inborn/*genetics Genome, Molecular Genes, Molecular Molecular Sequence Data *Mutation Neoplasms/genetics Proteins/genetics *Selection (Genetics) Tumor Suppressor Protein p53/chemistry/genetics, p53 Genetic Diseases},
	url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=16584746},
	author = {Arbiza, L. and Duchi, S. and Montaner, D. and Burguet, J. and Pantoja-Uceda, D. and Pineda-Lucena, A. and Dopazo, J. and H. Dopazo}
}
