Deciphering molecular bridges: Unveiling the interplay between metabolic syndrome and Alzheimer's disease through a systems biology approach and drug repurposing.

The association between Alzheimer's disease and metabolic disorders as significant risk factors is widely acknowledged. However, the intricate molecular mechanism intertwining these conditions remains elusive. To address this knowledge gap, we conducted a thorough investigation using a bioinformatics method to illuminate the molecular connections and pathways that provide novel perspectives on these disorders' pathological and clinical features. Microarray datasets (GSE5281, GSE122063) from the Gene Expression Omnibus (GEO) database facilitated the way to identify genes with differential expression in Alzheimer's disease (141 genes). Leveraging CoreMine, CTD, and Gene Card databases, we extracted genes associated with metabolic conditions, including hypertension, non-alcoholic fatty liver disease, and diabetes. Subsequent analysis uncovered overlapping genes implicated in metabolic conditions and Alzheimer's disease, revealing shared molecular links. We utilized String and HIPPIE databases to visualize these shared genes' protein-protein interactions (PPI) and constructed a PPI network using Cytoscape and MCODE plugin. SPP1, CD44, IGF1, and FLT1 were identified as crucial molecules in the main cluster of Alzheimer's disease and metabolic syndrome. Enrichment analysis by the DAVID dataset was employed and highlighted the SPP1 as a novel target, with its receptor CD44 playing a significant role in the inflammatory cascade and disruption of insulin signaling, contributing to the neurodegenerative aspects of Alzheimer's disease. ECM-receptor interactions, focal adhesion, and the PI3K/Akt pathways may all mediate these effects. Additionally, we investigated potential medications by repurposing the molecular links using the DGIdb database, revealing Tacrolimus and Calcitonin as promising candidates, particularly since they possess binding sites on the SPP1 molecule. In conclusion, our study unveils crucial molecular bridges between metabolic syndrome and AD, providing insights into their pathophysiology for therapeutic interventions.

Deciphering the similarities and disparities of molecular mechanisms behind respiratory epithelium response to HCoV-229E and SARS-CoV-2 and drug repurposing, a systems biology approach.

PURPOSE: Identifying the molecular mechanisms behind SARS-CoV-2 disparities and similarities will help find new treatments. The present study determines networks' shared and non-shared (specific) crucial elements in response to HCoV-229E and SARS-CoV-2 viruses to recommend candidate medications. METHODS: We retrieved the omics data on respiratory cells infected with HCoV-229E and SARS-CoV-2, constructed PPIN and GRN, and detected clusters and motifs. Using a drug-gene interaction network, we determined the similarities and disparities of mechanisms behind their host response and drug-repurposed. RESULTS: CXCL1, KLHL21, SMAD3, HIF1A, and STAT1 were the shared DEGs between both viruses' protein-protein interaction network (PPIN) and gene regulatory network (GRN). The NPM1 was a specific critical node for HCoV-229E and was a Hub-Bottleneck shared between PPI and GRN in HCoV-229E. The HLA-F, ADCY5, TRIM14, RPF1, and FGA were the seed proteins in subnetworks of the SARS-CoV-2 PPI network, and HSPA1A and RPL26 proteins were the seed in subnetworks of the PPI network of HCOV-229E. TRIM14, STAT2, and HLA-F played the same role for SARS-CoV-2. Top enriched KEGG pathways included cell cycle and proteasome in HCoV-229E and RIG-I-like receptor, Chemokine, Cytokine-cytokine, NOD-like receptor, and TNF signaling pathways in SARS-CoV-2. We suggest some candidate medications for COVID-19 patient lungs, including Noscapine, Isoetharine mesylate, Cycloserine, Ethamsylate, Cetylpyridinium, Tretinoin, Ixazomib, Vorinostat, Venetoclax, Vorinostat, Ixazomib, Venetoclax, and epoetin alfa for further in-vitro and in-vivo investigations. CONCLUSION: We suggested CXCL1, KLHL21, SMAD3, HIF1A, and STAT1, ADCY5, TRIM14, RPF1, and FGA, STAT2, and HLA-F as critical genes and Cetylpyridinium, Cycloserine, Noscapine, Ethamsylate, Epoetin alfa, Isoetharine mesylate, Ribavirin, and Tretinoin drugs to study further their importance in treating COVID-19 lung complications.

COVID-19: A novel holistic systems biology approach to predict its molecular mechanisms (in vitro) and repurpose drugs.

PURPOSE: COVID-19 strangely kills some youth with no history of physical weakness, and in addition to the lungs, it may even directly harm other organs. Its complex mechanism has led to the loss of any significantly effective drug, and some patients with severe forms still die daily. Common methods for identifying disease mechanisms and drug design are often time-consuming or reductionist. Here, we use a novel holistic systems biology approach to predict its molecular mechanisms (in vitro), significant molecular relations with SARS, and repurpose drugs. METHODS: We have utilized its relative phylogenic similarity to SARS. Using the available omics data for SARS and the fewer data for COVID-19 to decode the mechanisms and their significant relations, We applied the Cytoscape analyzer, MCODE, STRING, and DAVID tools to predict the topographically crucial molecules, clusters, protein interaction mappings, and functional analysis. We also applied a novel approach to identify the significant relations between the two infections using the Fischer exact test for MCODE clusters. We then constructed and analyzed a drug-gene network using PharmGKB and DrugBank (retrieved using the dgidb). RESULTS: Some of the shared identified crucial molecules, BPs and pathways included Kaposi sarcoma-associated herpesvirus infection, Influenza A, and NOD-like receptor signaling pathways. Besides, our identified crucial molecules specific to host response against SARS-CoV-2 included FGA, BMP4, PRPF40A, and IFI16. CONCLUSION: We also introduced seven new repurposed candidate drugs based on the drug-gene network analysis for the identified crucial molecules. Therefore, we suggest that our newly recommended repurposed drugs be further investigated in Vitro and in Vivo against COVID-19.

Deciphering molecular mechanisms of SARS-CoV-2 pathogenesis and drug repurposing through GRN motifs: a comprehensive systems biology study.

The world has recently been plagued by a new coronavirus infection called SARS-CoV-2. This virus may lead to severe acute respiratory syndrome followed by multiple organ failure. SARS-CoV-2 has approximately 80-90% genetic similarity to SARS-CoV. Given the limited omics data available for host response to the viruses (more limited data for SARS-CoV-2), we attempted to unveil the crucial molecular mechanisms underlying the SARS-CoV-2 pathogenesis by comparing its regulatory network motifs with SARS-CoV. We also attempted to identify the non-shared crucial molecules and their functions to predict the specific mechanisms for each infection and the processes responsible for their different manifestations. Deciphering the crucial shared and non-shared mechanisms at the molecular level and signaling pathways underlying both diseases may help shed light on their pathogenesis and pave the way for other new drug repurposing against COVID-19. We constructed the GRNs for host response to SARS-CoV and SARS-CoV-2 pathogens (in vitro) and identified the significant 3-node regulatory motifs by analyzing them topologically and functionally. We attempted to identify the shared and non-shared regulatory elements and signaling pathways between their host responses. Interestingly, our findings indicated that NFKB1, JUN, STAT1, FOS, KLF4, and EGR1 were the critical shared TFs between motif-related subnetworks in both SARS and COVID-1, which are considered genes with specific functions in the immune response. Enrichment analysis revealed that the NOD-like receptor signaling, TNF signaling, and influenza A pathway were among the first significant pathways shared between SARS and COVID-19 up-regulated DEGs networks, and the term "metabolic pathways" (hsa01100) among the down-regulated DEGs networks. WEE1, PMAIP1, and TSC22D2 were identified as the top three hubs specific to SARS. However, MYPN, SPRY4, and APOL6 were the tops specific to COVID-19 in vitro. The term "Complement and coagulation cascades" pathway was identified as the first top non-shared pathway for COVID-19 and the MAPK signaling pathway for SARS. We used the identified crucial DEGs to construct a drug-gene interaction network to propose some drug candidates. Zinc chloride, Fostamatinib, Copper, Tirofiban, Tretinoin, and Levocarnitine were the six drugs with higher scores in our drug-gene network analysis. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03518-x.

Deciphering crucial genes in multiple sclerosis pathogenesis and drug repurposing: A systems biology approach.

This study employed systems biology and high-throughput technologies to analyze complex molecular components of MS pathophysiology, combining data from multiple omics sources to identify potential biomarkers and propose therapeutic targets and repurposed drugs for MS treatment. This study analyzed GEO microarray datasets and MS proteomics data using geWorkbench, CTD, and COREMINE to identify differentially expressed genes associated with MS disease. Protein-protein interaction networks were constructed using Cytoscape and its plugins, and functional enrichment analysis was performed to identify crucial molecules. A drug-gene interaction network was also created using DGIdb to propose medications. This study identified 592 differentially expressed genes (DEGs) associated with MS disease using GEO, proteomics, and text-mining datasets. 37 DEGs were found to be important by topographical network studies, and 6 were identified as the most significant for MS pathophysiology. Additionally, we proposed six drugs that target these key genes. Crucial molecules identified in this study were dysregulated in MS and likely play a key role in the disease mechanism, warranting further research. Additionally, we proposed repurposing certain FDA-approved drugs for MS treatment. Our in silico results were supported by previous experimental research on some of the target genes and drugs. SIGNIFICANCE: As the long-lasting investigations continue to discover new pathological territories in neurodegeneration, here we apply a systems biology approach to determine multiple sclerosis's molecular and pathophysiological origin and identify multiple sclerosis crucial genes that contribute to candidating new biomarkers and proposing new medications.

Identification of miR-3182 and miR-3143 target genes involved in the cell cycle as a novel approach in TNBC treatment: A systems biology approach.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with a poor prognosis, lacking therapeutic targets. miRNAs play crucial roles in TNBC through regulating various mechanisms, including cellular growth and proliferation. This study aims to identify critical target genes of two novel miRNAs (miR-3143 and miR-3182) involved in the cell cycle of TNBC as possible therapeutic targets and investigates their regulatory and therapeutic roles through a systems biology approach and in vitro experiment. Datasets related to the TNBC cell line (MDA-MB-231) were screened and retrieved, and Gene regulatory networks were constructed. Significant regulatory motifs were detected and analyzed using the FANMOD and Cytoscape analyzer, and the clusters and seeds were identified using the MCODE. Functional enrichment analysis was also performed using DAVID and STRING. The most critical genes were determined using the analysis of GRN motifs and PPI clusters. The essential genes involved in the cell cycle were selected and verified using the bc-GenExMiner v4.7. We overexpressed miR-3143 and miR-3182 in the MDA-MB-231 cell line using human umbilical cord mesenchymal stem cell (HUCMSC)-miRNA loaded exosomes, and the expression of the critical target genes was investigated using RT-qPCR. We identified eight critical genes as potential therapeutic targets. Their expression decreased by overexpression of miR-3143 and miR-3182 in RT-qPCR. The identified critical genes have probably significant roles in the pathogenesis of TNBC through the cell cycle. We suggest that the overexpression of miR-3143 and miR-3182 could be a new therapeutic candidate in TNBC and is worth more investigation.

Mesenchymal Stem Cells in the Treatment of New Coronavirus Pandemic: A Novel Promising Therapeutic Approach.

After severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) outbreaks, coronavirus disease 2019 (COVID-19) is the third coronavirus epidemic that soon turned into a pandemic. This virus causes acute respiratory syndrome in infected people. The mortality rate of SARS-CoV-2 infection will probably rise unless efficient treatments or vaccines are developed. The global funding and medical communities have started performing more than five hundred clinical examinations on a broad spectrum of repurposed drugs to acquire effective treatments. Besides, other novel treatment approaches have also recently emerged, including cellular host-directed therapies. They counteract the unwanted responses of the host immune system that led to the severe pathogenesis of SARS-CoV-2. This brief review focuses on mesenchymal stem cell (MSC) principles in treating the COVID-19. The US clinical trials database and the world health organization database for clinical trials have reported 82 clinical trials (altogether) exploring the effects of MSCs in COVID-19 treatment. MSCs also had better be tried for treating other pathogens worldwide. MSC treatment may have the potential to end the high mortality rate of COVID-19. Besides, it also limits the long-term inability of survivors.

A Motif-Based Network Analysis of Regulatory Patterns in Doxorubicin Effects on Treating Breast Cancer, a Systems Biology Study.

Background: Breast cancer is the most common malignancy worldwide. Doxorubicin is an anthracycline used to treat breast cancer as the first treatment choice. Nevertheless, the molecular mechanisms underlying the response to Doxorubicin and its side effects are not comprehensively understood so far. We used systems biology and bioinformatics methods to identify essential genes and molecular mechanisms behind the body response to Doxorubicin and its side effects in breast cancer patients. Methods: Omics data were extracted and analyzed to construct the protein-protein interaction and gene regulatory networks. Network analysis was performed to identify hubs, bottlenecks, clusters, and regulatory motifs to evaluate crucial genes and molecular mechanisms behind the body response to Doxorubicin and its side effects. Results: Analyzing the constructed PPI and gene-TF-miRNA regulatory network showed that MCM3, MCM10, and TP53 are key hub-bottlenecks and seed proteins. Enrichment analysis also revealed cell cycle, TP53 signaling, Forkhead box O (FoxO) signaling, and viral carcinogenesis as essential pathways in response to this drug. Besides, SNARE interactions in vesicular transport and neurotrophin signaling were identified as pathways related to the side effects of Doxorubicin. The apoptosis induction, DNA repair, invasion inhibition, metastasis, and DNA replication are suggested as critical molecular mechanisms underlying Doxorubicin anti-cancer effect. SNARE interactions in vesicular transport and neurotrophin signaling and FoxO signaling pathways in glucose metabolism are probably the mechanisms responsible for side effects of Doxorubicin. Conclusion: Following our model validation using the existing experimental data, we recommend our other newly predicted biomarkers and pathways as possible molecular mechanisms and side effects underlying the response to Doxorubicin in breast cancer requiring further investigations.

Specific Regulatory Motifs Network in SARS-CoV-2-Infected Caco-2 Cell Line, as a Model of Gastrointestinal Infections.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was primarily noted as a respiratory pathogen, but later clinical reports highlighted its extrapulmonary effects particularly on the gastrointestinal (GI) tract. The aim of the current study was the prediction of crucial genes associated with the regulatory network motifs, probably responsible for the SARS-CoV-2 effects on the GI tract. The data were obtained from a published study on the effect of SARS-CoV-2 on the Caco-2 (colon carcinoma) cell line. We used transcription factors-microRNA-gene interaction databases to find the key regulatory molecules, then analyzed the data using the FANMOD software for detection of the crucial regulatory motifs. Cytoscape software was then used to construct and analyze the regulatory network of these motifs and identify their crucial genes. Finally, GEPIA2 (Gene Expression Profiling Interactive Analysis 2) and UALCAN datasets were used to evaluate the possible relationship between crucial genes and colon cancer development. Using bioinformatics tools, we demonstrated one 3edge feed-forward loop motifs and recognized 10 crucial genes in relationship with Caco-2 cell infected by SARS-CoV-2, including SP1, TSC22D2, POU2F1, REST, NFIC, CHD7, E2F1, CEBPA, TCF7L2, and TSC22D1. The box plot analysis indicated the significant overexpression of CEBPA in colon cancer compared to normal colon tissues, while it was in contrast with the results of stage plot. However, the overall survival analysis indicated that high expression of CEBPA has positive effect on colon cancer patient survivability, verifying the results of CEBPA stage plot. We predict that the SARS-CoV-2 GI infections may cause a serious risk in colon cancer patients. However, further experimental studies are required.

Repurposing new drug candidates and identifying crucial molecules underlying PCOS Pathogenesis Based On Bioinformatics Analysis.

BACKGROUNDS: Polycystic ovary syndrome affects 7% of women of reproductive ages. Poor-quality oocytes, along with lower cleavage and implantation rates, reduce fertilization. OBJECTIVE: This study aimed to determine crucial molecular mechanisms behind PCOS pathogenesis and repurpose new drug candidates interacting with them. To predict a more in-depth insight, we applied a novel bioinformatics approach to analyze interactions between the drug-related and PCOS proteins in PCOS patients. METHODS: The newest proteomics data was retrieved from 16 proteomics datasets and was used to construct the PCOS PPI network using Cytoscape. The topological network analysis determined hubs and bottlenecks. The MCODE Plugin was used to identify highly connected regions, and the associations between PCOS clusters and drug-related proteins were evaluated using the Chi-squared/Fisher's exact test. The crucial PPI hub-bottlenecks and the shared molecules (between the PCOS clusters and drug-related proteins) were then investigated for their drug-protein interactions with previously US FDA-approved drugs to predict new drug candidates. RESULTS: The PI3K/AKT pathway was significantly related to one PCOS subnetwork and most drugs (metformin, letrozole, pioglitazone, and spironolactone); moreover, VEGF, EGF, TGFB1, AGT, AMBP, and RBP4 were identified as the shared proteins between the PCOS subnetwork and the drugs. The shared top biochemical pathways between another PCOS subnetwork and rosiglitazone included metabolic pathways, carbon metabolism, and citrate cycle, while the shared proteins included HSPB1, HSPD1, ACO2, TALDO1, VDAC1, and MDH2. We proposed some new candidate medicines for further PCOS treatment investigations, such as copper and zinc compounds, reteplase, alteplase, gliclazide, Etc. CONCLUSION: Some of the crucial molecules suggested by our model have already been experimentally reported as critical molecules in PCOS pathogenesis. Moreover, some repurposed medications have already shown beneficial effects on infertility treatment. These previous experimental reports confirm our suggestion for investigating our other repurposed drugs (in vitro and in vivo).

Identification of FDA approved drugs against SARS-CoV-2 RNA dependent RNA polymerase (RdRp) and 3-chymotrypsin-like protease (3CLpro), drug repurposing approach.

The RNA-dependent RNA polymerase (RdRp) and 3C-like protease (3CLpro) from SARS-CoV-2 play crucial roles in the viral life cycle and are considered the most promising targets for drug discovery against SARS-CoV-2. In this study, FDA-approved drugs were screened to identify the probable anti-RdRp and 3CLpro inhibitors by molecular docking approach. The number of ligands selected from the PubChem database of NCBI for screening was 1760. Ligands were energy minimized using Open Babel. The RdRp and 3CLpro protein sequences were retrieved from the NCBI database. For Homology Modeling predictions, we used the Swiss model server. Their structure was then energetically minimized using SPDB viewer software and visualized in the CHIMERA UCSF software. Molecular dockings were performed using AutoDock Vina, and candidate drugs were selected based on binding affinity (∆G). Hydrogen bonding and hydrophobic interactions between ligands and proteins were visualized using Ligplot and the Discovery Studio Visualizer v3.0 software. Our results showed 58 drugs against RdRp, which had binding energy of - 8.5 or less, and 69 drugs to inhibit the 3CLpro enzyme with a binding energy of - 8.1 or less. Six drugs based on binding energy and number of hydrogen bonds were chosen for the next step of molecular dynamics (MD) simulations to investigate drug-protein interactions (including Nilotinib, Imatinib and dihydroergotamine for 3clpro and Lapatinib, Dexasone and Relategravir for RdRp). Except for Lapatinib, other drugs-complexes were stable during MD simulation. Raltegravir, an anti-HIV drug, was observed to be the best compound against RdRp based on docking binding energy (-9.5 kcal/mole) and MD results. According to the MD results and binding energy, dihydroergotamine is a suitable candidate for 3clpro inhibition (-9.6 kcal/mol). These drugs were classified into several categories, including antiviral, antibacterial, anti-inflammatory, anti-allergic, cardiovascular, anticoagulant, BPH and impotence, antipsychotic, antimigraine, anticancer, and so on. The common prescription-indications for some of these medication categories appeared somewhat in line with manifestations of COVID-19. We hope that they can be beneficial for patients with certain specific symptoms of SARS-CoV-2 infection, but they can also probably inhibit viral enzymes. We recommend further experimental evaluations in vitro and in vivo on these FDA-approved drugs to assess their potential antiviral effect on SARS-CoV-2.