Great progress has been made in recent years to reduce the high level of suffering caused by malaria worldwide. Notably, the use of insecticide-treated mosquito nets for malaria prevention and the use of artemisinin-based combination therapy (ACT) for malaria treatment have made a significant impact. Nevertheless, the development of resistance to the past and present anti-malarial drugs highlights the need for continued research to stay one step ahead. New drugs are needed, particularly those with new mechanisms of action. Here the range of anti-malarial medicines developed over the years are reviewed, beginning with the discovery of quinine in the early 1800s, through to modern day ACT and the recently-approved tafenoquine. A number of new potential anti-malarial drugs currently in development are outlined, along with a description of the hit to lead campaign from which it originated. Finally, promising novel mechanisms of action for these and future anti-malarial medicines are outlined.Electronic supplementary materialThe online version of this article (10.1186/s12936-019-2724-z) contains supplementary material, which is available to authorized users.

The hERG (human ether-a-go-go-related gene) encoded potassium ion (K+) channel plays a major role in cardiac repolarization. Drug-induced blockade of hERG has been a major cause of potentially lethal ventricular tachycardia termed Torsades de Pointes (TdPs). Therefore, we presented a pharmacoinformatics strategy using combined ligand and structure based models for the prediction of hERG inhibition potential (IC50) of new chemical entities (NCEs) during early stages of drug design and development. Integrated GRid-INdependent Descriptor (GRIND) models, and lipophilic efficiency (LipE), ligand efficiency (LE) guided template selection for the structure based pharmacophore models have been used for virtual screening and subsequent hERG activity (pIC50) prediction of identified hits. Finally selected two hits were experimentally evaluated for hERG inhibition potential (pIC50) using whole cell patch clamp assay. Overall, our results demonstrate a difference of less than ±1.6 log unit between experimentally determined and predicted hERG inhibition potential (IC50) of the selected hits. This revealed predictive ability and robustness of our models and could help in correctly rank the potency order (lower μM to higher nM range) against hERG.

The replacement of one chemical motif with another that is broadly similar is a common method in medicinal chemistry to modulate the physical and biological properties of a molecule (i.e., bioisosterism). In recent years, bioisosteres such as cubane and bicyclo[1.1.1]pentane (BCP) have been used as highly effective phenyl mimics. Herein, we show the successful incorporation of a range of phenyl bioisosteres during the opensource optimization of an antimalarial series. Cubane ( 19) and closo-carborane (23) analogues exhibited improved in vitro potency against Plasmodium falciparum compared to the parent phenyl compound; however, these changes resulted in a reduction in metabolic stability; unusually, enzyme-mediated oxidation was found to take place on the cubane core. A BCP analogue ( 22) was found to be equipotent to its parent phenyl compound and showed significantly improved metabolic properties. While these results demonstrate the utility of these atypical bioisosteres when used in a medicinal chemistry program, the search to find a suitable bioisostere may well require the preparation of many candidates, in our case, 32 compounds.

In only a matter of months, the coronavirus disease of 2019 (COVID-19) has spread around the world. The global impact of the disease has caused significant and repeated calls for quick action towards new medicines and vaccines. In response, researchers have adopted open science methods to begin to combat this disease via global collaborative efforts. We summarise here some of those initiatives, and have created an updateable list to which others may be added. Though open science has previously been shown as an accelerator of biomedical research, the COVID-19 crisis has made openness seem the logical choice. Will openness persist in the discovery of new medicines, after the crisis has receded?

The Open Source Malaria (OSM) consortium is developing compounds that kill the human malaria parasite, Plasmodium falciparum, by targeting PfATP4, an essential ion pump on the parasite surface. The structure of PfATP4 has not been determined. Here, we describe a public competition created to develop a predictive model for the identification of PfATP4 inhibitors, thereby reducing project costs associated with the synthesis of inactive compounds. Competition participants could see all entries as they were submitted. In the final round, featuring private sector entrants specializing in machine learning methods, the best-performing models were used to predict novel inhibitors, of which several were synthesized and evaluated against the parasite. Half possessed biological activity, with one featuring a motif that the human chemists familiar with this series would have dismissed as “ill-advised”. Since all data and participant interactions remain in the public domain, this research project “lives” and may be improved by others.

We have discovered and studied a telesubstitution reaction in a biologically important heterocyclic ring system. Conditions that favour the tele-substitution pathway were identified: the use of increased equivalents of the nucleophile or decreased equivalents of base, or the use of softer nucleophiles, less polar solvents and larger halogens on the electrophile. Using results from X-ray crystallographic and isotope labelling experiments, a mechanism for this unusual transformation is proposed. We focused on this triazolopyrazine as it is the core structure of the in vivo active anti-plasmodium compounds of Series 4 of the Open Source Malaria consortium.

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<p>The discovery of new antimalarial medicines with novel mechanisms of action is key to combating the problem of increasing resistance to our frontline treatments. The Open Source Malaria (OSM) consortium has been developing compounds ("Series 4") that have potent activity against <i>Plasmodium falciparum</i> <i>in vitro</i> and <i>in vivo</i> and that have been suggested to act through the inhibition of <i>Pf</i>ATP4, an essential membrane ion pump that regulates the parasite’s intracellular Na⁺ concentration. The structure of <i>Pf</i>ATP4 is yet to be determined. In the absence of structural information about this target, a public competition was created to develop a model that would allow the prediction of anti-<i>Pf</i>ATP4 activity among Series 4 compounds, thereby reducing project costs associated with the unnecessary synthesis of inactive compounds.</p>In the first round, in 2016, six participants used the open data collated by OSM to develop moderately predictive models using diverse methods. Notably, all submitted models were available to all other participants in real time. Since then further bioactivity data have been acquired and machine learning methods have rapidly developed, so a second round of the competition was undertaken, in 2019, again with freely-donated models that other participants could see. The best-performing models from this second round were used to predict novel inhibitory molecules, of which several were synthesised and evaluated against the parasite. One such compound, containing a motif that the human chemists familiar with this series would have dismissed as ill-advised, was active. The project demonstrated the abilities of new machine learning methods in the prediction of active compounds where there is no biological target structure, frequently the central problem in phenotypic drug discovery. Since all data and participant interactions remain in the public domain, this research project “lives” and may be improved by others.