Thousands of chemical starting points for antimalarial lead identification


Malaria is a devastating infection caused by protozoa of the genus Plasmodium. Drug resistance is widespread, no new chemical class of antimalarials has been introduced into clinical practice since 1996 and there is a recent rise of parasite strains with reduced sensitivity to the newest drugs. We screened nearly 2 million compounds in GlaxoSmithKline’s chemical library for inhibitors of P. falciparum, of which 13,533 were confirmed to inhibit parasite growth by at least 80% at 2 µM concentration. More than 8,000 also showed potent activity against the multidrug resistant strain Dd2. Most (82%) compounds originate from internal company projects and are new to the malaria community. Analyses using historic assay data suggest several novel mechanisms of antimalarial action, such as inhibition of protein kinases and host–pathogen interaction related targets. Chemical structures and associated data are hereby made public to encourage additional drug lead identification efforts and further research into this disease.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1: Three-dimensional plot of some of the novel chemical diversity present in TCAMS.
Figure 2: Description of TCAMS and its target space.
Figure 3: Phylogenetic tree of combined human and P. falciparum kinomes.


  1. 1

    World Health Organization. World malaria report. 〈〉 (2009)

  2. 2

    Anstey, N. M., Russell, B., Yeo, T. W. & Price, R. N. The pathophysiology of vivax malaria. Trends Parasitol. 25, 220–227 (2009)

    CAS  Article  Google Scholar 

  3. 3

    Ekland, E. H. & Fidock, D. A. In vitro evaluations of antimalarial drugs and their relevance to clinical outcomes. Int. J. Parasitol. 38, 743–747 (2008)

    CAS  Article  Google Scholar 

  4. 4

    Andriantsoanirina, V. et al. Plasmodium falciparum drug resistance in Madagascar: facing the spread of unusual pfdhfr and pfmdr-1 haplotypes and the decrease of dihydroartemisinin susceptibility. Antimicrob. Agents Chemother. 53, 4588–4597 (2009)

    CAS  Article  Google Scholar 

  5. 5

    Bonnet, M. et al. Varying efficacy of artesunate+amodiaquine and artesunate+sulphadoxine-pyrimethamine for the treatment of uncomplicated falciparum malaria in the Democratic Republic of Congo: a report of two in-vivo studies. Malar. J. 8, 192 (2009)

    Article  Google Scholar 

  6. 6

    Carrara, V. I. et al. Changes in the treatment responses to artesunate-mefloquine on the northwestern border of Thailand during 13 years of continuous deployment. PLoS ONE 4, e4551 (2009)

    ADS  Article  Google Scholar 

  7. 7

    Payne, D. J., Gwynn, M. N., Holmes, D. J. & Pompliano, D. L. Drugs for bad bugs: confronting the challenges of antibacterial discovery. Nature Rev. Drug Discov. 6, 29–40 (2007)

    CAS  Article  Google Scholar 

  8. 8

    O'Brien, P. J. et al. High concordance of drug-induced human hepatotoxicity with in vitro cytotoxicity measured in a novel cell-based model using high content screening. Arch. Toxicol. 80, 580–604 (2006)

    CAS  Article  Google Scholar 

  9. 9

    Xia, M. et al. Compound cytotoxicity profiling using quantitative high-throughput screening. Environ. Health Perspect. 116, 284–291 (2008)

    CAS  Article  Google Scholar 

  10. 10

    Yuan, J. et al. Genetic mapping of targets mediating differential chemical phenotypes in Plasmodium falciparum . Nature Chem. Biol. 5, 765–771 (2009)

    CAS  Article  Google Scholar 

  11. 11

    Reed, M. B., Saliba, K. J., Caruana, S. R., Kirk, K. & Cowman, A. F. Pgh1 modulates sensitivity and resistance to multiple antimalarials in Plasmodium falciparum . Nature 403, 906–909 (2000)

    ADS  CAS  Article  Google Scholar 

  12. 12

    Bemis, G. W. & Murcko, M. A. The properties of known drugs. 1. Molecular frameworks. J. Med. Chem. 39, 2887–2893 (1996)

    CAS  Article  Google Scholar 

  13. 13

    Daylight Chemical Information Systems, Inc. Daylight theory manual. 〈〉 (2008)

  14. 14

    Johnson, M., Lajiness, M. & Maggiora, G. M. in Qsar: Quantitative structure-activity relationships in drug design (ed Fauchere, J. L.) 167–171 (Alan R. Liss, 1989)

    Google Scholar 

  15. 15

    Davis, A. M., Keeling, D. J., Steele, J., Tomkinson, N. P. & Tinker, A. C. Components of successful lead generation. Curr. Top. Med. Chem. 5, 421–439 (2005)

    CAS  Article  Google Scholar 

  16. 16

    Köhler, S. et al. A plastid of probable green algal origin in apicomplexan parasites. Science 275, 1485–1489 (1997)

    Article  Google Scholar 

  17. 17

    McFadden, G. I., Reith, M. E., Munholland, J. & Lang-Unnasch, N. Plastid in human parasites. Nature 381, 482 (1996)

    ADS  CAS  Article  Google Scholar 

  18. 18

    Le Roch, K. G. et al. Discovery of gene function by expression profiling of the malaria parasite life cycle. Science 301, 1503–1508 (2003)

    ADS  CAS  Article  Google Scholar 

  19. 19

    Bozdech, Z. et al. The transcriptome of the intraerythrocytic developmental cycle of Plasmodium falciparum . PLoS Biol. 1, e5 (2003)

    Article  Google Scholar 

  20. 20

    Wu, Y., Wang, X., Liu, X. & Wang, Y. Data-mining approaches reveal hidden families of proteases in the genome of malaria parasite. Genome Res. 13, 601–616 (2003)

    CAS  Article  Google Scholar 

  21. 21

    Leroy, D. & Doerig, C. Drugging the Plasmodium kinome: The benefits of academia–industry synergy. Trends Pharmacol. Sci. 29, 241–249 (2008)

    CAS  Article  Google Scholar 

  22. 22

    Manning, G., Whyte, D. B., Martinez, R., Hunter, T. & Sudarsanam, S. The protein kinase complement of the human genome. Science 298, 1912–1934 (2002)

    ADS  CAS  Article  Google Scholar 

  23. 23

    Anamika, S. N. & Krupa, A. A genomic perspective of protein kinases in Plasmodium falciparum . Proteins 58, 180–189 (2005)

    CAS  Article  Google Scholar 

  24. 24

    Ward, P., Equinet, L., Packer, J. & Doerig, C. Protein kinases of the human malaria parasite Plasmodium falciparum: the kinome of a divergent eukaryote. BMC Genomics 5, 79 (2004)

    Article  Google Scholar 

  25. 25

    Karaman, M. W. et al. A quantitative analysis of kinase inhibitor selectivity. Nature Biotechnol. 26, 127–132 (2008)

    CAS  Article  Google Scholar 

  26. 26

    Madeira, L. et al. Genome-wide detection of serpentine receptor-like proteins in malaria parasites. PLoS ONE 3, e1889 (2008)

    ADS  Article  Google Scholar 

  27. 27

    Aurrecoechea, C. et al. PlasmoDB: A functional genomic database for malaria parasites. Nucleic Acids Res. 37, D539–D543 (2009)

    CAS  Article  Google Scholar 

  28. 28

    Trager, W. & Jensen, J. B. Human malaria parasites in continuous culture. Science 193, 673–675 (1976)

    ADS  CAS  Article  Google Scholar 

  29. 29

    Makler, M. T. & Hinrichs, D. J. Measurement of the lactate dehydrogenase activity of Plasmodium falciparum as an assessment of parasitemia. Am. J. Trop. Med. Hyg. 48, 205–210 (1993)

    CAS  Article  Google Scholar 

  30. 30

    Zhang, J. H., Chung, T. D. Y. & Oldenburg, K. R. A simple statistical parameter for use in evaluation and validation of high throughput screening assays. J. Biomol. Screen. 4, 67–73 (1999)

    CAS  Article  Google Scholar 

  31. 31

    Desjardins, R. E., Canfield, C. J., Haynes, J. D. & Chulay, J. D. Quantitative assessment of antimalarial activity in vitro by a semiautomated microdilution technique. Antimicrob. Agents Chemother. 16, 710–718 (1979)

    CAS  Article  Google Scholar 

  32. 32

    Goodman, C. D., Su, V. & McFadden, G. I. The effects of anti-bacterials on the malaria parasite Plasmodium falciparum . Mol. Biochem. Parasitol. 152, 181–191 (2007)

    CAS  Article  Google Scholar 

  33. 33

    Ramya, T. N. C., Mishra, S., Karmodiya, K., Surolia, N. & Surolia, A. Inhibitors of nonhousekeeping functions of the apicoplast defy delayed death in Plasmodium falciparum . Antimicrob. Agents Chemother. 51, 307–316 (2007)

    CAS  Article  Google Scholar 

  34. 34

    Fidock, D. A., Rosenthal, P. J., Croft, S. L., Brun, R. & Nwaka, S. Antimalarial drug discovery: Efficacy models for compound screening. Nature Rev. Drug Discov. 3, 509–520 (2004)

    CAS  Article  Google Scholar 

  35. 35

    Aureus Pharma. AurSCOPE database. 〈〉 (2004)

  36. 36

    Altschul, S. F. et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25, 3389–3402 (1997)

    CAS  Article  Google Scholar 

  37. 37

    Thompson, J. D., Higgins, D. G. & Gibson, T. J. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 22, 4673–4680 (1994)

    CAS  Article  Google Scholar 

  38. 38

    Felsentein, J. Phylip (phylogenetic inference package) v3.67. Department of Genetics, University of Washington〉.

  39. 39

    Huson, D. H. et al. Dendroscope: An interactive viewer for large phylogenetic trees. BMC Bioinformatics 8, 460 (2007)

    Article  Google Scholar 

Download references


We thank S. Peregrina and S. Prats for technical assistance, and D. Jiménez-Alfaro for supplying compounds pre-dispensed in microtitre plates. We thank P. Vallance and R. Keenan for organising support for this work, R. Macarron and J. Luengo for developing the IFI index and getting the chemistry data ready for publication, together with J. M. Fiandor, S. Chakravorty and members of GSK’s Chemistry Council. J. Lewis, A. Clow, J. Overington and M. Davies were instrumental in the uploading and formatting of the data. We also thank N. Cammack, P. Sanseau and J. Burrows for critically commenting on the manuscript. The support and funding of Medicines for Malaria Venture is gratefully acknowledged.

Author information




F.-J.G. and J.F.G.-B. planned and designed the work. F.-J.G. supervised all experimental work and analysed the screening data, L.M.S., J.V., C.d.C. and E.A. performed the screening assays and contributed to data analysis. J.-L.L., D.E.V., D.V.S.G. and C.E.P. performed the cheminformatic analyses and wrote sections of the manuscript. V.K., S.H. and J.R.B. performed the bioinformatic analyses and J.R.B. contributed the relevant sections to the manuscript. L.R.C and J.F.G.-B integrated individual contributions and wrote the final manuscript.

Corresponding author

Correspondence to Jose F. Garcia-Bustos.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

Chemical structures and data described have been deposited at EBI (

Supplementary information

Supplementary Information

This file contains Supplementary Figures 1-3 with legends and Supplementary Tables 3-5. (PDF 675 kb)

Supplementary Table 1

This table contains an annotated list of all positives from the P. falciparum screen. Structures are shown as "SMILES" codes. (XLS 3451 kb)

Supplementary Table 2

This table shows compounds in TCAMS with literature references on their mode of action. (XLS 437 kb)

Supplementary Data 1

The file contains the multiple kinase sequence alignment. This file was added on 2 June 2010. (TXT 173 kb)

PowerPoint slides

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Gamo, F., Sanz, L., Vidal, J. et al. Thousands of chemical starting points for antimalarial lead identification. Nature 465, 305–310 (2010).

Download citation

Further reading


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.