Limits...
A kernel for open source drug discovery in tropical diseases.

Ortí L, Carbajo RJ, Pieper U, Eswar N, Maurer SM, Rai AK, Taylor G, Todd MH, Pineda-Lucena A, Sali A, Marti-Renom MA - PLoS Negl Trop Dis (2009)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Structural Genomics Unit, Bioinformatics and Genomics Department, Centro de Investigación Príncipe Felipe, Valencia, Spain.

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.

Show MeSH

Related in: MedlinePlus

Examples of known antiprotozoal drugs detected by our method.(A) Trimethoprim drug predicted to bind M. leprae dihydrofolate reductase (UniProt identifier Q9CBW1). (B) Vorinostat drug predicted to bind L. major histone deacetylase (UniProt identifier Q4QCE7). The original PDB structure with the ligand bound is shown in blue; the transferred binding site in the template structure is shown in green; and a comparative protein structure model of the target sequence is shown in magenta.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC2667270&req=5

pntd-0000418-g003: Examples of known antiprotozoal drugs detected by our method.(A) Trimethoprim drug predicted to bind M. leprae dihydrofolate reductase (UniProt identifier Q9CBW1). (B) Vorinostat drug predicted to bind L. major histone deacetylase (UniProt identifier Q4QCE7). The original PDB structure with the ligand bound is shown in blue; the transferred binding site in the template structure is shown in green; and a comparative protein structure model of the target sequence is shown in magenta.

Mentions: Our pipeline correctly predicted that the known antiprotozoal drug Trimethoprim (DrugBank identifier DB00440) interacts with a dihydrofolate reductase (UniProt identifier A1QV37) in Mycobacterium tuberculosis. Trimethoprim is a pyrimidine-like inhibitor of dihydrofolate reductases that acts as an antibacterial agent and has weak antimalaria activity [57]. Moreover, our predictions suggest that Trimethoprim might also inhibit a dihydrofolate reductase from M. leprae (UniProt identifier Q9CBW1), given that its binding site is 93.3% identical in sequence to that of dihydrofolate reductase from M. tuberculosis (Figure 3A).


A kernel for open source drug discovery in tropical diseases.

Ortí L, Carbajo RJ, Pieper U, Eswar N, Maurer SM, Rai AK, Taylor G, Todd MH, Pineda-Lucena A, Sali A, Marti-Renom MA - PLoS Negl Trop Dis (2009)

Examples of known antiprotozoal drugs detected by our method.(A) Trimethoprim drug predicted to bind M. leprae dihydrofolate reductase (UniProt identifier Q9CBW1). (B) Vorinostat drug predicted to bind L. major histone deacetylase (UniProt identifier Q4QCE7). The original PDB structure with the ligand bound is shown in blue; the transferred binding site in the template structure is shown in green; and a comparative protein structure model of the target sequence is shown in magenta.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2667270&req=5

pntd-0000418-g003: Examples of known antiprotozoal drugs detected by our method.(A) Trimethoprim drug predicted to bind M. leprae dihydrofolate reductase (UniProt identifier Q9CBW1). (B) Vorinostat drug predicted to bind L. major histone deacetylase (UniProt identifier Q4QCE7). The original PDB structure with the ligand bound is shown in blue; the transferred binding site in the template structure is shown in green; and a comparative protein structure model of the target sequence is shown in magenta.
Mentions: Our pipeline correctly predicted that the known antiprotozoal drug Trimethoprim (DrugBank identifier DB00440) interacts with a dihydrofolate reductase (UniProt identifier A1QV37) in Mycobacterium tuberculosis. Trimethoprim is a pyrimidine-like inhibitor of dihydrofolate reductases that acts as an antibacterial agent and has weak antimalaria activity [57]. Moreover, our predictions suggest that Trimethoprim might also inhibit a dihydrofolate reductase from M. leprae (UniProt identifier Q9CBW1), given that its binding site is 93.3% identical in sequence to that of dihydrofolate reductase from M. tuberculosis (Figure 3A).

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Structural Genomics Unit, Bioinformatics and Genomics Department, Centro de Investigación Príncipe Felipe, Valencia, Spain.

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.

Show MeSH
Related in: MedlinePlus