Search tips
Search criteria 


Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Nature. Author manuscript; available in PMC 2010 November 20.
Published in final edited form as:
PMCID: PMC2874979

Chemical genetics of Plasmodium falciparum


Malaria caused by Plasmodium falciparum is a catastrophic disease worldwide (880,000 deaths yearly). Vaccine development has proved difficult and resistance has emerged for most antimalarials. In order to discover new antimalarial chemotypes, we have employed a phenotypic forward chemical genetic approach to assay 309,474 chemicals. Here we disclose structures and biological activity of the entire library, many of which exhibited potent in vitro activity against drug resistant strains, and detailed profiling of 172 representative candidates. A reverse chemical genetic study identified 19 new inhibitors of 4 validated drug targets and 15 novel binders among 61 malarial proteins. Phylochemogenetic profiling in multiple organisms revealed similarities between Toxoplasma gondii and mammalian cell lines and dissimilarities between P. falciparum and related protozoans. One exemplar compound displayed efficacy in a murine model. Overall, our findings provide the scientific community with new starting points for malaria drug discovery.

The wide-spread resistance of P. falciparum to many antimalarial drugs, the dependence of all new combinations on artemisinins (for which resistance may have emerged),1 ,2 and new efforts to eradicate malaria all drive the need to develop new, effective, and affordable antimalarial drugs.3 Although our understanding of the parasite’s biology has increased with sequencing of the genome4 and the development of new technologies to study resistance acquisition,5 ,6 ,7 few new drug targets or classes of drugs have been clinically validated.8 The lack of publicly-accessible antimalarial chemotypes with differing modes of action has significantly hindered efforts to discover and develop new drugs.9 In order to address this urgent need, we have developed a forward chemical genetic approach to identify novel antimalarials (Supplementary Fig. 1).

The forward chemical genetic screen

A library containing 309,474 unique compounds, designed at the scaffold level to provide diverse, comprehensive coverage of bioactive space,10 ,11 was screened against Plasmodium falciparum (Pf3D7) at a fixed concentration of 7 μM (Supplementary Information).12 Fidelity of the assay was examined by receiver operator characteristic (ROC) analysis and other metrics (Supplementary Fig. 2 and 3), demonstrating good discriminatory power (AUC ~0.85) and suggesting that a cutoff of ≥ 80% activity would retain the majority of true positives. The strength of the assay was further determined by testing a set of bioactive compounds including known antimalarials, all of which were re-identified (Supplementary Table 3), demonstrating that the method was very likely to identify any molecule acting by a known mechanism. The primary screen gave 1152 compounds with activity > 80%. These 1152 compounds and the true positives from the ROC set were serially diluted and tested against both the chloroquine-sensitive Pf3D7 and the chloroquine-resistant PfK1 strain, giving 1300 validated hits that had saturated dose-response curves. Chemical structure analysis of validated hits by topology mapping and clustering10 revealed a wide distribution of chemotypes in the active chemical space, with several displaying promising structure-activity relationships (Fig. 1). While all known antimalarial scaffolds (aminoquinolines, quinolones, bis-amidines) present in the screening collection were identified, providing positive controls for the screen, most of the chemotypes identified were novel. 561 of the validated hits had EC50 values ≤ 2 μM against either Pf3D7 or PfK1 and a therapeutic window ≥ 10-fold against two mammalian cell lines (HepG2 & BJ). From this set, 228 structurally distinct, pure compounds were re-purchased. Antimalarial potencies of ~75% of these compounds (172) were re-confirmed to within 10-fold (Bland-Altman analysis, Supplementary Fig. 4) by three laboratories using distinct methods providing the cross-validated hit set utilized for all subsequent experiments.

Figure 1
Chemical structure network graph and antimalarial potencies of the 1300 validated hits

Combination with antimalarial drugs

Due to rapid resistance acquisition, the WHO recommends combination therapy.13 The agonistic and antagonistic synergies of the cross-validated set were therefore quantified by measuring EC50 shifts in the presence of a fixed fraction of potency (EC10) concentration of chloroquine, mefloquine, artemisinin, and atovaquone. Most cross-validated compounds were additive in effect or had minor synergies with existing drugs. Two classes demonstrated strong synergies (EC50′s reduced by ≥ 10-fold): the diaminonaphthoquinones with artemisinin, and the dihydropyridines with mefloquine (Fig. 2). One diaminonaphthoquinone and a cycloguanil analog displayed antagonism with chloroquine and mefloquine, respectively.

Figure 2
Reduced representation of the network map showing synergistic activities with clinically relevant antimalarials

Reverse chemical genetics

The advantages of phenotypic screens for the identification of novel chemotypes are that no a priori assumptions are made concerning drug targets and that active compounds inherently have cellular bioavailability. Because insight into mechanism of action is helpful for drug development, we also investigated the interaction of the cross-validated set with 66 potential targets using enzyme inhibition assays and thermal-melt shift assays (to detect binding).

Three high-priority, well characterized biological targets were evaluated in activity assays (Fig. 3, left): P. falciparum dihydroorotate dehydrogenase (PfDHOD), hemozoin formation, and falcipain-2 (PfFP-2). PfDHOD, catalyzes the oxidation of dihydroorotate to orotate in de novo pyrimidine biosynthesis, which is essential for parasite viability.14 ,15 Three compounds inhibited this enzyme: two triazolopyrimidines, structurally related to known PfDHOD inhibitors with comparable potencies,14 and a dihydropyridine, structurally related to the calcium blocker felodipine. The potency of these compounds against PfDHOD strongly correlated with their antimalarial activities (Supplementary Table 5). Furthermore, these compounds were inactive against transgenic parasites expressing Saccharomyces cerevisiae dihydroorotate dehydrogenase (Supplementary Table 6). Next, hemozoin formation inhibition was investigated. The parasite digests host hemoglobin to provide amino acids, detoxifying the resulting heme molecules by conversion to a crystallized form known as hemozoin. Heme detoxification is believed to be the target of many antimalarial drugs.16 Twelve compounds exhibited appreciable efficacy in an in vitro hemozoin formation assay,17 including analogs of quinazoline, benzofuran, benzimidazole, and carbazole as well as amodiaquine, a known hemozoin formation inhibitor present in our library. The correlation between enzyme inhibitory potency and antimalarial potency was similar to that displayed by the positive controls quinine and amodiaquine (Supplementary Table 5). The third enzyme assayed was PfFP-2, which plays a critical role in hemoglobin degradation.18 Falcipains are redundant in P. falciparum, with four known homologs including two (falcipain-2 and falcipain-3) that appear to play key roles in erythrocytic stage parasites.19 Three weakly FP-2 inhibitors were identified. Thus 19 compounds (11%) were inhibitors of validated antimalarial targets.

Figure 3
Reduced representation of the network map showing the interaction of the cross-validated hits with potential biological targets

To expand the pool of potential targets, the compounds were tested for binding to 61 recombinant malarial proteins (95% purity or better after affinity and size exclusion chromatography, Supplementary Table 1) in a thermal-melt shift assay.20 Fifteen compounds displayed reproducible thermal shifts with seven malarial proteins (Fig. 3, right; Kd’s in Supplementary Table 2): 6-phosphogluconolactonase, 6-pyruvoyltetrahydropterin synthase, choline kinase, D-ribulose-5-phosphate 3-epimerase, dUTPase, glycogen synthase kinase 3, and thioredoxin. 2 compounds bound multiple proteins. 2 out of the 7 proteins are in essential malarial pathways: phosphatidylcholine synthesis21 (choline kinase) and redox metabolism22 (thioredoxin). The remaining 5 protein targets potentially represent novel antimalarial drug targets.

The potential for cross resistance

To evaluate the potential for cross-resistance with existing drugs, the cross-validated compounds were tested against a panel of P. falciparum strains with different chemosensitivities to known antimalarials, including Pf3D7 (chloroquine sensitive), PfK1, PfW2, PfV1/S and PfDd2 (all resistant to both chloroquine and to antifolates), PfSB-A6 and PfD10_yDHOD (both chloroquine sensitive and atovaquone resistant). All strains were profiled for sensitivity to a set of antimalarial drugs to normalize activity (Supplementary Table 3). 58 cross-validated compounds displayed similar potencies (EC50 shift ≤ 3-fold) against Pf3D7, PfK1, PfV1/S and PfSB-A6, suggesting that these compounds do not share mechanisms of resistance with chloroquine, atovaquone, or sulfadoxine/pyrimethamine. A subset of the 172 compounds that were inactive against drug resistant P. falciparum strains with known mutations in target proteins were tested against Pf3D7 dihydrofolate reductase and P. yoelii cytochrome bc1 complex in biochemical assays. Two inhibitors were identified for each protein (Supplementary Table 5 and 6).

Phylochemogenetic profiling

To understand relationships between chemical sensitivity of Plasmodium and related parasites, the cross-validated set was tested against three additional protozoan parasite species: Toxoplasma gondii (Tg), which belongs to the same phylum as Plasmodium (Apicomplexa); Leishmania major (Lm) and Trypanosoma brucei (Tb), which are both Kinetoplastida, unrelated to the Apicomplexa; and an expanded panel of human cell lines including a Burkitt’s lymphoma line (Raji) and embryonic kidney fibroblast cells (HEK-293). Phylogenetic criteria predict that chemical sensitivity should correlate with evolutionary history, due to homology between key protein targets, as is known to be the case for many antiparasitic drugs.23 ,24 Although a few compounds showed activity in other parasites, most were highly selective for Plasmodium (Fig. 4), while Toxoplasma exhibited a chemosensitivity pattern more similar to human cell lines. Similarly, the highly potent anti-leishmanial benzothiazoles were only weakly active against the related Trypanosoma. These findings suggest that chemical sensitivity of pathogens is regulated by a combination of pathogen genetics, physiology, and relationships to host and vector species in vivo.

Figure 4
Phylochemogenetic profiling

Early leads for drug development

In order to understand the potential for development of the novel chemotypes, the pharmacokinetic properties of the cross-validated set were assessed. The majority are reasonably drug-like, with 78% of compounds have no violations of the Lipinski Rule of 5, and 99% have one or fewer violations.25 Within the cross-validated set were embedded 3 chemical series that had multiple members that together gave structure-activity relationships that spanned 1000-fold potency differences, had consistent activity in drug resistant strains, had very good cellular therapeutic windows, and had at least one member with an EC50 more potent than 50 nM. An exemplar compound was selected from each series and fully profiled using standard models of in vitro and in vivo adsorption, distribution, metabolism, and toxicity (Supplementary Table 7). Each possessed reasonable characteristics for developable hits, indeed each comes close to passing MMV criteria for “late leads.” The compound from these exemplars with the best pharmacokinetic profile, was further evaluated to measure in vivo antimalarial activity and displayed efficacy in a murine malaria model infected with P. yoelii. A twice-daily administration of 100 mg/kg for 3 days resulted in a 90% suppression of the parasitemia (Supplementary Fig. 5). Although it is not suggested that any of the compounds discussed herein are bone fide preclinical candidates all provide reasonable starting points for drug development.


Drug therapy remains a key component in controlling malaria. Current challenges of rapid acquisition of resistance, cross-resistance, and dependence upon a limited number of chemical classes of antimalarials highlight the need to enhance our understanding of the “chemical space” that can fruitfully be brought to bear on malaria treatment. Solving this problem requires understanding the relationships between the structures of compounds active against malaria parasites and their potency, selectivity, and targets. We have identified a number of novel compounds and defined these relationships. We expect that these findings will provide novel paths for drug development and hope that making this set of well characterized, non-proprietary lead antimalarials publicly available to the global research community will help to reinvigorate drug discovery for malaria.

Methods summary

The primary screen was carried out by comparing quantities of DNA in treated and control cultures of Plasmodium falciparum in human erythrocytes after 72 h incubation with a fixed concentration of 7 μM of the test compounds.. The secondary potency determination was made by using the same assay in a dose-response mode with 12 concentrations varying from 10 μM to 5 nM. Chemical sensitivities of the human cell lines and T. brucei were determined by measuring their ATP content (Cell Titer Glo, Promega). T. gondii parasites expressing luciferase were cultured and drug sensitivity was determined by luminescence; L. major promastigotes drug susceptibility (Alamar Blue assay, Promega). Chemicals were assayed for hemozoin formation inhibition17, PfDHOD15, FP-227 activities based on previously described methods. Thermal shift assays were done at compound concentrations of 25 μM and protein concentrations of 100 μg/ml. All data processing and visualization, and chemical similarity and substructure analysis was performed using custom programs written in the Pipeline Pilot platform (Accelrys, v.7.0.1) and the R program.26 A complete description of the methods can be found in Supplementary Information.

Supplementary Material


This work was supported by the American Lebanese Syrian Associated Charities (ALSAC) and St. Jude Children’s Research Hospital (SJCRH, RKG), the Medicines for Malaria Venture (WCVV & VMA), National Institute of Allergy and Infectious Diseases (AI772682 (PHD), AI28724 (DSR), AI53862 (JLD), AI35707 (PJR), AI053680 (MAP and PKR), AI075594 (MAP, PKR, and IB), AI082617 (PKR) and AI045774 (DJS)), the National Cancer Institute (CA78039 (JSL)), the Welch Foundation (I-1257(MAP)), the Doris Duke Charitable Foundation (PJR), and the Ellison Medical Foundation (DSR). We acknowledge Akhil B. Vaidya for providing the parasite strain D10_yDHOD. We acknowledge Martina Sigal for assistance in the early leads project coordination, the SJCRH High Throughput Screening Center, particularly Jimmy Cui for robotic support; the SJCRH Lead Discovery Informatics Center, and the SJCRH High Throughput Analytical Chemistry Center, particularly Cynthia Nelson for compound management and Andrew Lemoff for compound quality control; at UW, Fred Buckner, Wim Hol, and Alberto Napuli, for selecting and preparing the proteins used in the thermal melt shift experiments (AI067921, Wim Hol PI); and the Australian Red Cross Blood Service for the provision O+ erythrocytes to Griffith University.


Supplementary information

The supplementary information provides a summary of all relevant data arising from the phenotypic screen and all secondary screens including relevant diagnostics and details about the following: cell-based, enzyme, and thermal shift screens, data processing, Bland-Altman analysis, and the algorithm to generate chemical structure network graph. Chemical structures annotated with assay data and high resolution PDF’s of the figures may be downloaded from


1. Wongsrichanalai C, Meshnick SR. Declining artesunate-mefloquine efficacy against falciparum malaria on the Cambodia-Thailand border. Emerg Infect Dis. 2008;14(5):716. [PMC free article] [PubMed]
2. Dondorp AM, et al. Artemisinin resistance in Plasmodium falciparum malaria. N Engl J Med. 2009;361(5):455. [PMC free article] [PubMed]
3. Ridley RG. Medical need, scientific opportunity and the drive for antimalarial drugs. Nature. 2002;415(6872):686. [PubMed]
4. Kissinger JC, et al. The Plasmodium genome database. Nature. 2002;419(6906):490. [PubMed]
5. Baniecki ML, Wirth DF, Clardy J. High-throughput Plasmodium falciparum growth assay for malaria drug discovery. Antimicrob Agents Chemother. 2007;51(2):716. [PMC free article] [PubMed]
6. 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 U S A. 2008;105(26):9059. [PubMed]
7. Weisman JL, et al. Searching for new antimalarial therapeutics amongst known drugs. Chem Biol Drug Des. 2006;67(6):409. [PMC free article] [PubMed]
8. Wells TN, Alonso PL, Gutteridge WE. New medicines to improve control and contribute to the eradication of malaria. Nat Rev Drug Discov. 2009;8(11):879. [PubMed]
9. Munos B. Can open-source R&D reinvigorate drug research? Nat Rev Drug Discov. 2006;5(9):723. [PubMed]
10. Shelat AA, Guy RK. Scaffold composition and biological relevance of screening libraries. Nat Chem Biol. 2007;3(8):442. [PubMed]
11. Shelat AA, Guy RK. The interdependence between screening methods and screening libraries. Curr Opin Chem Biol. 2007;11(3):244. [PubMed]
12. Smilkstein M, et al. Simple and inexpensive fluorescence-based technique for high-throughput antimalarial drug screening. Antimicrob Agents Chemother. 2004;48(5):1803. [PMC free article] [PubMed]
13. Cibulskis RE, et al. Estimating trends in the burden of malaria at country level. Am J Trop Med Hyg. 2007;77(6 Suppl):133. [PubMed]
14. Gujjar R, et al. Identification of a metabolically stable triazolopyrimidine-based dihydroorotate dehydrogenase inhibitor with antimalarial activity in mice. J Med Chem. 2009;52(7):1864. [PMC free article] [PubMed]
15. Patel V, et al. Identification and characterization of small molecule inhibitors of Plasmodium falciparum dihydroorotate dehydrogenase. J Biol Chem. 2008;283(50):35078. [PMC free article] [PubMed]
16. Weissbuch I, Leiserowitz L. Interplay between malaria, crystalline hemozoin formation, and antimalarial drug action and design. Chem Rev. 2008;108(11):4899. [PubMed]
17. Pisciotta JM, et al. The role of neutral lipid nanospheres in Plasmodium falciparum haem crystallization. Biochem J. 2007;402(1):197. [PubMed]
18. Sijwali PS, Rosenthal PJ. Gene disruption confirms a critical role for the cysteine protease falcipain-2 in hemoglobin hydrolysis by Plasmodium falciparum. Proc Natl Acad Sci U S A. 2004;101(13):4384. [PubMed]
19. Sijwali PS, Koo J, Singh N, Rosenthal PJ. Gene disruptions demonstrate independent roles for the four falcipain cysteine proteases of Plasmodium falciparum. Mol Biochem Parasitol. 2006;150(1):96. [PubMed]
20. Crowther GJ, et al. Buffer optimization of thermal melt assays of Plasmodium proteins for detection of small-molecule ligands. J Biomol Screen. 2009;14(6):700. [PMC free article] [PubMed]
21. Witola WH, et al. Disruption of the Plasmodium falciparum PfPMT gene results in a complete loss of phosphatidylcholine biosynthesis via the serine-decarboxylase-phosphoethanolamine-methyltransferase pathway and severe growth and survival defects. J Biol Chem. 2008;283(41):27636. [PMC free article] [PubMed]
22. Krnajski Z, et al. Thioredoxin reductase is essential for the survival of Plasmodium falciparum erythrocytic stages. J Biol Chem. 2002;277(29):25970. [PubMed]
23. McFadden GI, Roos DS. Apicomplexan plastids as drug targets. Trends Microbiol. 1999;7(8):328. [PubMed]
24. Reynolds MG, Roos DS. A biochemical and genetic model for parasite resistance to antifolates. Toxoplasma gondii provides insights into pyrimethamine and cycloguanil resistance in Plasmodium falciparum. J Biol Chem. 1998;273(6):3461. [PubMed]
25. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev. 2001;46(1-3):3. [PubMed]
26. Team, R. D. C. R: A language and environment for statistical computing. R Foundation for Statistical Computing; Vienna, Austria: 2009. Ritz C, Streibig JC. Bioassay Analysis using R. J Statist Software. 2005;12(5):22.
27. Shenai BR, et al. Structure-activity relationships for inhibition of cysteine protease activity and development of Plasmodium falciparum by peptidyl vinyl sulfones. Antimicrob Agents Chemother. 2003;47(1):154. [PMC free article] [PubMed]