JMIR Publications

ABSTRACT

Background:

Dengue fever can progress to dengue hemorrhagic fever (DHF), which is a more serious and occasionally fatal form of the disease. The patient may acquire warning indications of serious disease about the time the fever begins to reduce (typically 3–7 days following symptom onset), and there are currently no effective antivirals available. Drug repurposing is emerging as a novel drug discovery process for rapidly developing effective DHF therapies. Through network pharmacology modeling, several FDA-approved medications have already been researched for various viral outbreaks, by analyzing the interactions between virus-host gene interactions and therapeutic targets in the human genome network, a total of 45 repurposable medicines were discovered. Hub network analysis of host-virus-drugs association hypothesized that aspirin, captopril, rilonacept are efficient in the treatment of dengue hemorrhagic fever, and gene enrichment analysis supports the findings. As a result, genes targeting medications play a significant part in limiting the condition's advancement.

Objective:

•To identify a repurposable drug candidate group for dengue hemorrhagic fever (DHF) based on network-based drug reprofiling and drug enrichment analysis. •To find the effectiveness of existing drugs combination for the treatment of dengue hemorrhagic fever (DHF) (personalized drug). •To predict the toxicity and expression analysis of repurposed drugs in DHF.

Methods:

Building the dengue hemorrhagic fever -human interactome Based on Our literature similarity searches and database similarity searches found out more than 588 dengue hemorrhagic targeting human (host) genes-based similarity hit to score 50 we sort out 59 host interacting dengue hemorrhagic fever genes reported experimental evidence for interactions between human proteins and dengue virus proteins based on high-throughput yeast two-hybrid screening methods (Mairiang et al.2013) Recently, Dey and Mukhopadhyay reported the development of DenvInt, a database of manually curated experimental data of dengue protein and host protein interactions. We merged the data of published references from DenvInt and used it in our analysis along with the dengue-host interactome data from the recent investigations (Dey, L., & Mukhopadhyay, A.2016). Human(host) gene-Dengue hemorrhagic fever gene interactome The key host genes involved in Dengue hemorrhagic fever were identified from the GeneCard database using the search terms “Dengue hemorrhagic fever; Dengue hemorrhagic fever interacting human genes”. GeneCard is a searchable, integrative database that provides comprehensive, user-friendly information on all annotated and predicted human genes. The knowledgebase automatically integrates gene-centric data from ~150 web sources, including genomic, transcriptomic, proteomic, genetic, clinical, and functional information as of January 13 2022 Genecard comprises 326,787 genes are available in which 18,870 Disease genes and 500 Hot genes (Stelzer et al. 2016). The functions genes identified from GeneCard and related literature were collected and presented in Supplementary file 1. The PPI network was built with Cytoscape 3.9.0 v and Gephi 0.9.2v (Ramos et al. 2020) software. Drug-targets (human genes) interactome We collect 87 FDA-approved antiviral and 137 anti-dengue hemorrhagic fever drugs from the Therapeutic Target Database (TTD) compare them with the results of the Drugbank database (Y. Zhou et al. 2022, Wishart DS et al,2006), and identified drug targets and formulated them as a dataset its available in Supplementary file 1. We visualized it using Cytoscape (Shannon et al. 2003). Nodes in networks represent antiviral drugs or anti-dengue hemorrhagic fever drugs and the nodes of the network represent drugs targeting human genes (Huang et al. 2018). Building the drug -2-human interactome A network pharmacological based host-Dengue hemorrhagic fever-antiviral-anti Dengue hemorrhagic fever drugs interactome was constructed by assembling the host- Dengue hemorrhagic fever interacted proteins with or without antiviral, anti-dengue hemorrhagic fever drugs. The PPI network was built with Gephi 0.9.2v and Cytoscape 3.9.0v (Groshek et al. 2020) software. Each node in the constructed PPI network indicates a host gene and an edge indicates an interacting drug target. Network hub gene identification Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. Hub genes can be identified using the Contextual Hub Analysis Tool (CHAT) plug-in Cytoscape 3.9.0v (Muetze, T et al, 2016) which enables users to easily construct and visualize a network of interactions from a gene list of interest. Network betweenness centrality analysis Betweenness is a centrality measure of a vertex within a network, vertices that have a high probability to occur on a randomly chosen shortest path between two randomly chosen vertices have a high betweenness. The betweenness of a vertex α in a graph G: = (A, B) with A vertices and B edges (Linton Freeman 1977). For each pair of vertices (s,l), compute the shortest paths between them, For each pair of vertices (s,l), determine the fraction of shortest paths that pass through the vertex in question (here, vertex A). Sum this fraction over all pairs of vertices (sl). The degree Cb of node b is calculated as follows. C_b (A)=∑_(s≠A≠l€A)▒(σ_sl (A))/σ_sl Where, σ_sl (A) is the number of shortest paths from s to l that pass through a vertex A (Brandes, 2001). In a connected graph, the normalized closeness centrality (or closeness) of a node is the average length of the shortest path between the node and all other nodes in the graph (Alex Bavelas 1950) Thus, the more central a node is, the closer it is to all other nodes. C_a=1/(∑_b▒〖d(a,b)〗) Were d (a, b) being the distance between vertices a and b Functional enrichment analysis for genes and drugs Functional enrichment analysis is a method to determine classes of genes or drugs that are over-represented in a large group of genes or drugs and may have relations with disease phenotypes. This approach uses statistical methods to determine significantly enriched groups of genes. The biological relevance and functional pathways of our datasets were revealed by enriching the semantic similarities of the pathway, tissue. All functional enrichment analyses were performed using the Enrichr enrichment platform (Xie Z et al. 2021) as additional evidence for drug repurposing. The Enrichr is a comprehensive gene enrichment analysis platform that comprises 382,208 terms from 192 libraries. The combined score is described as c=log⁡(p).z where c = the combined score, p = Fisher exact test p-value, and z = z-score for deviation from expected rank.

Results:

Human (Host) - dengue hemorrhagic fever (viral) gene interactome. We constructed a host - DHF interactome consisting of 59 interacting genes with 60 nodes and 59 edges (Supplementary Fig. 1a). Based on Kegg pathway enrichment analysis indicates Genes involved in the AGE-RAGE signaling pathway in diabetic complications enriched (P = 3.01E-32) the most which indicate patients with DHF condition have a higher chance of poor blood sugar management while in the pathogenesis, AGE/RAGE signaling has been shown to increase oxidative stress to promote diabetes-mediated vascular calcification through activation of Nox-1 and decreased expression of SOD-1 (Kay et al 2016), and Chagas disease (P = 4.65E-32) and Influenza A pathways are typically enriched ( P = 6.17E-31). Compare to Kegg pathway analysis Reactome pathway analysis indicates Immune System (P=3.93E-28) and Cytokine Signalling in Immune system (P=7.06E-27) are enriched which indicates DHF hijack human immune system associated gene pathway the most, Gene set in which Immune system (1.12E-61) Bronchoalveolar lavage (2.85E-50) tissues are enriched the most (Supplementary file. 1b) Host – viral– antiviral drugs target interactome. A host-DHF-antiviral drug interactome was built with 298 nodes and 370 edges from 237 interacting genes (Supplementary Fig. 2a). based on Kegg pathway genes enrichment analysis Neuroactive ligand-receptor interaction(P=3.22E-45) i.e., collection of genes associated with intracellular and extracellular signaling pathways on the plasma membrane and MAPK pathways (P=9.57E-45) that relay, amplify and integrate signals from a diverse range of stimuli and elicit an appropriate physiological response including cellular proliferation, differentiation, development, inflammatory responses and apoptosis in mammalian cells enriched the most upon antiviral drug administration (Supplementary Fig. 2b). according to Reactome pathway analysis indicate Phase 2 - plateau phase (P=2.85E-34) that sustains cardiac action potential muscle contraction (Park & Fishman 2011, Grant 2009) and Transmission across Chemical Synapses (neurotransmitters) (P= 6.03E-34) pathway genes enriches and Adult(P=2.52E-69), Immune system(P=1.77E-49) tissue types expressed more on antiviral drug administration on HDF according to our enrichment analysis. Host – viral– Anti-dengue hemorrhagic fever drugs target interactome. A host - DHF interactome - Anti-dengue hemorrhagic fever drugs interactome was built with 558 nodes and 861 edges from 419 interacting genes (Supplementary Fig. 3a). Neuroactive ligand-receptor interaction (P=3.37E-75), cAMP signaling pathway (P=2.29E-54) also known as the adenylyl cyclase pathway, is a G protein-coupled receptor-triggered signaling cascade used in cell communication are the most enriched gene pathway respectively according to Kegg pathway analysis (Supplementary Fig. 3b). Amine ligand-binding receptors (1.76E-47) act as neurotransmitters in humans, Signal Transduction (P=1.40E-46) involves the binding of extracellular signaling molecules and ligands to receptors located on the cell surface are highly enriched. Adult (P=1.74E-59), Immune system(P=3.35E-54) are the most prominent tissue type during anti-dengue hemorrhagic fever drugs administration for COVID-19 patients. Host – viral– Antiviral -Anti-dengue hemorrhagic fever drugs target interactome. Based on all the interatomic data sets, we combine all the data sets to frame a network-based drug reprofiling approach to testing the robustness with which it involves network contains 717 nodes and 1175 edges from 487 interacting genes (Figure 1). Gene functional enrichment analysis of the Kegg pathway reveals that gene sets involved in neurotransmitters pathways(P=1.13E-84) and Calcium signaling pathway(P=1.78E-66) are highly enriched as similar as in previous drug-related host-virus interactome in human’s it also provides a stable outcome when a combined drug administration (antiviral, AHDFD) is employed during systemic DHF patients (Figure. 2). The majority of a gene set is enriched in Adult(P=1.53E-77), Immune system (P=3.07E-63) tissues. Genes related to Signal Transduction (P=6.76E-56), Signaling by GPCR (P=1.96E-49) are prevalent Reactome pathways enriched in DHF patients with combined drug medication. Network-based drug repurposing based on hub gene analysis. We predicted a hub gene module containing 20 interacting genes (66 nodes and 113 edges) from the above interactome of the host-virus-drugs systems framework (Figure 3). A total of 45 drugs are repurposed from the hub gene module in which 13 antiviral drugs and 32 Anti-dengue hemorrhagic fever drugs. From the hub gene-drug association network we find out that 3 major drugs bind efficiently with DHF targeting human genes, aspirin, captopril, rilonacept is efficient FDA approved drugs that can be used in the treatment of DHF (Figure 4) We identified 18 PTGS2 genes, 10 ACE, 4 F2, targeting drugs in hub genes in the network (Fig 2A). interestingly 18 out of 17 PTGS2 targeting drugs are ADHFD and 10 out of 9 ACE targeting genes are antiviral drugs in property, moreover, F2 targeting drugs are equal numbers ie 2 AVD and 2 ADHFD (Figure 5). Gene enrichment analysis shows that the hub gene module is highly enriched in tissues associated with the Immune system (P=7.29E-24), HUVEC cell(P=1.83E-20) this group of tissues act as an anticoagulant barrier between the vessel wall and blood, Kegg analysis shows that genes associated with cancer (P=1.13E-14), AGE-RAGE signaling pathway in diabetic complications(P=3.52E-14) which indicate that DHF patients with diabetes and cancer are risk of higher pathogenicity. Reactome pathway gene enrichment gives the evidence of immune systems associated pathways i.e., Signaling by Interleukins (2.04E-14), Cytokine Signaling in Immune system (7.12E-14) enrich the most (Figure 6). Functional enrichment analysis of drugs based on hub gene prediction. A total of 45 repurposable drugs were enriched for hub drug mechanism, gene expression of specific systems, and side effects (Figure 7). It shows that flurbiprofen, mefenamic acid, acetylsalicylic acid, indomethacin, naproxen, ketoprofen, acetaminophen, ketorolac, aceclofenac, lenalidomide, diclofenac, suprofen, loxoprofen, and nabumetone are PTGS2 targeting the hub gene module dyspnoea, shock, renal failure, nervousness, tension are prominent side effects of these drugs. prostaglandin metabolic process (P=0.000162675), regulation of Wnt signaling pathway (P=0.000307855) are prominent upregulated gene expression pathways during the above drug administration.

Conclusions:

We systematically study the association of the dengue viral interaction with the human genome through network-based association analysis. It is hypothesized that a host protein that functionally associates with this virus is localized in the corresponding sub-network within the comprehensive human interactome network. The host dependency factors mediating virus infection and effective molecular targets should be identified for developing broad-spectrum antiviral drugs and ADHFD for DHF. In our network-based analysis, we identified 45 repurposable drug candidates against DHF targeting the human gene in which 13 antiviral and 32 ADFHD that targeting 20 human genes, the most prevalent side-effect identified in repurposed drug enrichment was dyspnoea and shock. PTGS2, F2, and ACE genes are the highly targeted repurposed drugs, and it already reported the pathogenicity of PTGS2/ COX-2 gene pathways in the progression of DHF (Lin CK et al,2017). Most importantly PTGS2 gene has a direct relationship with Severe dengue happens when your blood vessels become damaged and leaky. And the number of clot-forming cells (platelets) in your bloodstream drops. This can lead to shock, internal bleeding, organ failure and even death (Ruan CH et al 2011) inhibiting this helps further prevent heart disease and better management of dengue hemorrhagic fever. For that, we sort out several effective targeting drugs based on our repurposing approach they are Aceclofenac, Acetaminophen, Aspirin, Choline magnesium trisalicylate, Diclofenac, Etodolac, Epinephrine, Indomethacin, Ketoprofen, Ketorolac, Loxoprofen, Mefenamic acid, Meloxicam, Nabumetone, Naproxen, Phenyl salicylate, Suprofen, Lenalidomide, enrichment analysis evidently emphasis most of the pathways of the immune system are enriched the most and adult and immune system associated tissues are associated with viral and drug response enriched throughout the study. This network-based analysis hypothesized that 3 drugs have repurposable properties are aspirin, captopril, rilonacept further studies are needed to prove its efficiencies in DHF patient treatment.