The worldwide health emergency of the SARS-CoV-2 pandemic and the absence of a specific treatment for this new coronavirus have led to the use of computational strategies (drug repositioning) to search for treatments. The aim of this work is to identify FDA (Food and Drug Administration)-approved drugs with the potential for binding to the spike structural glycoprotein at the hinge site, receptor binding motif (RBM), and fusion peptide (FP) using molecular docking simulations. Drugs that bind to amino acids are crucial for conformational changes, receptor recognition, and fusion of the viral membrane with the cell membrane. The results revealed some drugs that bind to hinge site amino acids (varenicline, or steroids such as betamethasone while other drugs bind to crucial amino acids in the RBM (naldemedine, atovaquone, cefotetan) or FP (azilsartan, maraviroc, and difluprednate); saquinavir binds both the RBM and the FP. Therefore, these drugs could inhibit spike glycoprotein and prevent viral entry as possible anti-COVID-19 drugs. Several drugs are in clinical studies; by focusing on other pharmacological agents (candesartan, atovaquone, losartan, maviroc and ritonavir) in this work we propose an additional target: the spike glycoprotein. These results can impact the proposed use of treatments that inhibit the first steps of the virus replication cycle.

After the outbreak of SARS-CoV-2 by the end of 2019, the vaccine development strategies became a worldwide priority. Furthermore, the appearances of novel SARS-CoV-2 variants challenge researchers to develop new pharmacological or preventive strategies. However, vaccines still represent an efficient way to control the SARS-CoV-2 pandemic worldwide. This review describes the importance of bioinformatic and immunoinformatic tools (in silico) for guide vaccine design. In silico strategies permit the identification of epitopes (immunogenic peptides) which could be used as potential vaccines, as well as nonacarriers such as: vector viral based vaccines, RNA-based vaccines and dendrimers through immunoinformatics. Currently, nucleic acid and protein sequential as well structural analyses through bioinformatic tools allow us to get immunogenic epitopes which can induce immune response alone or in complex with nanocarriers. One of the advantages of in silico techniques is that they facilitate the identification of epitopes, while accelerating the process and helping to economize some stages of the development of safe vaccines.

Peptic ulcer disease, the most common gastrointestinal disorder, is currently treated with several types of drugs, but all have severe side effects. The aim of the present study was to evaluate the gastroprotective activity of juanislamin, isolated from Calea urticifolia, in a rat model of ethanol-induced gastric lesions. Thirty minutes after orally administering a given dose of juanislamin (from 1 to 30 mg/kg) or carbenoxolone (the reference drug, at 1–100 mg/kg) to rats, 1 mL of ethanol was applied, and the animals were sacrificed 2 h later. The stomachs were removed and opened to measure the total area of lesions in each. To examine the possible participation of prostaglandins, nitric oxide and/or sulfhydryl groups in the mechanism of action of juanislamin, the rats received indomethacin, NG-Nitro-l-arginine methyl ester hydrochloride (l-NAME) or N-ethylmaleimide pretreatment, respectively, before being given juanislamin and undergoing the rest of the methodology. Juanislamin inhibited gastric lesions produced by ethanol in a non-dose-dependent manner, showing the maximum gastroprotective effect (100%) at 10 mg/kg. The activity of juanislamin was not modified by pretreatment with indomethacin, l-NAME or N-ethylmaleimide. In conclusion, juanislamin protected the gastric mucosa from ethanol-induced damage, and its mechanism of action apparently does not involve prostaglandins, nitric oxide or sulfhydryl groups.