Discovery of potent Plasmodium falciparum protein kinase 6 (PfPK6) inhibitors with a type II inhibitor pharmacophore

Biological evaluation as antimalarial of two families of biscationic compounds featuring two different sulphur linkers

Plasmodium falciparum kinases have been widely studied due to their potential as targets for the discovery of alternatives to artemisinin-combined therapies. Their role in parasite blood-stage replication and their homology with human kinases has led to the exploitation of already tested antitumoral kinase inhibitors as antiplasmodial drugs. Plasmodium falciparum choline kinase (PfCK), a cytosolic enzyme involved in phospholipid synthesis, is a promising target for parasite resistant strains. PfCK uses the host choline and catalyzes its transformation in phosphocholine, a key step for the formation of the lipid membranes required by the new parasite progeny inside the erythrocyte. Previously, we described the synthesis of two libraries (PL and FP) of human choline kinase (hCK) inhibitors, which we generated following a green by design approach. Some of these compounds were found to exhibit antitumoral properties. Here, we evaluated the same compounds as potential inhibitors of PfCK and antimalarial agents. Interestingly, while the compounds of the FP library, which feature a disulphide linker, show PfCK inhibition in the nM range independently of the cationic head (FP3 being the most active compound, PfCK IC50 = 0.16 μM), they show no effect on infected erythrocytes. On the other hand, the compounds of the PL library, which feature a dithioethane linker, show in vitro activity against the parasite but no inhibitory activity against the isolated enzyme (PL40 exhibits the highest antimalarial activity, with IC50 = 10 nM). This lack of correlation could be due to either cellular disulphide degradation in vitro or to the existence of alternative targets for the dithioethane library. Considering the previously reported anticancer potential of the PL family and the antiparasitic activity reported herein, these compounds may be considered as good starting points for the development of multifunctional drugs.

Identification of therapeutics against PfPK6 protein of Plasmodium falciparum: Structure and Deep Learning approach

The Plasmodium falciparum Protein Kinase 6 (PfPK6) is a serine/threonine protein kinase categorized under the CMGC group, displaying both cyclin-dependent kinases (CDKs) and mitogen-activated protein kinases (MAPKs) activity. Previous research has indicated that PfPK6 is expressed during the trophozoite and schizont stages of the Plasmodium falciparum asexual blood stage. Unlike typical cyclin-dependent kinases, PfPK6 demonstrates kinase activity independent of cyclin, making it a promising target for drug identification. In this study, we utilized a computational approach to identify a novel PfPK6 inhibitor through virtual screening of small inhibitor compounds from diverse datasets, employing a structure-based approach and a Deep Learning (DL) model. The most promising inhibitor molecule, TCMDC-132409 from the Tres Cantos Antimalarial Set, exhibited a binding affinity of -13.553 kcal/mol against PfPK6. Additionally, a 200ns molecular dynamics simulation study confirmed the stability of the binding mode, indicating the potential of TCMDC-132409 as an antiplasmodial inhibitor for further investigation.

Advancing antimalarial drug discovery: ensemble machine learning models for predicting PfPK6 inhibitor activity

Malaria is a significant global health challenge, causing high morbidity and mortality. The rise of drug resistance highlights the urgent need for new antimalarial agents. This study focuses on predictive modeling of 104 Plasmodium falciparum protein kinase 6 (PfPK6) inhibitors, employing a range of machine learning techniques to develop ensemble regression and classification models. Molecular descriptors were refined using classification and regression trees (CART) to identify the most relevant features. Six machine learning algorithms (Random Forest (RF), Relevance Vector Machine (RVM), Support Vector Machine (SVM), Cubist, Artificial Neural Networks (ANN), and XGBoost) were utilized to construct regression models. The consensus model demonstrated superior predictive performance, achieving R2Test = 0.94, SETest = 0.20, Q2CV = 0.90, and SECV = 0.25, outperforming individual models. For classification tasks, five algorithms were evaluated and a majority voting approach yielded an accuracy of 91% and a sensitivity of 93%. The robustness of the models was confirmed through applicability domain analysis (96% coverage) and y-randomization tests, ensuring that the predictive outcomes were not due to chance correlations. This study highlights the effectiveness of ensemble machine learning approaches in predictive modeling and provides critical insights for the rational design of novel PfPK6 inhibitors.

Towards next-generation treatment options to combat Plasmodium falciparum malaria

Malaria, which is caused by infection of red blood cells with Plasmodium parasites, can be fatal in non-immune individuals if left untreated. The recent approval of the pre-erythrocytic vaccines RTS, S/AS01 and R21/Matrix-M has ushered in hope of substantial reductions in mortality rates, especially when combined with other existing interventions. However, the efficacy of these vaccines is partial, and chemotherapy remains central to malaria treatment and control. For many antimalarial drugs, clinical efficacy has been compromised by the emergence of drug-resistant Plasmodium falciparum strains. Therefore, there is an urgent need for new antimalarial medicines to complement the existing first-line artemisinin-based combination therapies. In this Review, we discuss various opportunities to expand the present malaria treatment space, appraise the current antimalarial drug development pipeline and highlight examples of promising targets. We also discuss other approaches to circumvent antimalarial resistance and how potency against drug-resistant parasites could be retained.

Discovery of Potent Antimalarial Type II Kinase Inhibitors with Selectivity over Human Kinases

While progress has been made in the effort to eradicate malaria, the disease remains a significant threat to global health. Acquired resistance to frontline treatments is emerging in Africa, urging a need for the development of novel antimalarial agents. Repurposing human kinase inhibitors provides a potential expedited route given the availability of a diverse array of kinase-targeting drugs that are approved or in clinical trials. Phenotypic screening of a library of type II human kinase inhibitors identified compound 1 as a lead antimalarial, which was initially developed to target human ephrin type A receptor 2 (EphA2). Here, we report a structure-activity relationship study and lead optimization of compound 1, which led to compound 33, with improved antimalarial activity and selectivity.

Characterization of 2,4-Dianilinopyrimidines Against Five P. falciparum Kinases PfARK1, PfARK3, PfNEK3, PfPK9, and PfPKB

Plasmodium kinases are increasingly recognized as potential novel antiplasmodial targets for the treatment of malaria, but only a small subset of these kinases have had structure-activity relationship (SAR) campaigns reported. Herein we report the discovery of CZC-54252 (1) as an inhibitor of five P. falciparum kinases PfARK1, PfARK3, PfNEK3, PfPK9, and PfPKB. 39 analogues were evaluated against all five kinases to establish SAR at three regions of the kinase active site. Nanomolar inhibitors of each kinase were discovered. We identified common and divergent SAR trends across all five kinases, highlighting substituents in each region that improve potency and selectivity for each kinase. Potent analogues were evaluated against the P. falciparum blood stage. Eight submicromolar inhibitors were discovered, of which 37 demonstrated potent antiplasmodial activity (EC50 = 0.16 μM). Our results provide an understanding of features needed to inhibit each individual kinase and lay groundwork for future optimization efforts toward novel antimalarials.

How many kinases are druggable? A review of our current understanding

There are over 500 human kinases ranging from very well-studied to almost completely ignored. Kinases are tractable and implicated in many diseases, making them ideal targets for medicinal chemistry campaigns, but is it possible to discover a drug for each individual kinase? For every human kinase, we gathered data on their citation count, availability of chemical probes, approved and investigational drugs, PDB structures, and biochemical and cellular assays. Analysis of these factors highlights which kinase groups have a wealth of information available, and which groups still have room for progress. The data suggest a disproportionate focus on the more well characterized kinases while much of the kinome remains comparatively understudied. It is noteworthy that tool compounds for understudied kinases have already been developed, and there is still untapped potential for further development in this chemical space. Finally, this review discusses many of the different strategies employed to generate selectivity between kinases. Given the large volume of information available and the progress made over the past 20 years when it comes to drugging kinases, we believe it is possible to develop a tool compound for every human kinase. We hope this review will prove to be both a useful resource as well as inspire the discovery of a tool for every kinase.

Roles of Virtual Screening and Molecular Dynamics Simulations in Discovering and Understanding Antimalarial Drugs

Malaria continues to be a global health threat, with approximately 247 million cases worldwide. Despite therapeutic interventions being available, patient compliance is a problem due to the length of treatment. Moreover, drug-resistant strains have emerged over the years, necessitating urgent identification of novel and more potent treatments. Given that traditional drug discovery often requires a great deal of time and resources, most drug discovery efforts now use computational methods. In silico techniques such as quantitative structure-activity relationship (QSAR), docking, and molecular dynamics (MD) can be used to study protein-ligand interactions and determine the potency and safety profile of a set of candidate compounds to help prioritize those tested using assays and animal models. This paper provides an overview of antimalarial drug discovery and the application of computational methods in identifying candidate inhibitors and elucidating their potential mechanisms of action. We conclude with the continued challenges and future perspectives in the field of antimalarial drug discovery.

Parasite and host kinases as targets for antimalarials

INTRODUCTION

The deployment of Artemisinin-based combination therapies and transmission control measures led to a decrease in the global malaria burden over the recent decades. Unfortunately, this trend is now reversing, in part due to resistance against available treatments, calling for the development of new drugs against untapped targets to prevent cross-resistance.

AREAS COVERED

In view of their demonstrated druggability in noninfectious diseases, protein kinases represent attractive targets. Kinase-focussed antimalarial drug discovery is facilitated by the availability of kinase-targeting scaffolds and large libraries of inhibitors, as well as high-throughput phenotypic and biochemical assays. We present an overview of validated Plasmodium kinase targets and their inhibitors, and briefly discuss the potential of host cell kinases as targets for host-directed therapy.

EXPERT OPINION

We propose priority research areas, including (i) diversification of Plasmodium kinase targets (at present most efforts focus on a very small number of targets); (ii) polypharmacology as an avenue to limit resistance (kinase inhibitors are highly suitable in this respect); and (iii) preemptive limitation of resistance through host-directed therapy (targeting host cell kinases that are required for parasite survival) and transmission-blocking through targeting sexual stage-specific kinases as a strategy to protect curative drugs from the spread of resistance.