ARID3C Acts as a Regulator of Monocyte-to-Macrophage Differentiation Interacting with NPM1.

ARID3C is a protein located on human chromosome 9 and expressed at low levels in various organs, yet its biological function has not been elucidated. In this study, we investigated both the cellular localization and function of ARID3C. Employing a combination of LC-MS/MS and deep learning techniques, we identified NPM1 as a binding partner for ARID3C's nuclear shuttling. ARID3C was found to predominantly localize with the nucleus, where it functioned as a transcription factor for genes STAT3, STAT1, and JUNB, thereby facilitating monocyte-to-macrophage differentiation. The precise binding sites between ARID3C and NPM1 were predicted by AlphaFold2. Mutating this binding site prevented ARID3C from interacting with NPM1, resulting in its retention in the cytoplasm instead of translocation to the nucleus. Consequently, ARID3C lost its ability to bind to the promoters of target genes, leading to a loss of monocyte-to-macrophage differentiation. Collectively, our findings indicate that ARID3C forms a complex with NPM1 to translocate to the nucleus, acting as a transcription factor that promotes the expression of the genes involved in monocyte-to-macrophage differentiation.

Studying protein-protein interactions: Latest and most popular approaches.

PPIs, or protein-protein interactions, are essential for many biological processes. According to the findings, abnormal PPIs have been linked to several diseases, such as cancer and infectious and neurological disorders. Consequently, focusing on PPIs is a path toward disease treatment and a crucial tool for producing novel medications. Many methods exist to investigate PPIs, including low- and high-throughput studies. Since many PPIs have been discovered using in vitro and in vivo experimental approaches, the use of computational methods to predict PPIs has grown due to the expanding scale of PPI data and the intrinsic complexity of interacting mechanisms. Recognizing PPI networks offers a systematic means of predicting protein functions, and pathways that are included. These investigations can help uncover the underlying molecular mechanisms of complex phenotypes and clarify the biological processes related to health and diseases. Therefore, our goal in this study is to provide an overview of the latest and most popular approaches for investigating PPIs. We also overview some important clinical approaches based on the PPIs and how these interactions can be targeted.

Discovery and Characterization of Linear Motif Mediated Protein-Protein Complexes.

There are myriads of protein-protein complexes that form within the cell. In addition to classical binding events between globular domains, many protein-protein interactions involve short disordered protein regions. The latter contain so-called linear motifs binding specifically to ordered protein domain surfaces. Linear binding motifs are classified based on their consensus sequence, where only a few amino acids are conserved. In this chapter we will review experimental and in silico techniques that can be used for the discovery and characterization of linear motif mediated protein-protein complexes involved in cellular signaling, protein level and gene expression regulation.

The antiviral enzyme viperin inhibits cholesterol biosynthesis.

Many enveloped viruses bud from cholesterol-rich lipid rafts on the cell membrane. Depleting cellular cholesterol impedes this process and results in viral particles with reduced viability. Viperin (Virus Inhibitory Protein, Endoplasmic Reticulum-associated, Interferon iNducible) is an endoplasmic reticulum membrane-associated enzyme that exerts broad-ranging antiviral effects, including inhibiting the budding of some enveloped viruses. However, the relationship between viperin expression and the retarded budding of virus particles from lipid rafts on the cell membrane is unclear. Here, we investigated the effect of viperin expression on cholesterol biosynthesis using transiently expressed genes in the human cell line human embryonic kidney 293T (HEK293T). We found that viperin expression reduces cholesterol levels by 20% to 30% in these cells. Following this observation, a proteomic screen of the viperin interactome identified several cholesterol biosynthetic enzymes among the top hits, including lanosterol synthase (LS) and squalene monooxygenase (SM), which are enzymes that catalyze key steps in establishing the sterol carbon skeleton. Coimmunoprecipitation experiments confirmed that viperin, LS, and SM form a complex at the endoplasmic reticulum membrane. While coexpression of viperin was found to significantly inhibit the specific activity of LS in HEK293T cell lysates, coexpression of viperin had no effect on the specific activity of SM, although did reduce SM protein levels by approximately 30%. Despite these inhibitory effects, the coexpression of neither LS nor SM was able to reverse the viperin-induced depletion of cellular cholesterol levels, possibly because viperin is highly expressed in transfected HEK293T cells. Our results establish a link between viperin expression and downregulation of cholesterol biosynthesis that helps explain viperin's antiviral effects against enveloped viruses.

The p140Cap adaptor protein as a molecular hub to block cancer aggressiveness.

The p140Cap adaptor protein is a scaffold molecule encoded by the SRCIN1 gene, which is physiologically expressed in several epithelial tissues and in the neurons. However, p140Cap is also strongly expressed in a significant subset of cancers including breast cancer and neuroblastoma. Notably, cancer patients with high p140Cap expression in their primary tumors have a lower probability of developing a distant event and ERBB2-positive breast cancer sufferers show better survival. In neuroblastoma patients, SRCIN1 mRNA levels represent an independent risk factor, which is inversely correlated to disease aggressiveness. Consistent with clinical data, SRCIN1 gain or loss of function mouse models demonstrated that p140Cap may affect tumor growth and metastasis formation by controlling the signaling pathways involved in tumorigenesis and metastatic features. This study reviews data showing the relevance of SRCIN1/p140Cap in cancer patients, the impact of SRCIN1 status on p140Cap expression, the specific mechanisms through which p140Cap can limit cancer progression, the molecular functions regulated by p140Cap, along with the p140Cap interactome, to unveil its key role for patient stratification in clinics.

Flashlight into the Function of Unannotated C11orf52 using Affinity Purification Mass Spectrometry.

For an enhanced understanding of the biological mechanisms of human disease, it is essential to investigate protein functions. In a previous study, we developed a prediction method of gene ontology (GO) terms by the I-TASSER/COFACTOR result, and we applied this to uPE1 in chromosome 11. Here, to validate the bioinformatics prediction of C11orf52, we utilized affinity purification and mass spectrometry to identify interacting partners of C11orf52. Using immunoprecipitation methods with three different peptide tags (Myc, Flag, and 2B8) in HEK 293T cell lines, we identified 79 candidate proteins that are expected to interact with C11orf52. The results of a pathway analysis of the GO and STRING database with candidate proteins showed that C11orf52 could be related to signaling receptor binding, cell-cell adhesion, and ribosome biogenesis. Then, we selected three partner candidates of DSG1, JUP, and PTPN11 for verification of the interaction with C11orf52 and confirmed them by colocalization at the cell-cell junctions by coimmunofluorescence experiments. On the basis of this study, we expect that C11orf52 is related to the Wnt signaling pathway via DSG1 from the protein-protein interactions, given the results of a comprehensive analysis of the bioinformatic predictions. The data set is available at the ProteomeXchange consortium via PRIDE repository (PXD026986).

Musashi interaction with poly(A)-binding protein is required for activation of target mRNA translation.

The Musashi family of mRNA translational regulators controls both physiological and pathological stem cell self-renewal primarily by repressing target mRNAs that promote differentiation. In response to differentiation cues, Musashi can switch from a repressor to an activator of target mRNA translation. However, the molecular events that distinguish Musashi-mediated translational activation from repression are not understood. We have previously reported that Musashi function is required for the maturation of Xenopus oocytes and specifically for translational activation of specific dormant maternal mRNAs. Here, we employed MS to identify cellular factors necessary for Musashi-dependent mRNA translational activation. We report that Musashi1 needs to associate with the embryonic poly(A)-binding protein (ePABP) or the canonical somatic cell poly(A)-binding protein PABPC1 for activation of Musashi target mRNA translation. Co-immunoprecipitation studies demonstrated an increased Musashi1 interaction with ePABP during oocyte maturation. Attenuation of endogenous ePABP activity severely compromised Musashi function, preventing downstream signaling and blocking oocyte maturation. Ectopic expression of either ePABP or PABPC1 restored Musashi-dependent mRNA translational activation and maturation of ePABP-attenuated oocytes. Consistent with these Xenopus findings, PABPC1 remained associated with Musashi under conditions of Musashi target mRNA de-repression and translation during mammalian stem cell differentiation. Because association of Musashi1 with poly(A)-binding proteins has previously been implicated only in repression of Musashi target mRNAs, our findings reveal novel context-dependent roles for the interaction of Musashi with poly(A)-binding protein family members in response to extracellular cues that control cell fate.

A Click-Chemistry-Based Enrichable Crosslinker for Structural and Protein Interaction Analysis by Mass Spectrometry.

Mass spectrometry is the method of choice for the characterisation of proteomes. Most proteins operate in protein complexes, in which their close association modulates their function. However, with standard MS analysis, information on protein-protein interactions is lost and no structural information is retained. To gain structural and interactome data, new crosslinking reagents are needed that freeze inter- and intramolecular interactions. Herein, the development of a new reagent, which has several features that enable highly sensitive crosslinking MS, is reported. The reagent enables enrichment of crosslinked peptides from the majority of background peptides to facilitate efficient detection of low-abundant crosslinked peptides. Due to the special cleavable properties, the reagent can be used for MS2 and potentially for MS3 experiments. Thus, the new crosslinking reagent, in combination with high-end MS, should enable sensitive analysis of interactomes, which will help researchers to obtain important insights into cellular states in health and diseases.

Interactome and F-Actin Interaction Analysis of Dictyostelium discoideum Coronin A.

Coronin proteins are evolutionary conserved WD repeat containing proteins that have been proposed to carry out different functions. In Dictyostelium, the short coronin isoform, coronin A, has been implicated in cytoskeletal reorganization, chemotaxis, phagocytosis and the initiation of multicellular development. Generally thought of as modulators of F-actin, coronin A and its mammalian homologs have also been shown to mediate cellular processes in an F-actin-independent manner. Therefore, it remains unclear whether or not coronin A carries out its functions through its capacity to interact with F-actin. Moreover, the interacting partners of coronin A are not known. Here, we analyzed the interactome of coronin A as well as its interaction with F-actin within cells and in vitro. Interactome analysis showed the association with a diverse set of interaction partners, including fimbrin, talin and myosin subunits, with only a transient interaction with the minor actin10 isoform, but not the major form of actin, actin8, which was consistent with the absence of a coronin A-actin interaction as analyzed by co-sedimentation from cells and lysates. In vitro, however, purified coronin A co-precipitated with rabbit muscle F-actin in a coiled-coil-dependent manner. Our results suggest that an in vitro interaction of coronin A and rabbit muscle actin may not reflect the cellular interaction state of coronin A with actin, and that coronin A interacts with diverse proteins in a time-dependent manner.

Identification and characterization of a centrosomal protein, FOR20 as a novel S100A6 target.

S100A6 is a Ca2+-signal transducer that interacts with numerous proteins and regulates their biochemical functions. Here we identified a centrosomal protein, FOR20 (FOP-related protein of 20 kDa) as a novel S100A6 target by screening protein microarrays carrying 19,676 recombinant GST-fused human proteins. Binding experiments revealed that S100A6 interacts with the N-terminal region (residues 1-30) of FOR20 in a Ca2+-dependent manner in vitro and in living cells. Several S100 proteins including S100A1, A2, A4, A11, B also exhibited Ca2+-dependent interactions with FOR20 as well as S100A6. We found that two distantly related centrosomal proteins, FOP and OFD1, also possess N-terminal regions with a significant sequence similarity to the putative S100A6-binding site (residues 1-30) in FOR20 and are capable of binding to S100A6 in a Ca2+-dependent manner. Taken together, these results may indicate that S100A6 interacts with FOR20 and related centrosomal proteins through a conserved N-terminal domain, suggesting a novel Ca2+-dependent regulation of centrosomal function.

Extra Tree Classifier Predicts an Interactome Hub Gene as HSPB1 in Oral Cancer: A Bioinformatics Analysis.

Introduction Oral cancer is a significant global health issue that is mainly caused by factors, such as smoking, alcohol consumption, poor oral hygiene, age, and the human papillomavirus. Unfortunately, delayed diagnosis contributes to high rates of illness and mortality. However, saliva shows promise as a potential source for early detection, prognosis, and treatment. By analyzing the proteins and their interactions in saliva, we can gain insights that can assist in early detection and prediction. In this study, we aim to identify and predict the key genes, known as hub genes, in the salivary transcriptomics data of oral cancer patients and healthy individuals. Methods The data used for the analysis were obtained from salivaryproteome.org (https://salivaryproteome.org/) . The retrieved data consisted of individuals with oral cancer who were assigned unique identification numbers (IDs) 1025, 1030, 1027, and 1029, while the healthy individuals were assigned IDs 4256, 4257, 4255, and 4258, respectively. Differential gene expression analysis was used to identify genes that showed significant differences between the two groups. Uniformity and clustering were assessed through heatmaps and principal component analysis. Protein-protein interactions were investigated using the STRING database and Cytoscape. In addition, machine learning algorithms were employed to identify key genes involved in the interatomic interactions by analyzing transcriptomics data generated from the differential gene expression analysis. Results The accuracy and class accuracy of the extra tree classifier showed 98% and 97% in predicting interactomic hub genes, and HSPB1 was identified as a hub gene using Cytohubba from Cytoscape. Conclusion The predictive extra tree classifier, with its high accuracy in analysing interactomic hub genes in oral cancer, can potentially improve diagnosis and treatment strategies.

Assessing reproductive effects and epigenetic responses in Austrolebias charrua exposed to Roundup Transorb®: Insights from miRNA profiling and molecular interaction analysis.

This study examines the effects of Roundup Transorb® (RDT) exposure on reproductive functions and ovarian miRNA expression in Austrolebias charrua. Exposure to RDT (at 0.065 or 5 mg. L-1 for 96 h) significantly disrupts fertility, evidenced by changes in fertilization rates and egg diameter. Profiling of ovarian miRNAs identified a total 205 miRNAs in A. charrua. Among these, three miRNAs were upregulated (miR-10b-5p, miR-132-3p, miR-100-5p), while ten miRNAs were downregulated (miR-499-5p, miR-375, miR-205-5p, miR-206-3p, miR-203a-3p, miR-133b-3p, miR-203b-5p, miR-184, miR-133a-3p, miR-2188-5p) compared to non-exposed fish. This study reveals that differentially expressed miRNAs are linked to molecular pathways such as steroid hormone biosynthesis, lipid and carbohydrate metabolism, bioenergetics, and antioxidant defense. It also analyzes molecular interactions between miRNAs and target genes during RDT exposure in annual killifish, providing insights into biomarkers in ecotoxicology. Moreover, it provides scope for developing environmental health assessment models based on epigenomic endpoints, supporting the protection of biodiversity and ecosystem services through the quantification of stress responses in living organisms exposed to pesticides.

Comparative Proteomics and Interactome Analysis of the SARS-CoV-2 Nucleocapsid Protein in Human and Bat Cell Lines.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of COVID-19 and responsible for the global coronavirus pandemic which started in 2019. Despite exhaustive efforts to trace its origins, including potential links with pangolins and bats, the precise origins of the virus remain unclear. Bats have been recognized as natural hosts for various coronaviruses, including the Middle East respiratory coronavirus (MERS-CoV) and the SARS-CoV. This study presents a comparative analysis of the SARS-CoV-2 nucleocapsid protein (N) interactome in human and bat cell lines. We identified approximately 168 cellular proteins as interacting partners of SARS-CoV-2 N in human cells and 196 cellular proteins as interacting partners with this protein in bat cells. The results highlight pathways and events that are both common and unique to either bat or human cells. Understanding these interactions is crucial to comprehend the reasons behind the remarkable resilience of bats to viral infections. This study provides a foundation for a deeper understanding of host-virus interactions in different reservoirs.

Probing the acetylation code of histone H4.

Histone modifications play crucial roles in genome regulation with lysine acetylation being implicated in transcriptional control. Here we report a proteome-wide investigation of the acetylation-dependent protein-protein interactions of the N-terminal tail of histone H4. Quantitative peptide-based affinity MS experiments using the SILAC approach determined the interactomes of H4 tails monoacetylated at the four known acetylation sites K5, K8, K12, and K16, bis-acetylated at K5/K12, triple-acetylated at K8/12/16 and fully tetra-acetylated. A set of 29 proteins was found enriched on the fully acetylated H4 tail while specific binders of the mono and bis-acetylated tails were barely detectable. These observations are in good agreement with earlier reports indicating that the H4 acetylation state establishes its regulatory effects in a cumulative manner rather than via site-specific recruitment of regulatory proteins.

The Gene Network Correlation Analysis of Obesity to Type 1 Diabetes and Cardiovascular Disorders: An Interactome-Based Bioinformatics Approach.

The current study focuses on the importance of Protein-Protein Interactions (PPIs) in biological processes and the potential of targeting PPIs as a new treatment strategy for diseases. Specifically, the study explores the cross-links of PPIs network associated with obesity, type 1 diabetes mellitus (T1DM), and cardiac disease (CD), which is an unexplored area of research. The research aimed to understand the role of highly connected proteins in the network and their potential as drug targets. The methodology for this research involves retrieving genes from the NCBI online gene database, intersecting genes among three diseases (type 1 diabetes, obesity, and cardiovascular) using Interactivenn, determining suitable drug molecules using NetworkAnalyst, and performing various bioinformatics analyses such as Generic Protein-Protein Interactions, topological properties analysis, function enrichment analysis in terms of GO, and Kyoto Encyclopedia of Genes and Genomes (KEGG), gene co-expression network, and protein drug as well as protein chemical interaction network. The study focuses on human subjects. The results of this study identified 12 genes [VEGFA (Vascular Endothelial Growth Factor A), IL6 (Interleukin 6), MTHFR (Methylenetetrahydrofolate reductase), NPPB (Natriuretic Peptide B), RAC1 (Rac Family Small GTPase 1), LMNA (Lamin A/C), UGT1A1 (UDP-glucuronosyltransferase family 1 membrane A1), RETN (Resistin), GCG (Glucagon), NPPA (Natriuretic Peptide A), RYR2 (Ryanodine receptor 2), and PRKAG2 (Protein Kinase AMP-Activated Non-Catalytic Subunit Gamma 2)] that were shared across the three diseases and could be used as key proteins for protein-drug/chemical interaction. Additionally, the study provides an in-depth understanding of the complex molecular and biological relationships between the three diseases and the cellular mechanisms that lead to their development. Potentially significant implications for the therapy and management of various disorders are highlighted by the findings of this study by improving treatment efficacy, simplifying treatment regimens, cost-effectiveness, better understanding of the underlying mechanism of these diseases, early diagnosis, and introducing personalized medicine. In conclusion, the current study provides new insights into the cross-links of PPIs network associated with obesity, T1DM, and CD, and highlights the potential of targeting PPIs as a new treatment strategy for these prevalent diseases.

A Review and Meta-Analysis of Influenza Interactome Studies.

Annually, the influenza virus causes 500,000 deaths worldwide. Influenza-associated mortality and morbidity is especially high among the elderly, children, and patients with chronic diseases. While there are antivirals available against influenza, such as neuraminidase inhibitors and adamantanes, there is growing resistance against these drugs. Thus, there is a need for novel antivirals for resistant influenza strains. Host-directed therapies are a potential strategy for influenza as host processes are conserved and are less prone mutations as compared to virus-directed therapies. A literature search was performed for papers that performed viral-host interaction screens and the Reactome pathway database was used for the bioinformatics analysis. A total of 15 studies were curated and 1717 common interactors were uncovered among all these studies. KEGG analysis, Enrichr analysis, STRING interaction analysis was performed on these interactors. Therefore, we have identified novel host pathways that can be targeted for host-directed therapy against influenza in our review.

Correcting Differential Gene Expression Analysis for Cyto-Architectural Alterations in Substantia Nigra of Parkinson's Disease Patients Reveals Known and Potential Novel Disease-Associated Genes and Pathways.

Several studies have analyzed gene expression profiles in the substantia nigra to better understand the pathological mechanisms causing Parkinson's disease (PD). However, the concordance between the identified gene signatures in these individual studies was generally low. This might have been caused by a change in cell type composition as loss of dopaminergic neurons in the substantia nigra pars compacta is a hallmark of PD. Through an extensive meta-analysis of nine previously published microarray studies, we demonstrated that a big proportion of the detected differentially expressed genes was indeed caused by cyto-architectural alterations due to the heterogeneity in the neurodegenerative stage and/or technical artefacts. After correcting for cell composition, we identified a common signature that deregulated the previously unreported ammonium transport, as well as known biological processes such as bioenergetic pathways, response to proteotoxic stress, and immune response. By integrating with protein interaction data, we shortlisted a set of key genes, such as LRRK2, PINK1, PRKN, and FBXO7, known to be related to PD, others with compelling evidence for their role in neurodegeneration, such as GSK3ß, WWOX, and VPC, and novel potential players in the PD pathogenesis. Together, these data show the importance of accounting for cyto-architecture in these analyses and highlight the contribution of multiple cell types and novel processes to PD pathology, providing potential new targets for drug development.

Promising Acinetobacter baumannii Vaccine Candidates and Drug Targets in Recent Years.

In parallel to the uncontrolled use of antibiotics, the emergence of multidrug-resistant bacteria, like Acinetobacter baumannii, has posed a severe threat. A. baumannii predominates in the nosocomial setting due to its ability to persist in hospitals and survive antibiotic treatment, thereby eventually leading to an increasing prevalence and mortality due to its infection. With the increasing spectra of drug resistance and the incessant collapse of newly discovered antibiotics, new therapeutic countermeasures have been in high demand. Hence, recent research has shown favouritism towards the long-term solution of designing vaccines. Therefore, being a realistic alternative strategy to combat this pathogen, anti-A. Baumannii vaccines research has continued unearthing various antigens with variable results over the last decade. Again, other approaches, including pan-genomics, subtractive proteomics, and reverse vaccination strategies, have shown promise for identifying promiscuous core vaccine candidates that resulted in chimeric vaccine constructs. In addition, the integration of basic knowledge of the pathobiology of this drug-resistant bacteria has also facilitated the development of effective multiantigen vaccines. As opposed to the conventional trial-and-error approach, incorporating the in silico methods in recent studies, particularly network analysis, has manifested a great promise in unearthing novel vaccine candidates from the A. baumannii proteome. Some studies have used multiple A. baumannii data sources to build the co-functional networks and analyze them by k-shell decomposition. Additionally, Whole Genomic Protein Interactome (GPIN) analysis has utilized a rational approach for identifying essential proteins and presenting them as vaccines effective enough to combat the deadly pathogenic threats posed by A. baumannii. Others have identified multiple immune nodes using network-based centrality measurements for synergistic antigen combinations for different vaccination strategies. Protein-protein interactions have also been inferenced utilizing structural approaches, such as molecular docking and molecular dynamics simulation. Similar workflows and technologies were employed to unveil novel A. baumannii drug targets, with a similar trend in the increasing influx of in silico techniques. This review integrates the latest knowledge on the development of A. baumannii vaccines while highlighting the in silico methods as the future of such exploratory research. In parallel, we also briefly summarize recent advancements in A. baumannii drug target research.

Generation and Utilization of a Monoclonal Antibody against Hepatitis B Virus Core Protein for a Comprehensive Interactome Analysis.

Hepatitis B virus (HBV) core antigen (HBc) is a structural protein that forms the viral nucleocapsid and is involved in various steps of the viral replication cycle, but its role in the pathogenesis of HBV infection is still elusive. In this study, we generated a mouse monoclonal antibody (mAb) against HBc and used it in antibody-based in situ biotinylation analysis in order to identify host proteins that interact with HBc. HBc antigen was produced with a wheat germ cell-free protein synthesis system and used to immunize mice. Among the established hybridoma clones, a single clone (mAb #7) was selected and further characterized for its ability in the antibody-based in situ biotinylation analysis to collect host proteins that are in the vicinity of HBc. Using mass spectrometry, we identified 215 HBc-interacting host proteins, three of which bind HBc most significantly under hypoxic conditions. Our results indicate that mAb #7 can be used to systematically identify host proteins that interact with HBc under pathophysiological conditions, and thus may be useful to explore the molecular pathways involved in HBV-induced cytopathogenesis.

Computational analysis of human host binding partners of chikungunya and dengue viruses during coinfection.

Mosquito-borne viral diseases like chikungunya and dengue infections can cause severe illness and have become major public health concerns. Chikungunya virus (CHIKV) and dengue virus (DENV) infections share similar primary clinical manifestations and are transmitted by the same vector. Thus, the probability of their coinfection gets increased with more severe clinical complications in the patients. The present study was undertaken to elucidate the common human interacting partners of CHIKV and DENV proteins during coinfection. The viral-host protein-protein interactome was constructed using Cytoscape. Subsequently, significant host interactors were identified during coinfection. The network analysis elucidated 57 human proteins interacting with both CHIKV and DENV, represented as hub-bottlenecks. The functional and biological analyses of the 40 hub-bottlenecks revealed that they are associated with phosphoinositide 3-kinases (PI3K)/AKT, p53 signaling pathways, regulation of cell cycle and apoptosis during coinfection. Moreover, the molecular docking analysis uncovered the tight and robust binding of selected hub-bottlenecks with CHIKV/DENV proteins. Additionally, 23 hub-bottlenecks were predicted as druggable candidates that could be targeted to eradicate the host-viral interactions. The elucidated common host binding partners during DENV and CHIKV coinfection as well as indicated approved drugs can support the therapeutics development.