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Islam MA, Kibria MK, Hossen MB, Reza MS, Tasmia SA, Tuly KF, Mosharof MP, Kabir SR, Kabir MH, Mollah MNH. Bioinformatics-based investigation on the genetic influence between SARS-CoV-2 infections and idiopathic pulmonary fibrosis (IPF) diseases, and drug repurposing. Sci Rep 2023; 13:4685. [PMID: 36949176 PMCID: PMC10031699 DOI: 10.1038/s41598-023-31276-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Accepted: 03/09/2023] [Indexed: 03/24/2023] Open
Abstract
Some recent studies showed that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and idiopathic pulmonary fibrosis (IPF) disease might stimulate each other through the shared genes. Therefore, in this study, an attempt was made to explore common genomic biomarkers for SARS-CoV-2 infections and IPF disease highlighting their functions, pathways, regulators and associated drug molecules. At first, we identified 32 statistically significant common differentially expressed genes (cDEGs) between disease (SARS-CoV-2 and IPF) and control samples of RNA-Seq profiles by using a statistical r-package (edgeR). Then we detected 10 cDEGs (CXCR4, TNFAIP3, VCAM1, NLRP3, TNFAIP6, SELE, MX2, IRF4, UBD and CH25H) out of 32 as the common hub genes (cHubGs) by the protein-protein interaction (PPI) network analysis. The cHubGs regulatory network analysis detected few key TFs-proteins and miRNAs as the transcriptional and post-transcriptional regulators of cHubGs. The cDEGs-set enrichment analysis identified some crucial SARS-CoV-2 and IPF causing common molecular mechanisms including biological processes, molecular functions, cellular components and signaling pathways. Then, we suggested the cHubGs-guided top-ranked 10 candidate drug molecules (Tegobuvir, Nilotinib, Digoxin, Proscillaridin, Simeprevir, Sorafenib, Torin 2, Rapamycin, Vancomycin and Hesperidin) for the treatment against SARS-CoV-2 infections with IFP diseases as comorbidity. Finally, we investigated the resistance performance of our proposed drug molecules compare to the already published molecules, against the state-of-the-art alternatives publicly available top-ranked independent receptors by molecular docking analysis. Molecular docking results suggested that our proposed drug molecules would be more effective compare to the already published drug molecules. Thus, the findings of this study might be played a vital role for diagnosis and therapies of SARS-CoV-2 infections with IPF disease as comorbidity risk.
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Affiliation(s)
- Md Ariful Islam
- Bioinformatics Lab(Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Md Kaderi Kibria
- Bioinformatics Lab(Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Md Bayazid Hossen
- Bioinformatics Lab(Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Md Selim Reza
- Bioinformatics Lab(Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Samme Amena Tasmia
- Bioinformatics Lab(Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Khanis Farhana Tuly
- Bioinformatics Lab(Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Md Parvez Mosharof
- Bioinformatics Lab(Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh
- School of Business, University of Southern Queensland, Toowoomba, QLD, 4350, Australia
| | - Syed Rashel Kabir
- Department of Biochemistry and Molecular Biology, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Md Hadiul Kabir
- Bioinformatics Lab(Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh
| | - Md Nurul Haque Mollah
- Bioinformatics Lab(Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh.
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Sarker B, Rahaman MM, Islam MA, Alamin MH, Husain MM, Ferdousi F, Ahsan MA, Mollah MNH. Identification of host genomic biomarkers from multiple transcriptomics datasets for diagnosis and therapies of SARS-CoV-2 infections. PLoS One 2023; 18:e0281981. [PMID: 36913345 PMCID: PMC10010564 DOI: 10.1371/journal.pone.0281981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 02/05/2023] [Indexed: 03/14/2023] Open
Abstract
The pandemic of COVID-19 is a severe threat to human life and the global economy. Despite the success of vaccination efforts in reducing the spread of the virus, the situation remains largely uncontrolled due to the random mutation in the RNA sequence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which demands different variants of effective drugs. Disease-causing gene-mediated proteins are usually used as receptors to explore effective drug molecules. In this study, we analyzed two different RNA-Seq and one microarray gene expression profile datasets by integrating EdgeR, LIMMA, weighted gene co-expression network and robust rank aggregation approaches, which revealed SARS-CoV-2 infection causing eight hub-genes (HubGs) including HubGs; REL, AURKA, AURKB, FBXL3, OAS1, STAT4, MMP2 and IL6 as the host genomic biomarkers. Gene Ontology and pathway enrichment analyses of HubGs significantly enriched some crucial biological processes, molecular functions, cellular components and signaling pathways that are associated with the mechanisms of SARS-CoV-2 infections. Regulatory network analysis identified top-ranked 5 TFs (SRF, PBX1, MEIS1, ESR1 and MYC) and 5 miRNAs (hsa-miR-106b-5p, hsa-miR-20b-5p, hsa-miR-93-5p, hsa-miR-106a-5p and hsa-miR-20a-5p) as the key transcriptional and post-transcriptional regulators of HubGs. Then, we conducted a molecular docking analysis to determine potential drug candidates that could interact with HubGs-mediated receptors. This analysis resulted in the identification of top-ranked ten drug agents, including Nilotinib, Tegobuvir, Digoxin, Proscillaridin, Olysio, Simeprevir, Hesperidin, Oleanolic Acid, Naltrindole and Danoprevir. Finally, we investigated the binding stability of the top-ranked three drug molecules Nilotinib, Tegobuvir and Proscillaridin with the three top-ranked proposed receptors (AURKA, AURKB, OAS1) by using 100 ns MD-based MM-PBSA simulations and observed their stable performance. Therefore, the findings of this study might be useful resources for diagnosis and therapies of SARS-CoV-2 infections.
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Affiliation(s)
- Bandhan Sarker
- Faculty of Science, Department of Statistics, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh
- Department of Statistics, Bioinformatics Laboratory (Dry), University of Rajshahi, Rajshahi, Bangladesh
| | - Md. Matiur Rahaman
- Faculty of Science, Department of Statistics, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh
| | - Md. Ariful Islam
- Department of Statistics, Bioinformatics Laboratory (Dry), University of Rajshahi, Rajshahi, Bangladesh
| | - Muhammad Habibulla Alamin
- Faculty of Science, Department of Statistics, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh
| | - Md. Maidul Husain
- Faculty of Science, Department of Statistics, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh
| | - Farzana Ferdousi
- Faculty of Science, Department of Statistics, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh
| | - Md. Asif Ahsan
- Department of Statistics, Bioinformatics Laboratory (Dry), University of Rajshahi, Rajshahi, Bangladesh
- Liangzhu Laboratory, Zhejiang University Medical Center, Zhejiang University, Hangzhou, Zhejiang, China
| | - Md. Nurul Haque Mollah
- Department of Statistics, Bioinformatics Laboratory (Dry), University of Rajshahi, Rajshahi, Bangladesh
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Mosharaf MP, Kibria MK, Hossen MB, Islam MA, Reza MS, Mahumud RA, Alam K, Gow J, Mollah MNH. Meta-Data Analysis to Explore the Hub of the Hub-Genes That Influence SARS-CoV-2 Infections Highlighting Their Pathogenetic Processes and Drugs Repurposing. Vaccines (Basel) 2022; 10:vaccines10081248. [PMID: 36016137 PMCID: PMC9415433 DOI: 10.3390/vaccines10081248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 07/27/2022] [Accepted: 07/30/2022] [Indexed: 01/09/2023] Open
Abstract
The pandemic of SARS-CoV-2 infections is a severe threat to human life and the world economic condition. Although vaccination has reduced the outspread, but still the situation is not under control because of the instability of RNA sequence patterns of SARS-CoV-2, which requires effective drugs. Several studies have suggested that the SARS-CoV-2 infection causing hub differentially expressed genes (Hub-DEGs). However, we observed that there was not any common hub gene (Hub-DEGs) in our analyses. Therefore, it may be difficult to take a common treatment plan against SARS-CoV-2 infections globally. The goal of this study was to examine if more representative Hub-DEGs from published studies by means of hub of Hub-DEGs (hHub-DEGs) and associated potential candidate drugs. In this study, we reviewed 41 articles on transcriptomic data analysis of SARS-CoV-2 and found 370 unique hub genes or studied genes in total. Then, we selected 14 more representative Hub-DEGs (AKT1, APP, CXCL8, EGFR, IL6, INS, JUN, MAPK1, STAT3, TNF, TP53, UBA52, UBC, VEGFA) as hHub-DEGs by their protein-protein interaction analysis. Their associated biological functional processes, transcriptional, and post-transcriptional regulatory factors. Then we detected hHub-DEGs guided top-ranked nine candidate drug agents (Digoxin, Avermectin, Simeprevir, Nelfinavir Mesylate, Proscillaridin, Linifanib, Withaferin, Amuvatinib, Atazanavir) by molecular docking and cross-validation for treatment of SARS-CoV-2 infections. Therefore, the findings of this study could be useful in formulating a common treatment plan against SARS-CoV-2 infections globally.
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Affiliation(s)
- Md. Parvez Mosharaf
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (M.P.M.); (M.K.K.); (M.B.H.); (M.A.I.); (M.S.R.)
- School of Business, Faculty of Business, Education, Law and Arts, University of Southern Queensland, Toowoomba, QLD 4350, Australia; (K.A.); (J.G.)
| | - Md. Kaderi Kibria
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (M.P.M.); (M.K.K.); (M.B.H.); (M.A.I.); (M.S.R.)
| | - Md. Bayazid Hossen
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (M.P.M.); (M.K.K.); (M.B.H.); (M.A.I.); (M.S.R.)
| | - Md. Ariful Islam
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (M.P.M.); (M.K.K.); (M.B.H.); (M.A.I.); (M.S.R.)
| | - Md. Selim Reza
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (M.P.M.); (M.K.K.); (M.B.H.); (M.A.I.); (M.S.R.)
| | - Rashidul Alam Mahumud
- NHMRC Clinical Trials Centre, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia;
| | - Khorshed Alam
- School of Business, Faculty of Business, Education, Law and Arts, University of Southern Queensland, Toowoomba, QLD 4350, Australia; (K.A.); (J.G.)
| | - Jeff Gow
- School of Business, Faculty of Business, Education, Law and Arts, University of Southern Queensland, Toowoomba, QLD 4350, Australia; (K.A.); (J.G.)
- School of Accounting, Economics and Finance, University of KwaZulu Natal, Durban 4001, South Africa
| | - Md. Nurul Haque Mollah
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (M.P.M.); (M.K.K.); (M.B.H.); (M.A.I.); (M.S.R.)
- Correspondence:
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