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Genomic-scale prioritization of drug targets: the TDR Targets database


The increasing availability of genomic data for pathogens that cause tropical diseases has created new opportunities for drug discovery and development. However, if the potential of such data is to be fully exploited, the data must be effectively integrated and be easy to interrogate. Here, we discuss the development of the TDR Targets database (, which encompasses extensive genetic, biochemical and pharmacological data related to tropical disease pathogens, as well as computationally predicted druggability for potential targets and compound desirability information. By allowing the integration and weighting of this information, this database aims to facilitate the identification and prioritization of candidate drug targets for pathogens.

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Figure 1: Searching the TDR Targets database.
Figure 2: Ranking of Mycobacterium tuberculosis targets using the TDR Targets database.

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  1. Nwaka, S. & Hudson, A. Innovative lead discovery strategies for tropical diseases. Nature Rev. Drug Discov. 5, 941–955 (2006).

    Article  CAS  Google Scholar 

  2. Heby, O., Persson, L. & Rentala, M. Targeting the polyamine biosynthetic enzymes: a promising approach to therapy of African sleeping sickness, Chagas' disease, and leishmaniasis. Amino Acids 33, 359–366 (2007).

    Article  CAS  Google Scholar 

  3. Mori, M. et al. Contribution of structural biology to clinically validated target proteins. Drug Discov. Today 13, 469–472 (2008).

    Article  CAS  Google Scholar 

  4. Varghese, J. N. Development of neuraminidase inhibitors as anti-influenza virus drugs. Drug Dev. Res. 46, 176–196 (1999).

    Article  CAS  Google Scholar 

  5. Ghedin, E. et al. Draft genome of the filarial nematode parasite Brugia malayi. Science 317, 1756–1760 (2007).

    Article  CAS  Google Scholar 

  6. McAdam, R. A. et al. Characterization of a Mycobacterium tuberculosis H37Rv transposon library reveals insertions in 351 ORFs and mutants with altered virulence. Microbiology 148, 2975–2986 (2002).

    Article  CAS  Google Scholar 

  7. Sassetti, C. M., Boyd, D. H. & Rubin, E. J. Genes required for mycobacterial growth defined by high density mutagenesis. Mol. Microbiol. 48, 77–84 (2003).

    Article  CAS  Google Scholar 

  8. Lamichhane, G. et al. A postgenomic method for predicting essential genes at subsaturation levels of mutagenesis: application to Mycobacterium tuberculosis. Proc. Natl Acad. Sci. USA 100, 7213–7218 (2003).

    Article  CAS  Google Scholar 

  9. McNeil, L. K. et al. The National Microbial Pathogen Database Resource (NMPDR): a genomics platform based on subsystem annotation. Nucleic Acids Res. 35, D347–D353 (2007).

    Article  CAS  Google Scholar 

  10. Chen, F., Mackey, A. J., Vermunt, J. K. & Roos, D. S. Assessing performance of orthology detection strategies applied to eukaryotic genomes. PLoS ONE 2, e383 (2007).

    Article  Google Scholar 

  11. Chen, F., Mackey, A. J., Stoeckert, C. J. Jr & Roos, D. S. OrthoMCL-DB: querying a comprehensive multi-species collection of ortholog groups. Nucleic Acids Res. 34, D363–D368 (2006).

    Article  CAS  Google Scholar 

  12. Overington, J. P., Al-Lazikani, B. & Hopkins, A. L. How many drug targets are there? Nature Rev. Drug Discov. 5, 993–996 (2006).

    Article  CAS  Google Scholar 

  13. Al-Lazikani, B. et al. in Bioinformatics — From Genomes to Therapies. Volume 3: The Holy Grail: Molecular Function (ed. Lengauer, T.) 1315–1334 (Wiley-VCH, Weinheim, 2007).

    Book  Google Scholar 

  14. Winzeler, E. A. et al. Functional characterization of the S. cerevisiae genome by gene deletion and parallel analysis. Science 285, 901–906 (1999).

    Article  CAS  Google Scholar 

  15. Kamath, R. S. et al. Systematic functional analysis of the Caenorhabditis elegans genome using RNAi. Nature 421, 231–237 (2003).

    Article  CAS  Google Scholar 

  16. Gerdes, S. Y. et al. Experimental determination and system level analysis of essential genes in Escherichia coli MG1655. J. Bacteriol. 185, 5673–5684 (2003).

    Article  CAS  Google Scholar 

  17. Titus, R. G., Gueiros-Filho, F. J., de Freitas, L. A. & Beverley, S. M. Development of a safe live Leishmania vaccine line by gene replacement. Proc. Natl Acad. Sci. USA 92, 10267–10271 (1995).

    Article  CAS  Google Scholar 

  18. Chaudhary, K. et al. Purine salvage pathways in the apicomplexan parasite Toxoplasma gondii. J. Biol. Chem. 279, 31221–31227 (2004).

    Article  CAS  Google Scholar 

  19. Hopkins, A. L. & Groom, C. R. The druggable genome. Nature Rev. Drug Discov. 1, 727–730 (2002).

    Article  CAS  Google Scholar 

  20. Pieper, U. et al. MODBASE, a database of annotated comparative protein structure models, and associated resources. Nucleic Acids Res. 32, D217–D222 (2004).

    Article  CAS  Google Scholar 

  21. Paolini, G. V., Shapland, R. H., van Hoorn, W. P., Mason, J. S. & Hopkins, A. L. Global mapping of pharmacological space. Nature Biotech. 24, 805–815 (2006).

    Article  CAS  Google Scholar 

  22. Meissner, M., Breinich, M. S., Gilson, P. R. & Crabb, B. S. Molecular genetic tools in Toxoplasma and Plasmodium: achievements and future needs. Curr. Opin. Microbiol. 10, 349–356 (2007).

    Article  CAS  Google Scholar 

  23. Hasan, S., Daugelat, S., Rao, P. S. & Schreiber, M. Prioritizing genomic drug targets in pathogens: application to Mycobacterium tuberculosis. PLoS Comput. Biol. 2, e61 (2006).

    Article  Google Scholar 

  24. Kumar, S. et al. Mining predicted essential genes of Brugia malayi for nematode drug targets. PLoS ONE 2, e1189 (2007).

    Article  Google Scholar 

  25. Hopkins, A. L., Witty, M. J. & Nwaka, S. Mission possible. Nature 449, 166–169 (2007).

    Article  CAS  Google Scholar 

  26. Montalvetti, A. et al. Farnesyl pyrophosphate synthase is an essential enzyme in Trypanosoma brucei. In vitro RNA interference and in vivo inhibition studies. J. Biol. Chem. 278, 17075–17083 (2003).

    Article  CAS  Google Scholar 

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The authors wish to acknowledge all of the investigators who provided the data in the TDR Targets database including those that participated in the survey on drug targets for Human African Trypanosomiasis (HAT survey) conducted during 2007. We would also like to acknowledge Brandeis University MS students P. Bais and B. Coflan for work on the association of targets with compounds; R. L. Stevens (Argonne National Laboratory) for providing data for gene essentiality in bacteria; K. Chaudhary and T. Carlow (New England BioLabs) for integrated C. elegans phenotype data; J. Sacchetini (Texas A&M) for information on known M. tuberculosis drug targets; and M. Schreiber (Novartis Institute for Tropical Diseases, Singapore) and J. Brown (GlaxoSmithKline) for input on integrating data on persistent expressed genes in dormant-stage M. tuberculosis infection. We would also like to acknowledge essential computational infrastructure and genome annotations made available through the OrthoMCL database (supported by the US National Institutes of Health; NIH); GeneDB (supported by the Wellcome Trust); Ensembl (supported by the European Bioinformatics Institute); and EuPathDB (supported by a Bioinformatics Resource Center contract from the US NIH/National Institute of Allergy and Infectious Diseases). The authors also gratefully acknowledge Pfizer Global Research and Development for sharing data related to druggability. This work was supported by grants from the United Nations Development Programme/World Bank/World Health Organization Special Programme for Research and Training in Tropical Diseases.

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Correspondence to Fernán Agüero, Matthew Berriman, Solomon Nwaka, Stuart A. Ralph, David S. Roos or Wesley C. Van Voorhis.

Supplementary information

Supplementary information S1 (box)

Methods for (PDF 532 kb)

Supplementary information S2 (figure)

Step-by-step example of TDR Targets database search (PDF 1344 kb)

Related links

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Brugia targets ranked by Kumar et al.

EBI Chemigenomics Databases

Medical Structural Genomics of Pathogenic Protozoa


OrthoMCL database

Sigma–Aldrich Enzyme Explorer Assay Library

Structural Genomics Consortium

T. brucei query set (DSR VI/11/07)

TDR Targets database

Tuberculosis target prioritization by Hasan et al.

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Agüero, F., Al-Lazikani, B., Aslett, M. et al. Genomic-scale prioritization of drug targets: the TDR Targets database. Nat Rev Drug Discov 7, 900–907 (2008).

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