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.

A major cause of the paucity of new starting points for drug discovery is the lack of interaction between academia and industry. Much of the global resource in biology is present in universities, whereas the focus of medicinal chemistry is still largely within industry. Open source drug discovery, with sharing of information, is clearly a first step towards overcoming this gap. But the interface could especially be bridged through a scale-up of open sharing of physical compounds, which would accelerate the finding of new starting points for drug discovery. The Medicines for Malaria Venture Malaria Box is a collection of over 400 compounds representing families of structures identified in phenotypic screens of pharmaceutical and academic libraries against the Plasmodium falciparum malaria parasite. The set has now been distributed to almost 200 research groups globally in the last two years, with the only stipulation that information from the screens is deposited in the public domain. This paper reports for the first time on 236 screens that have been carried out against the Malaria Box and compares these results with 55 assays that were previously published, in a format that allows a meta-analysis of the combined dataset. The combined biochemical and cellular assays presented here suggest mechanisms of action for 135 (34%) of the compounds active in killing multiple life-cycle stages of the malaria parasite, including asexual blood, liver, gametocyte, gametes and insect ookinete stages. In addition, many compounds demonstrated activity against other pathogens, showing hits in assays with 16 protozoa, 7 helminths, 9 bacterial and mycobacterial species, the dengue fever mosquito vector, and the NCI60 human cancer cell line panel of 60 human tumor cell lines. Toxicological, pharmacokinetic and metabolic properties were collected on all the compounds, assisting in the selection of the most promising candidates for murine proof-of-concept experiments and medicinal chemistry programs. The data for all of these assays are presented and analyzed to show how outstanding leads for many indications can be selected. These results reveal the immense potential for translating the dispersed expertise in biological assays involving human pathogens into drug discovery starting points, by providing open access to new families of molecules, and emphasize how a small additional investment made to help acquire and distribute compounds, and sharing the data, can catalyze drug discovery for dozens of different indications. Another lesson is that when multiple screens from different groups are run on the same library, results can be integrated quickly to select the most valuable starting points for subsequent medicinal chemistry efforts.

Significance Useful antimalarial drugs must be rapidly acting, highly efficacious, and have low potential for developing resistance. (+)-SJ733 targets a Plasmodium cation-transporting ATPase, ATP4. (+)-SJ733 cleared parasites in vivo as quickly as artesunate by specifically inducing eryptosis/senescence in infected, treated erythrocytes. Although in vitro selection of pfatp4 mutants with (+)-SJ733 proceeded with moderate frequency, during in vivo selection of pbatp4 mutants, resistance emerged slowly and produced marginally resistant mutants with poor fitness. In addition, (+)-SJ733 met all other criteria for a clinical candidate, including high oral bioavailability, a high safety margin, and transmission blocking activity. These results demonstrate that targeting ATP4 has great potential to deliver useful drugs for malaria eradication.

Malaria, a devastating infectious disease caused by Plasmodium spp., leads to roughly 655,000 deaths per year, mostly of African children. To compound the problem, drug resistance has emerged to all classical antimalarials and may be emerging for artemisinin-based combination therapies. To address the need for new antimalarials with novel mechanisms, several groups carried out phenotypic screening campaigns to identify compounds inhibiting growth of the blood stages of Plasmodium falciparum. In this review, we describe the characterization of these compounds, explore currently ongoing strategies to develop lead molecules, and endorse the concept of a “malaria box” of publicly accessible active compounds.

Malaria is a protozoal parasitic disease that is widespread in tropical and subtropical regions of Africa, Asia, and the Americas and causes more than 800,000 deaths per year. The continuing emergence of multi-drug-resistant Plasmodium falciparum drives the ongoing need for the development of new and effective antimalarial drugs. Our previous work has explored the preliminary structural optimization of 4(1H)-quinolone ester derivatives, a new series of antimalarials related to the endochins. Herein, we report the lead optimization of 4(1H)-quinolones with a focus on improving both antimalarial potency and bioavailability. These studies led to the development of orally efficacious antimalarials including quinolone analogue 20g, a promising candidate for further optimization.