Abstract
The pandemic threat of COVID-19 has severely destroyed human life as well as the economy around the world. Although, the vaccination has reduced the outspread, but people are still suffering due to the unstable RNA sequence patterns of SARS-CoV-2 which demands supplementary drugs. To explore novel drug target proteins, in this study, a transcriptomics RNA-Seq data generated from SARS-CoV-2 infection and control samples were analyzed. We identified 109 differentially expressed genes (DEGs) that were utilized to identify 10 hub-genes/proteins (TLR2, USP53, GUCY1A2, SNRPD2, NEDD9, IGF2, CXCL2, KLF6, PAG1 and ZFP36) by the protein–protein interaction (PPI) network analysis. The GO functional and KEGG pathway enrichment analyses of hub-DEGs revealed some important functions and signaling pathways that are significantly associated with SARS-CoV-2 infections. The interaction network analysis identified 5 TFs proteins and 6 miRNAs as the key regulators of hub-DEGs. Considering 10 hub-proteins and 5 key TFs-proteins as drug target receptors, we performed their docking analysis with the SARS-CoV-2 3CL protease-guided top listed 90 FDA approved drugs. We found Torin-2, Rapamycin, Radotinib, Ivermectin, Thiostrepton, Tacrolimus and Daclatasvir as the top ranked seven candidate drugs. We investigated their resistance performance against the already published COVID-19 causing top-ranked 11 independent and 8 protonated receptor proteins by molecular docking analysis and found their strong binding affinities, which indicates that the proposed drugs are effective against the state-of-the-arts alternatives independent receptor proteins also. Finally, we investigated the stability of top three drugs (Torin-2, Rapamycin and Radotinib) by using 100 ns MD-based MM-PBSA simulations with the two top-ranked proposed receptors (TLR2, USP53) and independent receptors (IRF7, STAT1), and observed their stable performance. Therefore, the proposed drugs might play a vital role for the treatment against different variants of SARS-CoV-2 infections.
Highlights
The pandemic threat of COVID-19 has severely destroyed human life as well as the economy around the world
Though a number of vaccines including Pfizer, Moderna, Sputnik, AstraZeneca, Ad5-nCoV, EpiVacCorona, BBIBP-CorV, BBV152, CoronaVac, WIBP are available against SARS-CoV-2 and some are in p rogress[16,17], researchers are worried about their effectiveness due to unstable RNA sequence of coronaviruses
We identified the set of 109 differentially expressed genes (DEGs) as (AUR ∪ ADR) ∪ (BUR ∪ BDR) between COVID-19 infected and control samples from RNA-Seq dataset by using two popular statistical R-packages (DESeq[2] and edgeR) as introduced in the material and method section
Summary
The pandemic threat of COVID-19 has severely destroyed human life as well as the economy around the world. The repurposing of existing drugs for a particular disease could reduce the time and cost compared to de novo drug development By this time, several authors proposed host/SARS-CoV-2 transcriptome-guided several sets of candidate drugs by molecular docking with different sets of target proteins (receptors) for the treatment against SARS-CoV-2 infections[23–49]. Our main objectives are (1) computational identification of genomic biomarkers (drug targets) for SARS-CoV-2 infections highlighting their functions, pathways, regulatory factors and associated comorbidities (2) exploring candidate drugs for the treatment against different variants of SARSCoV-2 infections with comorbidities and (3) In-silico validation on the resistance of the proposed candidate drugs against the state-of-the-art alternatives top-ranked independent receptors associated with SARS-CoV-2 infections published by others.
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