Molecular networking-based drug repurposing strategies for SARS-CoV-2 infection by targeting alpha-1-antitrypsin (SERPINA1)

Abstract Background For a deeper comprehension of the condition and the development of more potent therapies, it is essential to understand COVID-19 pathogenesis. Transmembrane serine protease 2 (TMPRSS2) and disintegrin and metalloproteinase 17 (ADAM17) are two of the most significant proteases in the pathogenesis of COVID-19. An intrinsic tissue protector with antiviral and anti-inflammatory effects is called alpha-1-antitrypsin (A1AT), and it inhibits the protein TMPRSS2, which is crucial for SARS-CoV-2-S protein priming and viral infection. It also prevents the activity of pro-inflammatory chemicals like neutrophil elastase, TNF-, and IL-8.Objective According to current findings, repurposing available medications will result in more effective functioning than using newly designed medications. Based on this, we used FDA-approved drugs and did a computational study to find out what role A1AT plays in SARS-CoV-2 infections and how it stops Covid-19 from spreading.Method This computational study comprises the screening of FDA approved drugs by using molecular networking studies via cytoscape version 3.9.1 to identify any drugs binding interactions with SERPINA1, a gene that provides instructions for making a protein called A1AT, which is a type of serine protease inhibitor, followed by the generation of a pharmacophore model, virtual screening, and docking studies.Result The 22 compounds that were selected from this molecular-networking model were subjected to pharmacophore modelling followed by virtual screening. Through this screening, we have selected 22 molecules based on the Lipinski rule and low RMSD value, i.e., below 0.069235 Ao. From the ZINC database, the top six molecules discovered were found to have a higher affinity for A1AT when compared to the co-crystal ligand (-12.8236). The highest scores obtained by alpha-1-antitrypsin (PDB ID: 7NPK) are − 22.0254 and − 21.676 for ZINC00896543 and ZINC05316843, respectively.Conclusion Consequently, the molecules found by using different software programmes may be employed to control and treat COVID 19. By increasing the levels of A1AT, we may thus infer that these molecules have excellent action in the reversal of COVID-19.