In silico prediction of antimalarial drug target candidates

Updated List of Transport Proteins in Plasmodium falciparum

Malaria remains a leading cause of death and disease in many tropical and subtropical regions of the world. Due to the alarming spread of resistance to almost all available antimalarial drugs, novel therapeutic strategies are urgently needed. As the intracellular human malaria parasite Plasmodium falciparum depends entirely on the host to meet its nutrient requirements and the majority of its transmembrane transporters are essential and lack human orthologs, these have often been suggested as potential targets of novel antimalarial drugs. However, membrane proteins are less amenable to proteomic tools compared to soluble parasite proteins, and have thus not been characterised as well. While it had been proposed that P. falciparum had a lower number of transporters (2.5% of its predicted proteome) in comparison to most reference genomes, manual curation of information from various sources led to the identification of 197 known and putative transporter genes, representing almost 4% of all parasite genes, a proportion that is comparable to well-studied metazoan species. This transporter list presented here was compiled by collating data from several databases along with extensive literature searches, and includes parasite-encoded membrane-resident/associated channels, carriers, and pumps that are located within the parasite or exported to the host cell. It provides updated information on the substrates, subcellular localisation, class, predicted essentiality, and the presence or absence of human orthologs of P. falciparum transporters to quickly identify essential proteins without human orthologs for further functional characterisation and potential exploitation as novel drug targets.

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.

Evaluating the Performance of Malaria Genetics for Inferring Changes in Transmission Intensity Using Transmission Modeling

Substantial progress has been made globally to control malaria, however there is a growing need for innovative new tools to ensure continued progress. One approach is to harness genetic sequencing and accompanying methodological approaches as have been used in the control of other infectious diseases. However, to utilize these methodologies for malaria, we first need to extend the methods to capture the complex interactions between parasites, human and vector hosts, and environment, which all impact the level of genetic diversity and relatedness of malaria parasites. We develop an individual-based transmission model to simulate malaria parasite genetics parameterized using estimated relationships between complexity of infection and age from five regions in Uganda and Kenya. We predict that cotransmission and superinfection contribute equally to within-host parasite genetic diversity at 11.5% PCR prevalence, above which superinfections dominate. Finally, we characterize the predictive power of six metrics of parasite genetics for detecting changes in transmission intensity, before grouping them in an ensemble statistical model. The model predicted malaria prevalence with a mean absolute error of 0.055. Different assumptions about the availability of sample metadata were considered, with the most accurate predictions of malaria prevalence made when the clinical status and age of sampled individuals is known. Parasite genetics may provide a novel surveillance tool for estimating the prevalence of malaria in areas in which prevalence surveys are not feasible. However, the findings presented here reinforce the need for patient metadata to be recorded and made available within all future attempts to use parasite genetics for surveillance.

A computational approach to validate novel drug targets of gentianine from Swertiya chirayita in Plasmodium falciparum

Gentianine is one of the compounds found in the plant Swertiya chirayita that is known for its antimalarial activity. However, its exact molecular mechanism of action is yet to be understood. In our present study, we applied several computational approaches to filter out and determine possible targets of gentianine in Plasmodium falciparum 3D7. Protein-protein networks formed the basis of one of our strategies along with orthologous protein analysis to establish essentiality. Out of 6 essential proteins from unique pathways, haloacid dehalogenase like-hydrolase (PfHAD1), phosphoenolpyruvate carboxykinase (PfPEPCK) and fumarate hydratase (PfFH) were screened as drug targets through this approach. Through our other strategy we established the predicted IC50 (PIC50) value of gentianine with a set of molecular descriptors from 123 Pathogen Box anti-malarial compounds. Afterwards through 2D structural similarity, L-lactate dehydrogenase (PfLDH) was established as another possible target. In our work, we performed in silico docking and analysed the binding of gentianine to the proteins. All of the proteins were reported with favourable binding results and were considered for complex molecular dynamics simulation approach. Our research clears up the molecular mechanism of antimalarial activity of gentianine to some extent paving way for experimental validation of the same in future.

Development of efficient RNAi in Nezara viridula for use in insecticide target discovery

Stink bugs are an emerging pest in many regions of the world but their molecular biology is still poorly understood. While several transcriptomes are available, the lack of validated gene manipulation tools like RNA interference (RNAi) in species such as the southern green stinkbug Nezara viridula precludes the characterization of individual genes in vivo. Such tools are particularly useful in performing high-throughput screens to search for essential genes that can be prioritized as potential insecticide targets. Here, we developed and optimized an efficient RNAi in N. viridula for use in insecticide target discovery and beyond. The visible marker Sex combs reduced and the essential gene Actin were used to verify the usability and efficiency of RNAi by microinjection at both the adult and nymphal stages, respectively, with nymphal approach presenting significant advantages. Following validation, RNAi was then used to measure lethality following the knockdown (KD) of two genes that are known insecticide targets, Chitin synthase, and Acetyl-CoA carboxylase. The KD of each gene resulted in >75% corrected mortality. These results indicate that RNAi is an effective tool in N. viridula and set a benchmark to evaluate potential targets in future RNAi screens aimed at insecticide target discovery.

In-silico Subtractive Proteomic Analysis Approach for Therapeutic Targets in MDR Salmonella enterica subsp. enterica serovar Typhi str. CT18

OBJECTIVE

In the present study, an attempt has been made for subtractive proteomic analysis approach for novel drug targets in Salmonella enterica subsp. enterica serover Typhi str.CT18 using computational tools.

METHODS

Paralogous, redundant and less than 100 amino acid protein sequences were removed by using CD-HIT. Further detection of bacterial proteins which are non-homologous to host and are essential for the survival of pathogens by using BLASTp against host proteome and DEG`s, respectively. Comparative Metabolic pathways analysis was performed to find unique and common metabolic pathways. The non-redundant, non-homologous and essential proteins were BLAST against approved drug targets for drug targets while Psortb and CELLO were used to predict subcellular localization.

RESULTS

There were 4473 protein sequences present in NCBI Database for Salmonella enterica subsp. enterica serover Typhi str. CT18 out of these 327 were essential proteins which were non-homologous to human. Among these essential proteins, 124 proteins were involved in 19 unique metabolic pathways. These proteins were further BLAST against approved drug targets in which 7 cytoplasmic proteins showed druggability and can be used as a therapeutic target.

CONCLUSION

Drug targets identification is the prime step towards drug discovery. We identified 7 cytoplasmic druggable proteins which are essential for the pathogen survival and non-homologous to human proteome. Further in vitro and in vivo validation is needed for the evaluation of these targets to combat against salmonellosis.

Network-Based Metabolism-Centered Screening of Potential Drug Targets in Klebsiella pneumoniae at Genome Scale

Klebsiella pneumoniae is an opportunistic bacterial pathogen leading to life-threatening nosocomial infections. Emergence of highly resistant strains poses a major challenge in the management of the infections by healthcare-associated K. pneumoniae isolates. Thus, despite intensive efforts, the current treatment strategies remain insufficient to eradicate such infections. Failure of the conventional infection-prevention and treatment efforts explicitly indicates the requirement of new therapeutic approaches. This prompted us to systematically analyze the K. pneumoniae metabolism to investigate drug targets. Genome-scale metabolic networks (GMNs) facilitating the systematic analysis of the metabolism are promising platforms. Thus, we used a GMN of K. pneumoniae MGH 78578 to determine putative targets through gene- and metabolite-centric approaches. To develop more realistic infection models, we performed the bacterial growth simulations within different host-mimicking media, using an improved biomass formation reaction. We selected more suitable targets based on several property-based prioritization procedures. KdsA was identified as the high-ranked putative target satisfying most of the target prioritization criteria specified under the gene-centric approach. Through a structure-based virtual screening protocol, we identified potential KdsA inhibitors. In addition, the metabolite-centric approach extended the drug target list based on synthetic lethality. This revealed the importance of combined metabolic analyses for a better understanding of the metabolism. To our knowledge, this is the first comprehensive effort on the investigation of the K. pneumoniae metabolism for drug target prediction through the constraint-based analysis of its GMN in conjunction with several bioinformatic approaches. This study can guide the researchers for the future drug designs by providing initial findings regarding crucial components of the Klebsiella metabolism.

Baseline Ex Vivo and Molecular Responses of Plasmodium falciparum Isolates to Piperaquine before Implementation of Dihydroartemisinin-Piperaquine in Senegal

Dihydroartemisinin-piperaquine, which was registered in 2017 in Senegal, is not currently used as the first-line treatment against uncomplicated malaria. A total of 6.6% to 17.1% of P. falciparum isolates collected in Dakar in 2013 to 2015 showed ex vivo-reduced susceptibility to piperaquine. Neither the exonuclease E415G mutation nor the copy number variation of the plasmepsin II gene (Pfpm2), associated with piperaquine resistance in Cambodia, was detected in Senegalese parasites.

Highlights on the Application of Genomics and Bioinformatics in the Fight Against Infectious Diseases: Challenges and Opportunities in Africa

Genomics and bioinformatics are increasingly contributing to our understanding of infectious diseases caused by bacterial pathogens such as Mycobacterium tuberculosis and parasites such as Plasmodium falciparum. This ranges from investigations of disease outbreaks and pathogenesis, host and pathogen genomic variation, and host immune evasion mechanisms to identification of potential diagnostic markers and vaccine targets. High throughput genomics data generated from pathogens and animal models can be combined with host genomics and patients’ health records to give advice on treatment options as well as potential drug and vaccine interactions. However, despite accounting for the highest burden of infectious diseases, Africa has the lowest research output on infectious disease genomics. Here we review the contributions of genomics and bioinformatics to the management of infectious diseases of serious public health concern in Africa including tuberculosis (TB), dengue fever, malaria and filariasis. Furthermore, we discuss how genomics and bioinformatics can be applied to identify drug and vaccine targets. We conclude by identifying challenges to genomics research in Africa and highlighting how these can be overcome where possible.

Using Yeast Synthetic Lethality To Inform Drug Combination for Malaria

Combinatorial chemotherapy is necessary for the treatment of malaria. However, finding a suitable partner drug for a new candidate is challenging. Here we develop an algorithm that identifies all of the gene pairs of Plasmodium falciparum that possess orthologues in yeast that have a synthetic lethal interaction but are absent in humans. This suggests new options for drug combinations, particularly for inhibitors of targets such as P. falciparum calcineurin, cation ATPase 4, or phosphatidylinositol 4-kinase.

An in silico strategy for identification of novel drug targets against Plasmodium falciparum

The apicomplexan parasite Plasmodium falciparum is responsible for global malaria burden. With the reported resistance to artemisinin chemotherapy, there is an urgent need to maintain early phase drug discovery and identify novel drug targets for successful eradication of the pathogen from the host. In our previous work on comparative genomics study for identification of putative essential genes and therapeutic candidates in P. falciparum, we predicted 11 proteins as anti-malarial drug targets from PlasmoDB database. In this paper, we made an attempt for identification of novel drug targets in P. falciparum genome using a sequence of computational methods from Malaria Parasite Metabolic Pathway database. The study reported the identification of 71 proteins as potential drug targets for anti-malarial interventions. Furthermore, homology modeling and molecular dynamic simulation study of one of the potential drug targets, aminodeoxychorismate lyase, was carried to predict the 3D structure of the protein. Structure and ligand-based drug designing reported MMV019742 from Pathogen Box and TCAMS-141515 from GSK-TCAMS library as potential hits. The reliability of the binding mode of the inhibitors is confirmed by GROMACS for a simulation time of 20 ns in water environment. This will be helpful for experimental validation of the small-molecule inhibitor.

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.

The drug target genes show higher evolutionary conservation than non-target genes

Although evidence indicates that drug target genes share some common evolutionary features, there have been few studies analyzing evolutionary features of drug targets from an overall level. Therefore, we conducted an analysis which aimed to investigate the evolutionary characteristics of drug target genes. We compared the evolutionary conservation between human drug target genes and non-target genes by combining both the evolutionary features and network topological properties in human protein-protein interaction network. The evolution rate, conservation score and the percentage of orthologous genes of 21 species were included in our study. Meanwhile, four topological features including the average shortest path length, betweenness centrality, clustering coefficient and degree were considered for comparison analysis. Then we got four results as following: compared with non-drug target genes, 1) drug target genes had lower evolutionary rates; 2) drug target genes had higher conservation scores; 3) drug target genes had higher percentages of orthologous genes and 4) drug target genes had a tighter network structure including higher degrees, betweenness centrality, clustering coefficients and lower average shortest path lengths. These results demonstrate that drug target genes are more evolutionarily conserved than non-drug target genes. We hope that our study will provide valuable information for other researchers who are interested in evolutionary conservation of drug targets.

Cloning, expression and purification of the complete domain of the η-carbonic anhydrase from Plasmodium falciparum

The antimalarial drugs are of fundamental importance in the control of malaria, especially for the lack of efficient treatments and acquired resistance to the existing drugs. For this reason, there is a continuous work in identifying novel, less toxic and effective chemotherapies as well as new therapeutic targets against the causative agents of malaria. In this context, a superfamily of metalloenzymes named carbonic anhydrases (CAs, EC 4.2.1.1) has aroused a great interest as druggable enzymes to limit the development of Plasmodium falciparum gametocytes. CAs catalyze a common reaction in all life domains, the carbon dioxide hydration to bicarbonate and protons (CO₂ + H₂O ⇔ HCO₃^- + H⁺). P. falciparum synthesizes pyrimidines de novo starting from HCO₃^-, which is generated from CO₂ through the action of the η-CA identified in the genome of the protozoan. Here, we propose a procedure for the preparation of a wider portion of the protozoan η-CA, named PfCAdom (358 amino acid residues), with respect to the truncated form prepared by Krungkrai et al. (PfCA1, 235 amino acid residues). The results evidenced that the recombinant PfCAdom, produced as a His-tag fusion protein, was 2.7 times more active with respect the truncated form PfCA1.

In silico multiple-targets identification for heme detoxification in the human malaria parasite Plasmodium falciparum

Detoxification of hemoglobin byproducts or free heme is an essential step and considered potential targets for anti-malaria drug development. However, most of anti-malaria drugs are no longer effective due to the emergence and spread of the drug resistant malaria parasites. Therefore, it is an urgent need to identify potential new targets and even for target combinations for effective malaria drug design. In this work, we reconstructed the metabolic networks of Plasmodium falciparum and human red blood cells for the simulation of steady mass and flux flows of the parasite's metabolites under the blood environment by flux balance analysis (FBA). The integrated model, namely iPF-RBC-713, was then adjusted into two stage-specific metabolic models, which first was for the pathological stage metabolic model of the parasite when invaded the red blood cell without any treatment and second was for the treatment stage of the parasite when a drug acted by inhibiting the hemozoin formation and caused high production rate of heme toxicity. The process of identifying target combinations consisted of two main steps. Firstly, the optimal fluxes of reactions in both the pathological and treatment stages were computed and compared to determine the change of fluxes. Corresponding enzymes of the reactions with zero fluxes in the treatment stage but non-zero fluxes in the pathological stage were predicted as a preliminary list of potential targets in inhibiting heme detoxification. Secondly, the combinations of all possible targets listed in the first step were examined to search for the best promising target combinations resulting in more effective inhibition of the detoxification to kill the malaria parasites. Finally, twenty-three enzymes were identified as a preliminary list of candidate targets which mostly were in pyruvate metabolism and citrate cycle. The optimal set of multiple targets for blocking the detoxification was a set of heme ligase, adenosine transporter, myo-inositol 1-phosphate synthase, ferrodoxim reductase-like protein and guanine transporter. In conclusion, the method has shown an effective and efficient way to identify target combinations which are obviously useful in the development of novel antimalarial drug combinations.

In silico characterization of an atypical MAPK phosphatase of Plasmodium falciparum as a suitable target for drug discovery

Plasmodium falciparum, the causative agent of malaria, contributes to significant morbidity and mortality worldwide. Forward genetic analysis of the blood-stage asexual cycle identified the putative phosphatase from PF3D7_1305500 as an important element of intraerythrocytic development expressed throughout the life cycle. Our preliminary evaluation identified it as an atypical mitogen-activated protein kinase phosphatase. Additional bioinformatic analysis delineated a conserved signature motif and three residues with potential importance to functional activity of the atypical dual-specificity phosphatase domain. A homology model of the dual-specificity phosphatase domain was developed for use in high-throughput in silico screening of the available library of antimalarial compounds from ChEMBL-NTD. Seven compounds from this set with predicted affinity to the active site were tested against in vitro cultures, and three had reduced activity against a ∆PF3D7_1305500 parasite, suggesting PF3D7_1305500 is a potential target of the selected compounds. Identification of these compounds provides a novel starting point for a structure-based drug discovery strategy that moves us closer toward the discovery of new classes of clinical antimalarial drugs. These data suggest that mitogen-activated protein kinase phosphatases represent a potentially new class of P. falciparum drug target.