Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Opinion
  • Published:

Hit and lead criteria in drug discovery for infectious diseases of the developing world

Abstract

Reducing the burden of infectious diseases that affect people in the developing world requires sustained collaborative drug discovery efforts. The quality of the chemical starting points for such projects is a key factor in improving the likelihood of clinical success, and so it is important to set clear go/no-go criteria for the progression of hit and lead compounds. With this in mind, the Japanese Global Health Innovative Technology (GHIT) Fund convened with experts from the Medicines for Malaria Venture, the Drugs for Neglected Diseases initiative and the TB Alliance, together with representatives from the Bill & Melinda Gates Foundation, to set disease-specific criteria for hits and leads for malaria, tuberculosis, visceral leishmaniasis and Chagas disease. Here, we present the agreed criteria and discuss the underlying rationale.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Similar content being viewed by others

References

  1. World Health Organization. Antimicrobial resistance: global report on surveillance 2014 (WHO, 2014).

  2. Martis, E. A., Radhakrishnan, R. & Badve, R. R. High-throughput screening: the hits and leads of drug discovery — an overview. J. Appl. Pharma. Sci. 1, 2–10 (2011).

    Google Scholar 

  3. Khanna, I. Drug discovery in pharmaceutical industry: productivity challenges and trends. Drug Discov. Today 17, 1088–1102 (2012).

    Article  Google Scholar 

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

    Article  CAS  Google Scholar 

  5. Nwaka, S. et al. Advancing drug innovation for neglected diseases-criteria for lead progression. PLoS Negl Trop. Dis. 3, e440 (2009).

    Article  Google Scholar 

  6. Burrows, J. N., Hooft van Huijsduijnen, R., Möhrle, J. J., Oeuvray, C. & Wells, T. N. C. Designing the next generation of medicines for malaria control and eradication. Malar. J. 12, 187 (2013).

    Article  Google Scholar 

  7. Swinney, D. C. Phenotypic versus target-based drug discovery for first-in-class medicines. Clin. Pharmacol. Ther. 93, 299–301 (2013).

    Article  CAS  Google Scholar 

  8. Eder, J., Sedrani, R. & Wiesmann, C. The discovery of first-in-class drugs: origins and evolution. Nat. Rev. Drug Discov. 13, 577–587 (2014).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  10. Deng, X. et al. Fluorine modulates species selectivity in the triazolopyrimidine class of Plasmodium falciparum dihydroorotate dehydrogenase inhibitors. J. Med. Chem. 57, 5381–5394 (2014).

    Article  CAS  Google Scholar 

  11. Schuster, F. L. Cultivation of Plasmodium spp. Clin. Microbiol. Rev. 15, 355–364 (2002).

    Article  Google Scholar 

  12. Mutai, B. K. & Waitumbi, J. N. Apoptosis stalks Plasmodium falciparum maintained in continuous culture condition. Malar J. 9 (Suppl. 3), S6 (2010).

    Article  CAS  Google Scholar 

  13. Chatelain, E. Chagas disease drug discovery: toward a new era. J. Biomol. Screen 20, 22–35 (2015).

    Article  Google Scholar 

  14. Wells, T. N. C., Hooft van Huijsduijnen, R. & Van Voorhis, W. C. Malaria medicines: a glass half full? Nat. Rev. Drug Discov. 14, 1–18 (2015).

    Article  Google Scholar 

  15. Bosman, A. & Mendis, K. N. A major transition in malaria treatment: the adoption and deployment of artemisinin-based combination therapies. Am. J. Trop. Med. Hyg. 77, 193–197 (2007).

    Article  Google Scholar 

  16. Leibert, E., Danckers, M. & Rom, W. N. New drugs to treat multidrug-resistant tuberculosis: the case for bedaquiline. Ther. Clin. Risk Manag. 10, 597–602 (2014).

    Article  CAS  Google Scholar 

  17. Xavier, A. S. & Lakshmanan, M. Delamanid: a new armor in combating drug-resistant tuberculosis. J. Pharmacol. Pharmacother. 5, 222–224 (2014).

    Article  CAS  Google Scholar 

  18. Wunberg, T. et al. Improving the hit-to-lead process: data-driven assessment of drug-like and lead-like screening hits. Drug Discov. Today 11, 175–180 (2006).

    Article  CAS  Google Scholar 

  19. Hughes, M. et al. Early drug discovery and development guidelines: for academic researchers, collaborators, and start-up companies. Assay Guidance Manual [online], (2012).

    Google Scholar 

  20. Ariey, F. et al. A molecular marker of artemisinin-resistant Plasmodium falciparum malaria. Nature 505, 50–55 (2014).

    Article  Google Scholar 

  21. Ashley, E. A. et al. Spread of artemisinin resistance in Plasmodium falciparum malaria. N. Engl. J. Med. 371, 411–423 (2014).

    Article  Google Scholar 

  22. Burrows, J. Microbiology: malaria runs rings round artemisinin. Nature 520, 628–630 (2015).

    Article  CAS  Google Scholar 

  23. Mbengue, A. et al. A molecular mechanism of artemisinin resistance in Plasmodium falciparum malaria. Nature 520, 683–687 (2015).

    Article  CAS  Google Scholar 

  24. Burrows, J. N. & Waterson, D. in Third World Diseases (ed. Elliot, R. L.) 125–180 (Springer, 2011).

    Book  Google Scholar 

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

    Article  CAS  Google Scholar 

  26. Guiguemde, W. A. et al. Chemical genetics of Plasmodium falciparum. Nature 465, 311–315 (2010).

    Article  CAS  Google Scholar 

  27. Plouffe, D. et al. In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen. Proc. Natl Acad. Sci. USA 105, 9059–9064 (2008).

    Article  CAS  Google Scholar 

  28. Meister, S. et al. Imaging of Plasmodium liver stages to drive next-generation antimalarial drug discovery. Science 334, 1372–1377 (2011).

    Article  CAS  Google Scholar 

  29. Angulo-Barturen, I. et al. A murine model of falciparum-malaria by in vivo selection of competent strains in non-myelodepleted mice engrafted with human erythrocytes. PLoS ONE 3, e2252 (2008).

    Article  Google Scholar 

  30. Nilsen, A. et al. Quinolone-3-diarylethers: a new class of antimalarial drug. Sci. Transl. Med. 5, 177ra37 (2013).

    Article  Google Scholar 

  31. Winzeler, E. A. & Manary, M. J. Drug resistance genomics of the antimalarial drug artemisinin. Genome Biol. 15, 544 (2014).

    Article  Google Scholar 

  32. Isozumi, R. et al. Novel mutations in K13 propeller gene of artemisinin-resistant Plasmodium falciparum. Emerg. Infect. Dis. 21, 490–492 (2015).

    Article  CAS  Google Scholar 

  33. Tun, K. M. et al. Spread of artemisinin-resistant Plasmodium falciparum in Myanmar: a cross-sectional survey of the K13 molecular marker. Lancet Infect. Dis. 15, 415–421 (2015).

    Article  CAS  Google Scholar 

  34. Dembele, L. et al. Towards an in vitro model of Plasmodium hypnozoites suitable for drug discovery. PLoS ONE 6, e18162 (2011).

    Article  CAS  Google Scholar 

  35. Sinden, R. E., Carter, R., Drakeley, C. & Leroy, D. The biology of sexual development of Plasmodium: the design and implementation of transmission-blocking strategies. Malar J. 11, 70 (2012).

    Article  Google Scholar 

  36. World Health Organization. Global tuberculosis report 2014. WHO [online], (2014).

  37. Franzblau, S. G. et al. Rapid, low-technology MIC determination with clinical Mycobacterium tuberculosis isolates by using the microplate Alamar Blue assay. J. Clin. Microbiol. 36, 362–366 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Cho, S. H. et al. Low-oxygen-recovery assay for high-throughput screening of compounds against nonreplicating Mycobacterium tuberculosis. Antimicrob. Agents Chemother. 51, 1380–1385 (2007).

    Article  CAS  Google Scholar 

  39. Mak, P. A. et al. A high-throughput screen to identify inhibitors of ATP homeostasis in non-replicating Mycobacterium tuberculosis. ACS Chem. Biol. 7, 1190–1197 (2012).

    Article  CAS  Google Scholar 

  40. Wayne, L. G. In vitro model of hypoxically induced nonreplicating persistence of Mycobacterium tuberculosis. Methods Mol. Med. 54, 247–269 (2001).

    CAS  PubMed  Google Scholar 

  41. Lakshminarayana, S. B. et al. Comprehensive physicochemical, pharmacokinetic and activity profiling of anti-TB agents. J. Antimicrob. Chemother. 70, 857–867 (2015).

    Article  CAS  Google Scholar 

  42. Dhar, N. & McKinney, J. D. Microbial phenotypic heterogeneity and antibiotic tolerance. Curr. Opin. Microbiol. 10, 30–38 (2007).

    Article  CAS  Google Scholar 

  43. Mitchison, D. A. The search for new sterilizing anti-tuberculosis drugs. Front. Biosci. 9, 1059–1072 (2004).

    Article  CAS  Google Scholar 

  44. Franzblau, S. G. et al. Comprehensive analysis of methods used for the evaluation of compounds against Mycobacterium tuberculosis. Tuberculosis (Edinb.) 92, 453–488 (2012).

    Article  CAS  Google Scholar 

  45. Silva-Miranda, M. et al. High-content screening technology combined with a human granuloma model as a new approach to evaluate the activities of drugs against Mycobacterium tuberculosis. Antimicrob. Agents Chemother. 59, 693–697 (2015).

    Article  Google Scholar 

  46. Pethe, K. et al. Discovery of Q203, a potent clinical candidate for the treatment of tuberculosis. Nat. Med. 19, 1157–1160 (2013).

    Article  CAS  Google Scholar 

  47. Russell, D. G., Cardona, P. J., Kim, M. J., Allain, S. & Altare, F. Foamy macrophages and the progression of the human tuberculosis granuloma. Nat. Immunol. 10, 943–948 (2009).

    Article  CAS  Google Scholar 

  48. Harper, J. et al. Mouse model of necrotic tuberculosis granulomas develops hypoxic lesions. J. Infect. Dis. 205, 595–602 (2012).

    Article  CAS  Google Scholar 

  49. Datta, M. et al. Anti-vascular endothelial growth factor treatment normalizes tuberculosis granuloma vasculature and improves small molecule delivery. Proc. Natl Acad. Sci. USA 112, 1827–1832 (2015).

    Article  CAS  Google Scholar 

  50. Hawn, T. R., Shah, J. A. & Kalman, D. New tricks for old dogs: countering antibiotic resistance in tuberculosis with host-directed therapeutics. Immunol. Rev. 264, 344–362 (2015).

    Article  CAS  Google Scholar 

  51. Moore, E. M. & Lockwood, D. N. Treatment of visceral leishmaniasis. J. Glob. Infect. Dis. 2, 151–158 (2010).

    Article  CAS  Google Scholar 

  52. Sundar, S. & Chakravarty, J. An update on pharmacotherapy for leishmaniasis. Expert Opin. Pharmacother. 16, 237–252 (2014).

    Article  Google Scholar 

  53. Molina, I. et al. Randomized trial of posaconazole and benznidazole for chronic Chagas' disease. N. Engl. J. Med. 370, 1899–1908 (2014).

    Article  Google Scholar 

  54. De Rycker, M. et al. Comparison of a high-throughput high-content intracellular Leishmania donovani assay with an axenic amastigote assay. Antimicrob. Agents Chemother. 57, 2913–2922 (2013).

    Article  CAS  Google Scholar 

  55. Keenan, M. et al. Selection and optimization of hits from a high-throughput phenotypic screen against Trypanosoma cruzi. Future Med. Chem. 5, 1733–1752 (2013).

    Article  CAS  Google Scholar 

  56. Pena, I. et al. New compound sets identified from high throughput phenotypic screening against three kinetoplastid parasites: an open resource. Sci. Rep. 5, 8771 (2015).

    Article  CAS  Google Scholar 

  57. Don, R. & Ioset, J. R. Screening strategies to identify new chemical diversity for drug development to treat kinetoplastid infections. Parasitology 141, 140–146 (2014).

    Article  Google Scholar 

  58. Lipinski, C. A., Lombardo, F., Dominy, B. W. & Feeney, P. J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. 46, 3–26 (2001).

    Article  CAS  Google Scholar 

  59. Gilbert, I. H. Drug discovery for neglected diseases: molecular target-based and phenotypic approaches. J. Med. Chem. 56, 7719–7726 (2013).

    Article  CAS  Google Scholar 

  60. Ansari, M. T. et al. Malaria and artemisinin derivatives: an updated review. Mini Rev. Med. Chem. 13, 1879–1902 (2013).

    Article  CAS  Google Scholar 

  61. Clark, R. L. Embryotoxicity of the artemisinin antimalarials and potential consequences for use in women in the first trimester. Reprod. Toxicol. 28, 285–296 (2009).

    Article  CAS  Google Scholar 

  62. Toovey, S. Safety of artemisinin antimalarials. Clin. Infect. Dis. 42, 1214–1215 (2006).

    Article  Google Scholar 

  63. Braselmann, S. et al. R406, an orally available spleen tyrosine kinase inhibitor blocks fc receptor signaling and reduces immune complex-mediated inflammation. J. Pharmacol. Exp. Ther. 319, 998–1008 (2006).

    Article  CAS  Google Scholar 

  64. Oberlies, N. H. & Kroll, D. J. Camptothecin and taxol: historic achievements in natural products research. J. Nat. Prod. 67, 129–135 (2004).

    Article  CAS  Google Scholar 

  65. Tsang, C. K., Qi, H., Liu, L. F. & Zheng, X. F. Targeting mammalian target of rapamycin (mTOR) for health and diseases. Drug Discov. Today 12, 112–124 (2007).

    Article  CAS  Google Scholar 

  66. Borel, J. F. History of the discovery of cyclosporin and of its early pharmacological development. Wien Klin. Wochenschr. 114, 433–437 (2002).

    CAS  PubMed  Google Scholar 

  67. Slingsby, B. T. & Kurokawa, K. The Global Health Innovative Technology (GHIT) fund: financing medical innovations for neglected populations. Lancet Glob. Health 1, e184–185 (2013).

    Article  CAS  Google Scholar 

  68. Holmes, D. The GHIT fund shows its cards. Nat. Rev. Drug Discov. 12, 894 (2013).

    Article  Google Scholar 

  69. Crump, A. & Omura, S. Ivermectin, 'wonder drug' from Japan: the human use perspective. Proc. Jpn Acad., Ser. B 87, 13–28 (2011).

    Article  CAS  Google Scholar 

  70. Kita, K., Shiomi, K. & Omura, S. Advances in drug discovery and biochemical studies. Trends Parasitol. 23, 223–229 (2007).

    Article  CAS  Google Scholar 

  71. Omura, S. & Crump, A. The life and times of ivermectin - a success story. Nat. Rev. Microbiol. 2, 984–989 (2004).

    Article  CAS  Google Scholar 

  72. Strader, C. R., Pearce, C. J. & Oberlies, N. H. Fingolimod (FTY720): a recently approved multiple sclerosis drug based on a fungal secondary metabolite. J. Nat. Prod. 74, 900–907 (2011).

    Article  CAS  Google Scholar 

  73. Endo, A. A historical perspective on the discovery of statins. Proc. Jpn Acad. Ser. B Phys. Biol. Sci. 86, 484–493 (2010).

    Article  CAS  Google Scholar 

  74. Tobert, J. A. Lovastatin and beyond: the history of the HMG-CoA reductase inhibitors. Nat. Rev. Drug Discov. 2, 517–526 (2003).

    Article  CAS  Google Scholar 

  75. Baell, J. B. & Holloway, G. A. New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays. J. Med. Chem. 53, 2719–2740 (2010).

    Article  CAS  Google Scholar 

  76. McGovern, S. L., Caselli, E., Grigorieff, N. & Shoichet, B. K. A common mechanism underlying promiscuous inhibitors from virtual and high-throughput screening. J. Med. Chem. 45, 1712–1722 (2002).

    Article  CAS  Google Scholar 

  77. Baell, J. & Walters, M. A. Chemistry: chemical con artists foil drug discovery. Nature 513, 481–483 (2014).

    Article  CAS  Google Scholar 

  78. Burrows, J. N., Leroy, D., Lotharius, J. & Waterson, D. Challenges in antimalarial drug discovery. Future Med. Chem. 3, 1401–1412 (2011).

    Article  CAS  Google Scholar 

  79. Ruecker, A. et al. A male and female gametocyte functional viability assay to identify biologically relevant malaria transmission-blocking drugs. Antimicrob. Agents Chemother. 58, 7292–7302 (2014).

    Article  CAS  Google Scholar 

  80. Orme, I. Cellular and genetic mechanisms underlying susceptibility of animal models to tuberculosis infection. Novartis Found. Symp. 217, 112–117; discussion 117–119 (1998).

    Article  CAS  Google Scholar 

  81. Priest, B. T., Bell, I. M. & Garcia, M. L. Role of hERG potassium channel assays in drug development. Channels (Austin) 2, 87–93 (2008).

    Article  Google Scholar 

  82. Riss, T. L. et al. Cell viability assays. Assay Guidance Manual [online], (2004).

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kei Katsuno.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Related links

Related links

FURTHER INFORMATION

Drugs for Neglected Diseases initiative

Global Health Innovative Technology (GHIT) Fund

Japanese Pharmaceutical Manufacturers Association

Medicines for Malaria Venture

TB Alliance

WHO website

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Katsuno, K., Burrows, J., Duncan, K. et al. Hit and lead criteria in drug discovery for infectious diseases of the developing world. Nat Rev Drug Discov 14, 751–758 (2015). https://doi.org/10.1038/nrd4683

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrd4683

This article is cited by

Search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research