Oxytetracycline for COVID-19

AbstractTo attain promising pharmacotherapies, researchers have applied drug repurposing (DR) techniques to discover the candidate medicines to combat the coronavirus disease 2019 (COVID-19) outbreak. Although many DR approaches have been introduced for treating different diseases, only structure-based DR (SBDR) methods can be employed as the first therapeutic option against the COVID-19 pandemic because they rely on the rudimentary information about the diseases such as the sequence of the severe acute respiratory syndrome coronavirus 2 genome. Hence, to try out new treatments for the disease, the first attempts have been made based on the SBDR methods which seem to be among the proper choices for discovering the potential medications against the emerging and re-emerging infectious diseases. Given the importance of SBDR approaches, in the present review, well-known SBDR methods are summarized, and their merits are investigated. Then, the databases and software applications, utilized for repurposing the drugs against COVID-19, are introduced. Besides, the identified drugs are categorized based on their targets. Finally, a comparison is made between the SBDR approaches and other DR methods, and some possible future directions are proposed.

The present coronavirus disease 2019 (COVID-19) pandemic scenario has posed a difficulty for cancer treatment. Even under ideal conditions, malignancies like small cell lung cancer (SCLC) are challenging to treat because of their fast development and early metastases. The treatment of these patients must not be jeopardized, and they must be protected as much as possible from the continuous spread of the COVID-19 infection. Initially identified in December 2019 in Wuhan, China, the contagious coronavirus illness 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Finding inhibitors against the druggable targets of SARS-CoV-2 has been a significant focus of research efforts across the globe. The primary motivation for using molecular modeling tools against SARS-CoV-2 was to identify candidates for use as therapeutic targets from a pharmacological database. In the published study, scientists used a combination of medication repurposing and virtual drug screening methodologies to target many structures of SARS-CoV-2. This virus plays an essential part in the maturation and replication of other viruses. In addition, the total binding free energy and molecular dynamics (MD) modeling findings showed that the dynamics of various medications and substances were stable; some of them have been tested experimentally against SARS-CoV-2. Different virtual screening (VS) methods have been discussed as potential means by which the evaluated medications that show strong binding to the active site might be repurposed for use against SARS-CoV-2.

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.