Network-driven analysis of human–Plasmodium falciparum interactome: processes for malaria drug discovery and extracting in silico targets

Plasmodium falciparum malaria is a common infectious disease in Africa, and arguably the most important parasitic disease in the world, posing a significant public health burden as compared to other World Health Organization (WHO) disease-endemic regions. For instance, Africa contributed to about 93% (213 million of 228 million) and 94% (380,000 of 405,000) of global cases and deaths, respectively in 2018 [1].

The use of anti-malarial drugs has been the optimal avenue for controlling the disease. Currently, artemisinin-based combination therapy (ACT) is used as the first-line option for malaria treatment globally [2]. ACT was adopted in Africa after the decline in efficacy of previous widely used anti-malarial drugs, including chloroquine and sulfadoxine-pyrimethamine (SP) [2]. This was to ensure that, each component of the combinatorial drug acts through different mechanisms within the parasite, aiming to significantly reduce the likelihood of the emergence of multi-drug resistant parasites. Unfortunately, the parasite has shown tremendous ability to develop resistance and tolerance to these artemisinin derivatives and the long half-life partner drugs in some countries of the Greater Mekong Sub-region [2‐4]. With several reports supporting parasite recrudescence and a significant decrease in their sensitivity to ACT, there has been continuous surveillance to monitor the emergence and spread of artemisinin-resistant parasite strains in Africa and elucidate whether it will follow a similar pattern observed for chloroquine and SP resistance where resistant strains originated from Southeast Asia [2, 4‐7]. Interestingly, a study conducted by Uwimana et al. [7] has demonstrated the independent emergence and local spread of artemisinin partial resistance in Rwanda driven by R561H mutation in kelch gene. Another study conducted in Northern Uganda has also reported independent emergence and local spread of artemisinin-resistant parasite driven by mutations in the A675V or C469Y allele in the kelch13 gene [8]. These pieces of evidence suggest that artemisinin resistance has emerged independently in Eastern Africa.

Researchers have proposed that the emergence of artemisinin parasite-resistant strains in Africa would result in about 78 million additional cases [4] and over 100,000 deaths annually [9]. Evidence abounds to the fact that a major challenge to controlling, eliminating, and eradicating malaria is drug resistance. It is the principal reason for the expansion of this life-threatening disease.

The architectural framework of the parasite’s genome constitutes a major framework influencing variations in the levels of the drug susceptibility, particularly having elucidated that P. falciparum anti-malarial drug resistance involves a single major gene effect. Spontaneous alterations in the form of single nucleotide variation and multiple mutations in different genes within the parasite genome capacitate the pathogen’s ability to develop tolerance mechanisms or resist the drug action over time thus, yielding the unexpected result. Genetic polymorphisms of known drug-resistance genes, such as pfcrt, pfmdr1, pfk13, pfmrp1, pfdhfr, and pfdhps generally express effects that counteract drugs controlling the disease [7, 10‐12]. Compared to the clinical phenotype of resistance to quinolones and SP which usually takes the form of reduced accumulation of drugs within the parasite, particularly targets, artemisinin resistance, manifests as slow parasite clearance in patients and is characterized by the parasite’s ability to alter intraerythrocytic cell cycle with an increased ring stage and a shortened trophozoite stage [8, 13].

Falciparum malaria is a multifactorial disease that involves the complex interplay between the host, vector, and the pathogen [14, 15]. The host–pathogen interactions have been a driving selective force influencing the genetic architecture of both species, particularly, on how their genes are involved in drug and/or genetic resistance, disease susceptibility, and the infection processes [14, 16, 17].

Understanding these interactions requires an in-depth analysis of the organism’s proteome which is regarded to execute the genetic programme. Proteins execute functions mostly through extended networks with each other thereby forming a framework of the sensitive and complex regulatory system underlying a wide degree of post-translational modifications and processes [18]. The complex physicochemical dynamic connections formed within the system facilitate the structural and functional organization of the organism. These connections make up the protein–protein interaction network (PPIN).

Recent advances in host and parasite genomics in terms of high-throughput proteomics studies, host and parasite genome sequencing have led to a corresponding increase in biological datasets that describe the transition of species over time, particularly, the metabolic and developmental stages of pathogens. As such, the application of computational approaches to efficiently mine the inter and intra-species functional interactions to address the challenges presented by the disease is critical [19]. A systematic and comprehensive study of these complex interactions is essential in elucidating relevant pathways, signalling, drug resistance patterns, genes-gene products inter-relationships, and drug targets as well as developing novel hypotheses and models to predict disease causality [20].

In this study, a network-based integrative computational framework was leveraged to predict protein targets that may be used to guide the rational design of pathogen- and host-directed therapies for malaria treatment. Following the target prediction, a semantic similarity approach was implemented to prioritize informed potentially repurposable drugs that can be engineered for malaria treatment. Further analysis of host–pathogen network shortest paths enabled the prediction of immune-related biological processes and pathways potentially subverted by P. falciparum to increase its within-host survival.

In this study, an integrative network-based framework was implemented on the various heterogeneous experimental and in silico datasets retrieved from databases and literature to assemble Plasmodium falciparum, human, and human-Plasmodium falciparum functional protein–protein interaction network. Using host-malaria GWAS summary statistics datasets, host-disease-associated genes were identified by mapping nominally significant SNPs to their associated genes. The identified genes, malaria parasite selective variants, and parasite variants under strong signature of selection were mapped onto the host and pathogen functional network respectively to identify key subnetworks. The subnetworks of each assembled network were evaluated to investigate nodes (candidate key proteins) that contribute significantly to the stability and integrity of the network. Gene annotation and enrichment analysis of the identified hub genes were performed to elucidate underlying statistically significant biological processes and pathways. Also, shortest paths analysis was performed to elucidate pathways that could account for parasite adaptiveness to host response and potential drug resistance development. From the parasite assembled functional network, the analysis performed predicted C6KTD2 (SET1) and C6KTB7 (PFF1365c) as key targets. These targets are essential at specific developmental stages of the parasite and have been reported as candidates for drug and vaccine development. The results confirm the importance of these targets. Also, the analysis (Figs. 2B and 4A) showed that these targets could be critical for combinatorial drug design. There is an accumulation of evidence that C6KTB7 is a potential multi-stage target for a malaria vaccine and drug development [64‐68]. C6KTB7 is mainly involved in ubiquitin-protein transferase activity (GO:0004842, GO:0019787) through the protein ubiquitination and modification pathway (UPA00143). Studies have shown that many biological processes and substrates are targeted by the ubiquitin pathway such that instability or modification in ubiquitination and deubiquitination reactions influences the pathogenesis of many eukaryotic system-related diseases [65]. For instance, the dysregulation of ubiquitin ligase is associated with neurodegenerative disorders, such as Parkinson’s disease and infectious diseases including tuberculosis [66]. This is usually associated with interference with immune response. C6KTB7 significantly influences the parasite’s development and malaria pathogenesis by regulating various cellular processes and pathways critical for the pathogen’s survival in the human host [69]. This phenomenon usually happens as a result of post-translational modifications within the biological system through processes such as transcriptional regulation and cell cycle progression [66]. For example, the protein is responsible for the positive regulation of DNA-templated transcription and epigenetic factors such as histone H3-K4 methylation, essential for transcription regulation [65]. Interestingly, studies have shown that inhibition of the activities of C6KTB7 and the ubiquitin–proteasome system has the potential for many disease treatments including P. falciparum malaria [65, 68, 69]. Of note, the parasite candidate proteins are essential during specific developmental stages. For instance, Aminake et al. [68] explored the role of the proteasome of P. falciparum for malaria drug research and revealed C6KTB7 as a component of the ubiquitin–proteasome which could serve as a promising multi-stage (liver, blood, and transmission stages of the pathogen) target, thus a supporting results presented by Chung et al. [70]. Additionally, Ponts et al. [65] showed that proteins involved in the ubiquitylation pathway including the ubiquitin ligases (E3) such as C6KTB7 (PFF1365c) influence parasite virulence, thus targeting such a pathway may represent new therapeutic targets for apicomplexan parasites, such as P. falciparum. This suggests that inhibiting parasite adaptation to the ubiquitylation pathway and the proteins involved (including putative E3 ubiquitin-protein ligase protein PFF1365c (C6KTB7)) is important for malaria drug research [65, 68]. C6KTD2 is a possible candidate for effective malaria vaccine development [67]. The protein plays an essential role in chromatin structure, protein domain-specific binding. and gene expression in the parasite [35, 71]. Also, it is mainly involved in the histone lysine methylation post-translational modification process (GO: 0051568) which usually involves the synergistic effect of histone-lysine methyltransferases and histone lysine demethylases [71, 72]. A gene knock-out study conducted by Jian et al. [73] revealed that C6KTD2 is essential particularly during the blood stage of the parasite, thus targeting it in drug research is important. Interactome analysis on the host functional network revealed (P22301 (IL10), P05362 (ICAM1), P01375 (TNF), P30480 (HLA-B), P16284 (PECAM1), O00206 (TLR4)) as key targets. These host candidate key proteins are involved in immune response and resistance against malaria infection including severe and cerebral malaria, thus, critical targets for adjunctive and antibody-based host-directed therapy for malaria control [74‐76]. Importantly, studies have shown the need to complement artemisinin derivatives with host-directed therapy involved in immune modulation to help effectively control and treat severe malaria and cerebral malaria [77]. This may contribute significantly to improve treatment efficacy, reduce disease-associated complexity, reduce malaria-associated mortality and morbidity as well as slow artemisinin resistance development. In both the parasite and host-parasite functional network, the functional interactions between hubs formed by C6KTD2 and C6KTB7 were identified (Fig. 2B). This finding suggests the functional relatedness of these proteins and their modularity within the parasite to jointly regulate post-translational modification processes. Having established that nodes within a cluster might be involved in the same biological process, it is, therefore, possible that these key proteins within the clusters contribute significantly to similar processes [78].

23 significantly enriched malaria-related biological processes described in (Table 3) were identified. These gene ontology groups comprised of those involved in cell immune and inflammatory responses, regulation and production of transcription factors, biosynthetic processes, cell–cell adhesion, cell signalling, and cell apoptotic processes. Positive regulation of NIK/NF-kappaB signalling (GO:0042346) process responsible for the regulation of NF-kappaB importation has been studied to be involved in immune and inflammatory responses, particularly in eukaryotic cells. Down or negative regulation of NF-kappaB has been reported to be associated with P. falciparum-modulated endothelium transcriptome contributing to cerebral malaria [79]. Positive regulation of the MHC class II biosynthetic process (GO:0045348) process has been shown to regulate immune response to malaria [80]. Pre-erythrocytic immunity to malaria (cerebral malaria) is linked to MHC antigens such that variations in class I and class II in these antigens contribute significantly to malaria susceptibility thus, reduced, or increased host immune response [80]. Also, other processes such as negative regulation of interferon-gamma production (GO:0032689), negative regulation of interleukin-6 production (GO:0032715), negative regulation of cytokine secretion involved in immune response (GO:0002740), and positive regulation of interferon-gamma production (GO:0032729) serves as immunological mediating processes that influence disease susceptibility by either conferring protection or influencing disease progress. Activation and regulation of NLRP3 inflammasomes, immune system receptors, controls the activation of caspase-1 and induce inflammation in response to infectious pathogens [81]. Due to their influence on a wide range of diseases, their dysfunction results in the initiation or progression of diseases. Endothelial cell apoptosis has been studied to contribute to malaria severity. For instance, haem-induced microvasculature endothelial cell apoptosis mediated by proinflammatory and proapoptotic pathways contributes significantly to severe malaria.

Shortest path analysis further revealed human immune-related genes and pathways that could be overwhelmed by the pathogen, knowing that the pathology of malaria is immune-mediated and inflammatory response-driven. Such inhibition could result in reduced anti-inflammatory responses thus limiting the production and possible cytopathic effects of cytokines [82]. The analysis revealed potential pathways between host malaria-associated candidate key protein O00206 (Toll-like receptor 4, TLR4) and pathogen proteins C6KTB7 (Putative E3 ubiquitin-protein ligase protein PFF1365c) and C6KTD2 (Putative histone-lysine N-methyltransferase 1, SET1) that could account for unrestrained parasite growth and severe complications. Experimental findings have revealed that activation of TLRs induces the production of nitric oxide and synthesis of pro-inflammatory cytokines, such as TNF and IL‑1β [50, 83]. Of note, activation of TLR4 induces macrophage release of pro-inflammatory mediators, such as TNF and nitric oxide [50, 83]. It also induces the expression of adhesion molecules on endothelial cells [50]. This may suggest that PECAM1, ICAM1, and TNF are from the downstream signalling cascade generated by TLR4 [83].

Severe malaria is associated with an increased level of pro-inflammatory cytokines (T helper 1 (Th1) cytokines) such as interleukin (IL)-12, IL-8, and interferon (IFN)-\(\upgamma \) in the affected person which helps to modulate defence against the infection and limit disease progression [59, 82]. This is attributed to the fact that the severity of malaria is proportional to the flawlessness in the host inflammatory response.

TLR4, a pathogen-recognition receptor, detects pathogen-associated molecular mechanisms in the body and initiates immune response through activation of signalling cascades such as nuclear factorkB, mitogen-activated protein kinase (MAPK), and Plasmodium antigens [59]. TLR4 and its immune-related signalling pathways have been reported to contribute significantly to P. falciparum growth and malaria pathogenesis, such that dysregulation and dysfunction of the gene increase malaria severity, symptomatic malaria, severe malaria anaemia, and resistance in Africa [84]. This suggests that deleterious activation of TLR4 by C6KTB7 and C6KTD2 will significantly contribute to parasite survival and disease susceptibility thereby causing severe pathological conditions.

Finally, a semantic similarity approach was implemented to identify 113 diseases like malaria (Additional file 8: Table S5) that facilitated the prediction of 26 potential repurposable drug hits, spanning across anti-malarials, monoclonal antibodies, immunomodulators, herbs, natural products, Janus kinase inhibitors, and thrombolytic agents, that can be computationally and experimentally modified for parasite or host-directed malaria treatment. Drug hits for each category were ranked based on the enriched similarity score. The results revealed certolizumab pegol and golimumab as hits for the monoclonal antibody category, pomalidomide for the immunomodulator category, ginseng for the herbs and natural product category, ruxolitinib for the Janus kinase inhibitors, anistreplase for the thrombolytic agent category, and chloroquine for the anti-malarial category. Additional file 9: Table S6 describes the known activity and the original therapeutic purpose of the potentially repurposable drugs identified.

With the gradual emergence and spread of malaria drug resistance, considering other potential drug targets and drug candidates are essential to increase the longevity of existing drugs as well as develop alternative treatment options. In this research, integrative computational methods were leveraged to (1) predict potential drug targets for both human host and pathogen-directed drug discovery, (2) predict drug candidates that could be re-engineered for malaria treatment and, (3) identify biological processes and pathways that could be overwhelmed by the pathogen to increase within-host survival.

The analysis revealed that repurposable drugs involved in regulating host immune response to inflammatory-driven disorders and/or inhibiting residual malaria infection may enable appropriate malaria treatment. Of note, the potential to treat malaria using inhibitors or drugs that target the proteasome component and/or proteins involved in the parasite’s post-translational modification such as C6KTB7 and C6KTD2 have been established. However, exploring these targets for drug and vaccine development is yet to be fully achieved. Both C6KTD2 and C6KTB7 proteins have no crystallized structure yet, but the availability of other homologs could be explored using homology modelling approach to model the proteins. The generated homology models could be the starting point for novel drug discovery and structure-based studies to identify potential inhibitors. Additionally, the host protein targets predicted have solved structures that can be harnessed for structure-based drug discovery to identify potential inhibitors for malaria research.

In summary, the uniqueness of the integrative network framework lies in the input datasets, scoring metrics/schemes, clustering algorithm, and the criteria defined for the various analysis which translates into the findings from this study. The integrative network-based approach incorporates interologs, sequence blast interactions, and protein–protein interaction data from the literature, as well as the STRING, IntAct, MINT, and BIOGRID databases. In addition, the network approach implements a scalable hierarchical agglomerative clustering model, based on modularity optimization, to cluster the network into communities by leveraging candidate genes. This is then followed by network topology analysis to evaluate the topological features (degree, betweenness, and closeness) of the malaria candidate genes to identify hubs genes/proteins. The semantic similarity measures implemented coupled with literature evidence helped to identify diseases similar to malaria and potential repurposable drug candidates.

Like other computational approaches which need validation through further functional study, our findings presented can inform functional study for potential experimental and clinical validation. Extended computational analysis of this work would consider incorporating non-reviewed protein data, other omics level datasets, and drug-drug interaction information.