Prediction of the P. falciparum target space relevant to malaria drug discovery

The Medicines for Malaria Venture Malaria Box contains inhibitors of protein secretion in Plasmodium falciparum blood stage parasites

Plasmodium falciparum parasites which cause malaria, traffic hundreds of proteins into the red blood cells (RBCs) they infect. These exported proteins remodel their RBCs enabling host immune evasion through processes such as cytoadherence that greatly assist parasite survival. As resistance to all current antimalarial compounds is rising new compounds need to be identified and those that could inhibit parasite protein secretion and export would both rapidly reduce parasite virulence and ultimately lead to parasite death. To identify compounds that inhibit protein export we used transgenic parasites expressing an exported nanoluciferase reporter to screen the Medicines for Malaria Venture Malaria Box of 400 antimalarial compounds with mostly unknown targets. The most potent inhibitor identified in this screen was MMV396797 whose application led to export inhibition of both the reporter and endogenous exported proteins. MMV396797 mediated blockage of protein export and slowed the rigidification and cytoadherence of infected RBCs—modifications which are both mediated by parasite‐derived exported proteins. Overall, we have identified a new protein export inhibitor in P. falciparum whose target though unknown, could be developed into a future antimalarial that rapidly inhibits parasite virulence before eliminating parasites from the host.

Targeting the Plasmodium falciparum’s Thymidylate Monophosphate Kinase for the Identification of Novel Antimalarial Natural Compounds

Recent reports of resistance to artemisinin-based combination drugs necessitate the need to discover novel antimalarial compounds. The present study was aimed at identifying novel antimalarial compounds from natural product libraries using computational methods. Plasmodium falciparum is highly dependent on the pyrimidine biosynthetic pathway, a de novo pathway responsible for the production of pyrimidines, and the parasite lacks the pyrimidine salvage enzymes. The P. falciparum thymidylate monophosphate kinase (PfTMPK) is an important protein necessary for rapid DNA replication; however, due to its broad substrate specificity, the protein is distinguished from its homologs, making it a suitable drug target. Compounds from AfroDB, a database of natural products originating from Africa, were screened virtually against PfTMPK after filtering the compounds for absorption, distribution, metabolism, excretion, and toxicity (ADMET)-acceptable compounds with FAF-Drugs4. Thirteen hits with lower binding energies than thymidine monophosphate were selected after docking. Among the thirteen compounds, ZINC13374323 and ZINC13365918 with binding energies of −9.4 and −8.9 kcal/mol, respectively, were selected as plausible lead compounds because they exhibited structural properties that ensure proper binding at the active site and inhibitory effect against PfTMPK. ZINC13374323 (also called aurantiamide acetate) is known to exhibit anti-inflammatory and antiviral activities, and ZINC13365918 exhibits antileishmanial activity. Furthermore, aurantiamide acetate, which is commercially available, is a constituent of Artemisia annua, the herb from which artemisinin was derived. The compound also shares interactions with several residues with a potent thymidine analog inhibitor of PfTMPK. The anti-plasmodial activity of aurantiamide acetate was evaluated in vitro, and the mean half-maximal inhibitory concentration (IC50) was 69.33 μM when synchronized P. falciparum 3D7 culture was used as compared to IC50 > 100 μM with asynchronized culture. The significance of our findings within the context of malaria treatment strategies and challenges is discussed.

High-content phenotypic and pathway profiling to advance drug discovery in diseases of unmet need

Conventional thinking in modern drug discovery postulates that the design of highly selective molecules which act on a single disease-associated target will yield safer and more effective drugs. However, high clinical attrition rates and the lack of progress in developing new effective treatments for many important diseases of unmet therapeutic need challenge this hypothesis. This assumption also impinges upon the efficiency of target agnostic phenotypic drug discovery strategies, where early target deconvolution is seen as a critical step to progress phenotypic hits. In this review we provide an overview of how emerging phenotypic and pathway-profiling technologies integrate to deconvolute the mechanism-of-action of phenotypic hits. We propose that such in-depth mechanistic profiling may support more efficient phenotypic drug discovery strategies that are designed to more appropriately address complex heterogeneous diseases of unmet need.

Targeting malaria protein kinases

Malaria is one of the most impacting public health problems in tropical and subtropical areas of the globe, with approximately 200 million cases worldwide annually. In the absence of an effective vaccine, rapid treatment is vital for effective malaria control. However, parasite resistance to currently available drugs underscores the urgent need for identifying new antimalarial therapies with new mechanisms of action. Among potential drug targets for developing new antimalarial candidates, protein kinases are attractive. These enzymes catalyze the phosphorylation of several proteins, thereby regulating a variety of cellular processes and playing crucial roles in the development of all stages of the malaria parasite life cycle. Moreover, the large phylogenetic distance between Plasmodium species and its human host is reflected in marked differences in structure and function of malaria protein kinases between the homologs of both species, indicating that selectivity can be attained. In this review, we describe the functions of the different types of Plasmodium kinases and highlight the main recent advances in the discovery of kinase inhibitors as potential new antimalarial drug candidates.

Closing the Gap Between Therapeutic Use and Mode of Action in Remedial Herbs

The ancient tradition of taking parts of a plant or preparing plant extracts for treating certain discomforts and maladies has long been lacking a scientific rationale to support its preparation and still widespread use in several parts of the world. In an attempt to address this challenge, we collected and integrated data connecting metabolites, plants, diseases, and proteins. A mechanistic hypothesis is generated when a metabolite is known to be present in a given plant, that plant is known to be used to treat a certain disease, that disease is known to be linked to the function of a given protein, and that protein is finally known or predicted to interact with the original metabolite. The construction of plant–protein networks from mutually connected metabolites and diseases facilitated the identification of plausible mechanisms of action for plants being used to treat analgesia, hypercholesterolemia, diarrhea, catarrh, and cough. Additional concrete examples using both experimentally known and computationally predicted, and subsequently experimentally confirmed, metabolite–protein interactions to close the connection circle between metabolites, plants, diseases, and proteins offered further proof of concept for the validity and scope of the approach to generate mode of action hypotheses for some of the therapeutic uses of remedial herbs.

Novel Computational Approach to Predict Off-Target Interactions for Small Molecules

Most small molecule drugs interact with unintended, often unknown, biological targets and these off-target interactions may lead to both preclinical and clinical toxic events. Undesired off-target interactions are often not detected using current drug discovery assays, such as experimental polypharmacological screens. Thus, improvement in the early identification of off-target interactions represents an opportunity to reduce safety-related attrition rates during preclinical and clinical development. In order to better identify potential off-target interactions that could be linked to predictable safety issues, a novel computational approach to predict safety-relevant interactions currently not covered was designed and evaluated. These analyses, termed Off-Target Safety Assessment (OTSA), cover more than 7,000 targets (~35% of the proteome) and > 2,46,704 preclinical and clinical alerts (as of January 20, 2019). The approach described herein exploits a highly curated training set of >1 million compounds (tracking >20 million compound-structure activity relationship/SAR data points) with known in vitro activities derived from patents, journals, and publicly available databases. This computational process was used to predict both the primary and secondary pharmacological activities for a selection of 857 diverse small molecule drugs for which extensive secondary pharmacology data are readily available (456 discontinued and 401 FDA approved). The OTSA process predicted a total of 7,990 interactions for these 857 molecules. Of these, 3,923 and 4,067 possible high-scoring interactions were predicted for the discontinued and approved drugs, respectively, translating to an average of 9.3 interactions per drug. The OTSA process correctly identified the known pharmacological targets for >70% of these drugs, but also predicted a significant number of off-targets that may provide additional insight into observed in vivo effects. About 51.5% (2,025) and 22% (900) of these predicted high-scoring interactions have not previously been reported for the discontinued and approved drugs, respectively, and these may have a potential for repurposing efforts. Moreover, for both drug categories, higher promiscuity was observed for compounds with a MW range of 300 to 500, TPSA of ~200, and clogP ≥7. This computation also revealed significantly lower promiscuity (i.e., number of confirmed off-targets) for compounds with MW > 700 and MW<200 for both categories. In addition, 15 internal small molecules with known off-target interactions were evaluated. For these compounds, the OTSA framework not only captured about 56.8% of in vitro confirmed off-target interactions, but also identified the right pharmacological targets for 14 compounds as one of the top scoring targets. In conclusion, the OTSA process demonstrates good predictive performance characteristics and represents an additional tool with utility during the lead optimization stage of the drug discovery process. Additionally, the computed physiochemical properties such as clogP (i.e., lipophilicity), molecular weight, pKa and logS (i.e., solubility) were found to be statistically different between the approved and discontinued drugs, but the internal compounds were close to the approved drugs space in most part.

Functional analysis of Plasmodium falciparum subpopulations associated with artemisinin resistance in Cambodia

Background

Plasmodium falciparum malaria is one of the most widespread parasitic infections in humans and remains a leading global health concern. Malaria elimination efforts are threatened by the emergence and spread of resistance to artemisinin-based combination therapy, the first-line treatment of malaria. Promising molecular markers and pathways associated with artemisinin drug resistance have been identified, but the underlying molecular mechanisms of resistance remains unknown. The genomic data from early period of emergence of artemisinin resistance (2008–2011) was evaluated, with aim to define k13 associated genetic background in Cambodia, the country identified as epicentre of anti-malarial drug resistance, through characterization of 167 parasite isolates using a panel of 21,257 SNPs.

Results

Eight subpopulations were identified suggesting a process of acquisition of artemisinin resistance consistent with an emergence-selection-diffusion model, supported by the shifting balance theory. Identification of population specific mutations facilitated the characterization of a core set of 57 background genes associated with artemisinin resistance and associated pathways. The analysis indicates that the background of artemisinin resistance was not acquired after drug pressure, rather is the result of fixation followed by selection on the daughter subpopulations derived from the ancestral population.

Conclusions

Functional analysis of artemisinin resistance subpopulations illustrates the strong interplay between ubiquitination and cell division or differentiation in artemisinin resistant parasites. The relationship of these pathways with the P. falciparum resistant subpopulation and presence of drug resistance markers in addition to k13, highlights the major role of admixed parasite population in the diffusion of artemisinin resistant background. The diffusion of resistant genes in the Cambodian admixed population after selection resulted from mating of gametocytes of sensitive and resistant parasite populations.

Electronic supplementary material

The online version of this article (10.1186/s12936-017-2140-1) contains supplementary material, which is available to authorized users.

Decoding the Role of Glycans in Malaria

Complications arising from malaria are a concern for public health authorities worldwide, since the annual caseload in humans usually exceeds millions. Of more than 160 species of Plasmodium, only 4 infect humans, with the most severe cases ascribed to Plasmodium falciparum and the most prevalent to Plasmodium vivax. Over the past 70 years, since World War II, when the first antimalarial drugs were widely used, many efforts have been made to combat this disease, including vectorial control, new drug discoveries and genetic and molecular approaches. Molecular approaches, such as glycobiology, may lead to new therapeutic targets (both in the host and the parasites), since all interactions are mediated by carbohydrates or glycan moieties decorating both cellular surfaces from parasite and host cells. In this review, we address the carbohydrate-mediated glycobiology that directly affects Plasmodium survival or host resistance.

QSAR modeling and chemical space analysis of antimalarial compounds

Generative topographic mapping (GTM) has been used to visualize and analyze the chemical space of antimalarial compounds as well as to build predictive models linking structure of molecules with their antimalarial activity. For this, a database, including ~3000 molecules tested in one or several of 17 anti-Plasmodium activity assessment protocols, has been compiled by assembling experimental data from in-house and ChEMBL databases. GTM classification models built on subsets corresponding to individual bioassays perform similarly to the earlier reported SVM models. Zones preferentially populated by active and inactive molecules, respectively, clearly emerge in the class landscapes supported by the GTM model. Their analysis resulted in identification of privileged structural motifs of potential antimalarial compounds. Projection of marketed antimalarial drugs on this map allowed us to delineate several areas in the chemical space corresponding to different mechanisms of antimalarial activity. This helped us to make a suggestion about the mode of action of the molecules populating these zones.

Discovery of a New Class of Cathepsin K Inhibitors in Rhizoma Drynariae as Potential Candidates for the Treatment of Osteoporosis

Rhizoma Drynariae (RD), as one of the most common clinically used folk medicines, has been reported to exert potent anti-osteoporotic activity. The bioactive ingredients and mechanisms that account for its bone protective effects are under active investigation. Here we adopt a novel in silico target fishing method to reveal the target profile of RD. Cathepsin K (Ctsk) is one of the cysteine proteases that is over-expressed in osteoclasts and accounts for the increase in bone resorption in metabolic bone disorders such as postmenopausal osteoporosis. It has been the focus of target based drug discovery in recent years. We have identified two components in RD, Kushennol F and Sophoraflavanone G, that can potentially interact with Ctsk. Biological studies were performed to verify the effects of these compounds on Ctsk and its related bone resorption process, which include the use of in vitro fluorescence-based Ctsk enzyme assay, bone resorption pit formation assay, as well as Receptor Activator of Nuclear factor κB (NF-κB) ligand (RANKL)-induced osteoclastogenesis using murine RAW264.7 cells. Finally, the binding mode and stability of these two compounds that interact with Ctsk were determined by molecular docking and dynamics methods. The results showed that the in silico target fishing method could successfully identify two components from RD that show inhibitory effects on the bone resorption process related to protease Ctsk.

Plasmodium falciparum Cyclic Amine Resistance Locus (PfCARL), a Resistance Mechanism for Two Distinct Compound Classes

MMV007564 is a novel antimalarial benzimidazolyl piperidine chemotype identified in cellular screens. To identify the genetic determinant of MMV007564 resistance, parasites were cultured in the presence of the compound to generate resistant lines. Whole genome sequencing revealed distinct mutations in the gene named Plasmodium falciparum cyclic amine resistance locus (pfcarl), encoding a conserved protein of unknown function. Mutations in pfcarl are strongly associated with resistance to a structurally unrelated class of compounds, the imidazolopiperazines, including KAF156, currently in clinical trials. Our data demonstrate that pfcarl mutations confer resistance to two distinct compound classes, benzimidazolyl piperidines and imidazolopiperazines. However, MMV007564 and the imidazolopiperazines, KAF156 and GNF179, have different timings of action in the asexual blood stage and different potencies against the liver and sexual blood stages. These data suggest that pfcarl is a multidrug-resistance gene rather than a common target for benzimidazolyl piperidines and imidazolopiperazines.

Open Source Drug Discovery with the Malaria Box Compound Collection for Neglected Diseases and Beyond

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.

Malaria leads to the loss of over 440,000 lives annually; accelerating research to discover new candidate drugs is a priority. Medicines for Malaria Venture (MMV) has distilled over 25,000 compounds that kill malaria parasites in vitro into a group of 400 representative compounds, called the "Malaria Box". These Malaria Box sets were distributed free-of-charge to research laboratories in 30 different countries that work on a wide variety of pathogens. Fifty-five groups compiled >290 assay results for this paper describing the many activities of the Malaria Box compounds. The collective results suggest a potential mechanism of action for over 130 compounds against malaria and illuminate the most promising compounds for further malaria drug development research. Excitingly some of these compounds also showed outstanding activity against other disease agents including fungi, bacteria, other single-cellular parasites, worms, and even human cancer cells. The results have ignited over 30 drug development programs for a variety of diseases. This open access effort was so successful that MMV has begun to distribute another set of compounds with initial activity against a wider range of infectious agents that are of public health concern, called the Pathogen Box, available now to scientific labs all over the world (www.PathogenBox.org).

Polypharmacology: in silico methods of ligand design and development

How to design a ligand to bind multiple targets, rather than to a single target, is the focus of this review. Rational polypharmacology draws on knowledge that is both broad ranging and hierarchical. Computer-aided multitarget ligand design methods are described according to their nested knowledge level. Ligand-only and then receptor-ligand strategies are first described; followed by the metabolic network viewpoint. Subsequently strategies that view infectious diseases as multigenomic targets are discussed, and finally the disease level interpretation of medicinal therapy is considered. As yet there is no consensus on how best to proceed in designing a multitarget ligand. The current methodologies are bought together in an attempt to give a practical overview of how polypharmacology design might be best initiated.

Structure Based Docking and Molecular Dynamic Studies of Plasmodial Cysteine Proteases against a South African Natural Compound and its Analogs

Identification of potential drug targets as well as development of novel antimalarial chemotherapies with unique mode of actions due to drug resistance by Plasmodium parasites are inevitable. Falcipains (falcipain-2 and falcipain-3) of Plasmodium falciparum, which catalyse the haemoglobin degradation process, are validated drug targets. Previous attempts to develop peptide based drugs against these enzymes have been futile due to the poor pharmacological profiles and susceptibility to degradation by host enzymes. This study aimed to identify potential non-peptide inhibitors against falcipains and their homologs from other Plasmodium species. Structure based virtual docking approach was used to screen a small non-peptidic library of natural compounds from South Africa against 11 proteins. A potential hit, 5α-Pregna-1,20-dien-3-one (5PGA), with inhibitory activity against plasmodial proteases and selectivity on human cathepsins was identified. A 3D similarity search on the ZINC database using 5PGA identified five potential hits based on their docking energies. The key interacting residues of proteins with compounds were identified via molecular dynamics and free binding energy calculations. Overall, this study provides a basis for further chemical design for more effective derivatives of these compounds. Interestingly, as these compounds have cholesterol-like nuclei, they and their derivatives might be well tolerated in humans.

Resisting resistance: is there a solution for malaria?

INTRODUCTION

Currently, widely used antimalarial drugs have a limited clinical lifespan due to parasite resistance development. With resistance continuously rising, antimalarial drug discovery requires strategies to decrease the time of delivering a new antimalarial drug while simultaneously increasing the drug's therapeutic lifespan. Lessons learnt from various chemotherapeutic resistance studies in the fields of antibiotic and cancer research offer potentially useful strategies that can be applied to antimalarial drug discovery.

AREAS COVERED

In this review the authors discuss current strategies to circumvent resistance in malaria and alternatives that could be employed.

EXPERT OPINION

Scientists have been 'beating back' the malaria parasite with novel drugs for the past 49 years but the constant rise in antimalarial drug resistance is forcing the drug discovery community to explore alternative strategies. Avant-garde anti-resistance strategies from alternative fields may assist our endeavors to manage, control and prevent antimalarial drug resistance to progress beyond beating the resistant parasite back, to stopping it dead in its tracks.

Screening of potential targets in Plasmodium falciparum using stage-specific metabolic network analysis

The Apicomplexa parasite Plasmodium is a major cause of death in developing countries which are less equipped to bring new medicines to the market. Currently available drugs used for treatment of malaria are limited either by inadequate efficacy, toxicity and/or increased resistance. Availability of the genome sequence, microarray data and metabolic profile of Plasmodium parasite offers an opportunity for the identification of stage-specific genes important to the organism's lifecycle. In this study, microarray data were analysed for differential expression and overlapped onto metabolic pathways to identify differentially regulated pathways essential for transition to successive erythrocytic stages. The results obtained indicate that S-adenosylmethionine decarboxylase/ornithine decarboxylase, a bifunctional enzyme required for polyamine synthesis, is important for the Plasmodium cell growth in the absence of exogenous polyamines. S-adenosylmethionine decarboxylase/ornithine decarboxylase is a valuable target for designing therapeutically useful inhibitors. One such inhibitor, [Formula: see text]-difluoromethyl ornithine, is currently in use for the treatment of African sleeping sickness caused by Trypanosoma brucei. Structural studies of ornithine decarboxylase along with known inhibitors and their analogues were carried out to screen drug databases for more effective and less toxic compounds.

Bayesian models trained with HTS data for predicting β-haematin inhibition and in vitro antimalarial activity

A large quantity of high throughput screening (HTS) data for antimalarial activity has become available in recent years. This includes both phenotypic and target-based activity. Realising the maximum value of these data remains a challenge. In this respect, methods that allow such data to be used for virtual screening maximise efficiency and reduce costs. In this study both in vitro antimalarial activity and inhibitory data for β-haematin formation, largely obtained from publically available sources, has been used to develop Bayesian models for inhibitors of β-haematin formation and in vitro antimalarial activity. These models were used to screen two in silico compound libraries. In the first, the 1510 U.S. Food and Drug Administration approved drugs available on PubChem were ranked from highest to lowest Bayesian score based on a training set of β-haematin inhibiting compounds active against Plasmodium falciparum that did not include any of the clinical antimalarials or close analogues. The six known clinical antimalarials that inhibit β-haematin formation were ranked in the top 2.1% of compounds. Furthermore, the in vitro antimalarial hit-rate for this prioritised set of compounds was found to be 81% in the case of the subset where activity data are available in PubChem. In the second, a library of about 5000 commercially available compounds (Aldrich(CPR)) was virtually screened for ability to inhibit β-haematin formation and then for in vitro antimalarial activity. A selection of 34 compounds was purchased and tested, of which 24 were predicted to be β-haematin inhibitors. The hit rate for inhibition of β-haematin formation was found to be 25% and a third of these were active against P. falciparum, corresponding to enrichments estimated at about 25- and 140-fold relative to random screening, respectively.

Proteochemometric modelling coupled to in silico target prediction: an integrated approach for the simultaneous prediction of polypharmacology and binding affinity/potency of small molecules

The rampant increase of public bioactivity databases has fostered the development of computational chemogenomics methodologies to evaluate potential ligand-target interactions (polypharmacology) both in a qualitative and quantitative way. Bayesian target prediction algorithms predict the probability of an interaction between a compound and a panel of targets, thus assessing compound polypharmacology qualitatively, whereas structure-activity relationship techniques are able to provide quantitative bioactivity predictions. We propose an integrated drug discovery pipeline combining in silico target prediction and proteochemometric modelling (PCM) for the respective prediction of compound polypharmacology and potency/affinity. The proposed pipeline was evaluated on the retrospective discovery of Plasmodium falciparum DHFR inhibitors. The qualitative in silico target prediction model comprised 553,084 ligand-target associations (a total of 262,174 compounds), covering 3,481 protein targets and used protein domain annotations to extrapolate predictions across species. The prediction of bioactivities for plasmodial DHFR led to a recall value of 79% and a precision of 100%, where the latter high value arises from the structural similarity of plasmodial DHFR inhibitors and T. gondii DHFR inhibitors in the training set. Quantitative PCM models were then trained on a dataset comprising 20 eukaryotic, protozoan and bacterial DHFR sequences, and 1,505 distinct compounds (in total 3,099 data points). The most predictive PCM model exhibited R²_0test and RMSE_test values of 0.79 and 0.59 pIC₅₀ units respectively, which was shown to outperform models based exclusively on compound (R²_0test/RMSE_test = 0.63/0.78) and target information (R²_0test/RMSE_test = 0.09/1.22), as well as inductive transfer knowledge between targets, with respective R²_0test and RMSE_test values of 0.76 and 0.63 pIC₅₀ units. Finally, both methods were integrated to predict the protein targets and the potency on plasmodial DHFR for the GSK TCAMS dataset, which comprises 13,533 compounds displaying strong anti-malarial activity. 534 of those compounds were identified as DHFR inhibitors by the target prediction algorithm, while the PCM algorithm identified 25 compounds, and 23 compounds (predicted pIC₅₀ > 7) were identified by both methods. Overall, this integrated approach simultaneously provides target and potency/affinity predictions for small molecules.

Graphical abstract

Identification of inhibitors of Plasmodium falciparum RuvB1 helicase using biochemical assays

Human malaria is a major parasitic infection, and the situation has worsened mainly due to the emergence of resistant malaria parasites to several anti-malarial drugs. Thus, an urgent need to find suitable drug targets has led to the development of newer classes of anti-malarial drugs. Helicases have been targeted to develop therapeutics for viral, bacterial, and other microorganism infections. Recently, Plasmodium falciparum RuvB ATPases/helicases have been characterized and proposed as a suitable antimalarial drug target. In the present study, the screening of various compounds was done and the results suggest that PfRuvB1 ATPase activity is inhibited considerably by the novobiocin and partially by cisplatin and ciprofloxacin. Helicase assay of PfRuvB1 in the presence of various compounds suggest novobiocin, actinomycin, and ethidium bromide as potent inhibitors. Novobiocin inhibits the helicase activity of PfRuvB1 possibly by blocking the ATPase activity of PfRuvB1. This study is unique in respect to the identification of novobiocin as inhibitor of PfRuvB1, partially by competing with ATP binding at its active site and provides evidence for PfRuvB1 as target of novobiocin after DNA gyrase-B and HSP90. These studies will certainly help the pharmacologist to design and develop some novel inhibitor specific to PfRuvB1, which may serve as suitable chemotherapeutics to target malaria.

Deorphaning pyrrolopyrazines as potent multi-target antimalarial agents

The discovery of pyrrolopyrazines as potent antimalarial agents is presented, with the most effective compounds exhibiting EC50 values in the low nanomolar range against asexual blood stages of Plasmodium falciparum in human red blood cells, and Plasmodium berghei liver schizonts, with negligible HepG2 cytotoxicity. Their potential mode of action is uncovered by predicting macromolecular targets through avant-garde computer modeling. The consensus prediction method suggested a functional resemblance between ligand binding sites in non-homologous target proteins, linking the observed parasite elimination to IspD, an enzyme from the non-mevalonate pathway of isoprenoid biosynthesis, and multi-kinase inhibition. Further computational analysis suggested essential P. falciparum kinases as likely targets of our lead compound. The results obtained validate our methodology for ligand- and structure-based target prediction, expand the bioinformatics toolbox for proteome mining, and provide unique access to deciphering polypharmacological effects of bioactive chemical agents.

Towards structural systems pharmacology to study complex diseases and personalized medicine

Genome-Wide Association Studies (GWAS), whole genome sequencing, and high-throughput omics techniques have generated vast amounts of genotypic and molecular phenotypic data. However, these data have not yet been fully explored to improve the effectiveness and efficiency of drug discovery, which continues along a one-drug-one-target-one-disease paradigm. As a partial consequence, both the cost to launch a new drug and the attrition rate are increasing. Systems pharmacology and pharmacogenomics are emerging to exploit the available data and potentially reverse this trend, but, as we argue here, more is needed. To understand the impact of genetic, epigenetic, and environmental factors on drug action, we must study the structural energetics and dynamics of molecular interactions in the context of the whole human genome and interactome. Such an approach requires an integrative modeling framework for drug action that leverages advances in data-driven statistical modeling and mechanism-based multiscale modeling and transforms heterogeneous data from GWAS, high-throughput sequencing, structural genomics, functional genomics, and chemical genomics into unified knowledge. This is not a small task, but, as reviewed here, progress is being made towards the final goal of personalized medicines for the treatment of complex diseases.

Plasmodium falciparum UvrD activities are downregulated by DNA-interacting compounds and its dsRNA inhibits malaria parasite growth

Background

Human malaria parasite infection and its control is a global challenge which is responsible for ~0.65 million deaths every year globally. The emergence of drug resistant malaria parasite is another challenge to fight with malaria. Enormous efforts are being made to identify suitable drug targets in order to develop newer classes of drug. Helicases play crucial roles in DNA metabolism and have been proposed as therapeutic targets for cancer therapy as well as viral and parasitic infections. Genome wide analysis revealed that Plasmodium falciparum possesses UvrD helicase, which is absent in the human host.

Results

Recently the biochemical characterization of P. falciparum UvrD helicase revealed that N-terminal UvrD (PfUDN) hydrolyses ATP, translocates in 3’ to 5’ direction and interacts with MLH to modulate each other’s activity. In this follow up study, further characterization of P. falciparum UvrD helicase is presented. Here, we screened the effect of various DNA interacting compounds on the ATPase and helicase activity of PfUDN. This study resulted into the identification of daunorubicin (daunomycin), netropsin, nogalamycin, and ethidium bromide as the potential inhibitor molecules for the biochemical activities of PfUDN with IC₅₀ values ranging from ~3.0 to ~5.0 μM. Interestingly etoposide did not inhibit the ATPase activity but considerable inhibition of unwinding activity was observed at 20 μM. Further study for analyzing the importance of PfUvrD enzyme in parasite growth revealed that PfUvrD is crucial/important for its growth ex-vivo.

Conclusions

As PfUvrD is absent in human hence on the basis of this study we propose PfUvrD as suitable drug target to control malaria. Some of the PfUvrD inhibitors identified in the present study can be utilized to further design novel and specific inhibitor molecules.