key: cord-0879620-0sdjy80s authors: Hazra, Suvojit; Chaudhuri, Alok Ghosh; Tiwary, Basant K.; Chakrabarti, Nilkanta title: Matrix metallopeptidase 9 as a host protein target of chloroquine and melatonin for immunoregulation in COVID-19: A network-based meta-analysis date: 2020-07-15 journal: Life Sci DOI: 10.1016/j.lfs.2020.118096 sha: c38cfc1d755381afc0c6361298c55ac3a2db2010 doc_id: 879620 cord_uid: 0sdjy80s AIMS: The molecular pathogenesis of COVID-19 is similar to other coronavirus (CoV) infections viz. severe acute respiratory syndrome (SARS) in human. Due to scarcity of the suitable treatment strategy, the present study was undertaken to explore host protein(s) targeted by potent repurposed drug(s) in COVID-19. MATERIALS AND METHODS: The differentially expressed genes (DEGs) were identified from microarray data repository of SARS-CoV patient blood. The repurposed drugs for COVID-19 were selected from available literature. Using DEGs and drugs, the protein-protein interaction (PPI) and chemo-protein interaction (CPI) networks were constructed and combined to develop an interactome model of PPI-CPI network. The top-ranked sub-network with its hub-bottleneck nodes were evaluated with their functional annotations. KEY FINDINGS: A total of 120 DEGs and 65 drugs were identified. The PPI-CPI network (118 nodes and 293 edges) exhibited a top-ranked sub-network (35 nodes and 174 connectivities) with 12 hub-bottleneck nodes having two drugs chloroquine and melatonin in association with 10 proteins corresponding to six upregulated and four downregulated genes. Two drugs interacted directly with the hub-bottleneck node i.e. matrix metallopeptidase 9 (MMP9), a host protein corresponding to its upregulated gene. MMP9 showed functional annotations associated with neutrophil mediated immunoinflammation. Moreover, literature survey revealed that angiotensin converting enzyme 2, a membrane receptor of SARS-CoV-2 virus, might have functional cooperativity with MMP9 and a possible interaction with both drugs. SIGNIFICANCE: The present study reveals that between chloroquine and melatonin, melatonin appears to be more promising repurposed drug against MMP9 for better immunocompromisation in COVID-19. J o u r n a l P r e -p r o o f (inclusion of loops i.e. self-edges in neighborhood density calculation) and 'degree cut-off 2' (number of connections necessary for a node to be scored). The cluster finding cut-off parameters were 'node score cut-off 0.2' (cluster size for selection of new members), hairfall included (deletion of all single connected nodes from clusters), fluff included (allowance of cluster expansion with one neighbor shells), node density cut-off 0.1 (controls the neighbor inclusion criteria during 'fluffing'), K-core cut-off 2 (filters out clusters by eliminating small inter-connected sub-cluster) and maximum depth of network cut-off 100 (limiting the distance from the seed node within which the cluster member can be searched). The chemo-protein components of overall PPI-CPI interactome were analyzed in CentiScaPe 2.2 [34] plugin of Cytoscape using key network centrality parameters like node degree (the number of neighboring nodes to which the node of interest is directly connected), shortest path betweenness (the number of information streams passing through a given node) and stress (the extent to which a node can hold network communications) to identify the most potential nodes in J o u r n a l P r e -p r o o f The list of genes of interest with their identifiers (ID) found in the top sub-network of PPI-CPI interactome was submitted to Enrichr web-tool platform (http://amp.pharm.mssm.edu/Enrichr) [35, 36] for the enrichment (i.e. over representation of common annotated biological features) analysis of functional annotations implemented across a number of resources including 'gene ontology' ('biological process', 'cellular component', 'molecular function'), 'KEGG biological pathways', 'Jensen Disease'. The Enrichr analysis was performed using statistical parameters viz. p-value (Fisher exact test), q-value (adjusted p-value for false discovery rate), old p-value, adjusted old p-value, odd ratio, z-score and combined score (log(p-value)×z-value) The Enriched results (functional annotations) were ranked based on the levels of significance with p-values < 0.05 and corresponding combined scores followed by selection of terms with certain cut-off (top 10 terms). (log(p-value)×z-value) J o u r n a l P r e -p r o o f The results found in the present mechanistic systems biology analysis are systematically documented in the flow diagram with the findings of potential drugs against the targeted biomolecule(s) in COVID-19 ( Fig. 1 ). From in silico analysis of SARS microarray dataset we identified 120 differentially expressed genes among which 45 genes were upregulated and 75 genes were downregulated. Details of the differentially expressed genes including gene identifiers (ID), "false discovery rate" (FDR) adjusted p-values (<0.05) and log 2 (fold change) values (>1) are summarized in Figure 2 . The interactome model of PPI network was constructed using proteins corresponding to the respective DEGs of SARS-CoV patients in STRING webtool. A total of 72 protein nodes and 212 connections had been found in PPI network (data not shown). Literature survey provided a total of 65 potential drugs proposed for treatment of COVID-19 (Table 1 ) and these drugs were included in further analysis for selection of most potent drug(s) against putative protein target(s). The interactome model of CPI network was constructed using COVID-19 drug candidates and J o u r n a l P r e -p r o o f DEGs of SARS-CoV patients in STITCH webtool. Total 88 nodes (proteins and drugs) and 120 connections had been found in the CPI network (data not shown). The characterization of protein-drug interactions in COVID-19 had been executed through development of interactome model of PPI-CPI network in Cytoscape by merging the already identified PPI and CPI network and that was found to be composed of 118 nodes (proteins and drugs) interconnected by 293 interactions (Fig. 3A) . The identification of nodes of gene products/proteins and drugs has been designated by the corresponding gene IDs and name of the drugs respectively in the present study. Accordingly, the respective gene IDs have been used as the node (protein) identifiers in the further descriptions. From the interactome model of PPI-CPI network, the MCODE module in Cytoscape identified only one top-ranked sub-network (cluster having MCODE score 9.33) that comprised 35 nodes J o u r n a l P r e -p r o o f Gene enrichment analysis study (Fig. 5 ) indicated that the gene products of the top-ranked subnetwork were associated with biological processes including neutrophil related processes (neutrophil activation, neutrophil degranulation, neutrophil mediated immunity and immune responses), innate immune responses in mucosa, humoral immune responses mediated by antimicrobial peptides, antibacterial humoral responses, defence responses to bacteria with high statistical significances (Enrichr p-value < 0.05 and combined score). The association of the gene products of this sub-network were found to be statistically significant (Enrichr p-value < 0.05 and combined score) for the cellular components involving subcellular and granular secretary functions. Statistically significant (Enrichr p-value < 0.05 and combined score) molecular functions like nuclear hormone receptor bindings, iron and transition metal ion bindings, serinetype endopeptidase activities, endonuclease and ribonuclease activities and RNA polymerase-II core promoter proximal region sequence-specific DNA bindings were also associated with the gene products of this sub-network. In addition, KEGG pathway enrichment study included The present study developed a chemo-protein interactome network (Fig. 3A ) on basis of differentially expressed genes in SARS-CoV infection (Fig. 2) and repurposed drugs for COVID-19 (Table 1) . A sub-network (Fig. 3B ) was identified that appeared to be involved in neutrophil activation and degranulation pathways ( ARDS is the main cause of morbidities in COVID-19 and infections of other coronaviruses [5] [6] [7] 37, 38] . Cytokine storm is a key mechanism of ARDS materialization leading to multiorgan failure and death [5, 6, 39, 40] . Till date, the molecular pathogenesis of COVID-19 is unclear. Therefore, the similar mechanism of SARS-CoV/MERS-CoV infection can confer a lot to the molecular level of understanding in pathogenesis of COVID-19 [6] . The present study identified a sub-network (Fig. 3B ) that includes the statistically significant pathways of both neutrophil activation and degranulation (Fig. 5) . The sub-network comprised 29.66% nodes (proteins) and provided 59.38% connectivities of the overall network, which indicated the colossal importance of this sub-network in the whole network model (Fig. 3A-B) . The global and local topological analyses provided ten potential protein molecules consisting of six proteins corresponding to These ten nodes appeared to be the hub nodes of the PPI-CPI interactome network and were chosen for further study (Fig. 4C ). All these molecules had been found to be highly enriched in blood after antimicrobial-induced neutrophil-mediated humoral and innate immunity responses in COVID-19 (Fig. 5 ). In the present study, MMP9 was found as the functionally important hub node (protein) and target of the drugs in the central hub node of the PPI-CPI interactome network ( Fig. 3B and Fig 4C) . Matrix metallopeptidases (MMPs), the zinc-containing and calcium-dependent proteolytic endopeptidases, are released from the intracellular stores and become active extracellularly [41] . MMPs cause deterioration of a number of extracellular matrix proteins that help in the extracellular matrix remodelling in various physiological and pathological processes including inflammation [41] [42] [43] [44] . MMPs are widely distributed in tissues and their expressions are controlled by cytokines, growth factors and hormones. MMP9 (83kD), a glycoprotein with type-IV collagenase activity, is found in neutrophils, lymphocytes and dendritic cells that are involved in angiogenesis and inflammatory cytokine generation [41, 44] . Notably, the Enrichr functional analysis in the current study revealed MMP9 as to be associated with transition ion binding (molecular function under gene ontology) and diverse pathophysiological conditions viz. (Fig. 5) . MMP9 is reported to relate with tertiary lumens for release of cytokines during neutrophil activation [53] . In monocytes and macrophages, MMP9 is over-activated by plasmin and reacts with 'toll like receptor 9' (TLR9) signalling to induce formation of tumour necrosis factor (TNF) that leads to the development of pro-inflammatory cytokine storm [54, 55] . The involvement of MMP9 with serine protease activities was also noticed in Enrichr functional analysis with molecular function under gene ontology (Fig. 5) . MMP9 deficiency is found to be protective against severe H1N1 influenza virus A infection in mice model [56] . Therefore, our J o u r n a l P r e -p r o o f findings and other reports support the view that the approach to MMP9 inhibition and/or alterations of its activators (plasmin) and inhibitors (TIMP1) may prevent the deadly cytokine storm and the life-risk of COVID-19 patients. Here, both chloroquine and melatonin were identified as the repurposed drug candidates that appeared to be the interacting partners of MMP9 (Fig. 3B and Fig. 4) . Chloroquine treatment decreases serum MMP9 level in systemic lupus erythematosus [57] and suppresses MMP9 activity and its mRNA expression in breast cancer [58] . Chloroquine can also lower the TNFmediated neutrophil apoptosis, neutrophil degranulation and cytokine burst [59] [60] [61] [62] [63] . Chloroquine/hydroxychloroquine efficiently inhibits the human retrovirus activities in vitro [64] . Recently, a number of studies [17, 65, 66] and a clinical trial [67] support the use of chloroquine/hydroxychloroquine for the treatment of COVID-19. Conversely, certain clinical studies strongly disagree with its uses [68] [69] [70] , as it develops cardiac failure in COVID-19 patients [68] , indicating the clinical data about chloroquine/hydroxychloroquine are not conclusive [71] . Notably, hydroxychloroquine did not appear in the sub-network in the present study (Fig-3B ) and remained unattained for further consideration. Melatonin is responsible for normal sleep and maintenance of the 'biological clock' in human [72] . It has anti-inflammatory properties [73, 74] , exerts its potential role in anti-viral mechanism [74] [75] [76] [77] [78] and has also been used in Ebola virus infection [78] . The pathophysiological observation in COVID-19 patients supports the chronobiological uses of melatonin in its treatment [79, 80] and a therapeutic algorithm in this regard has also been proposed recently [81] . In addition, melatonin is reported as the promising adjuvant for COVID-19 treatment [21, 82] and its J o u r n a l P r e -p r o o f deficiencies may enhance susceptibility of diabetic and hypertensive elderly patients in SARS-CoV-2 infection [80] . The first clinical trial of melatonin in a small cohort indicates its involvement in abating ARDS in COVID-19 patients [83] . Interestingly, melatonin can bind to the active site of MMP9 and inhibit the latter to arrest immunoinflammation [84] . Thus, the present network based meta-analysis justified the involvement of melatonin interaction with MMP9 in immunocompromised COVID-19. The cell culture study (kidney cell line Vero E6) and network analysis reveal that chloroquine [85] and melatonin [21] respectively may have potential anti-viral role in targeting human cell membrane-bound ACE2 receptor, a zinc dependent carboxypeptidase, and other associated protein partners in COVID-19. Interestingly, separate studies report that MMP9 level increases in ACE2-knockout mice model [86] and ACE inhibitors (lisinopril and imidapril) also target MMP9 along with ACE2 [87] . Therefore, both metallopeptidases i.e. ACE2 and MMP9 may have cooperativities for immunoinflammation in COVID-19 and can be potential targets of both chloroquine and melatonin therapies. [6, [88] [89] [90] [91] [92] [93] . The ectodomain of membrane-bound ACE2 is shed into the extracellular fluid as its soluble form [88, [94] [95] [96] . In vitro studies also indicate that the soluble ACE2 can bind to SARS-CoV/SARS-CoV-2 and is supposed to limit the availability of viruses to interact with the membrane-bound ACE2 receptors thus minimizing the chances of viral load [88, 92, 94] . Notably, ACE2 converts angiotensin-II to angiotensin(1-7), a peptide which causes modification of inflammatory processes [97] . Angiotensin(1-7) also has a vasodilatory effect [98] and enhances the heart rate acting on the caudal ventrolateral medulla in the brain [99] , which may contribute to the development of hypotension and tachycardia as found in SARS/COVID-19 patients [100] . Moreover, the interaction of SARS/SARS-CoV-2 with the ACE2 receptors of the support cells in olfactory mucosa also results in inflammation-induced anosmia [101] . 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