Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) emergence has resulted in a global health crisis. As a consequence, discovering an effective therapy that saves lives and slows the spread of the pandemic is a global concern currently. In silico drug repurposing is highly regarded as a precise computational method for obtaining fast and reliable results. Transmembrane serine-type 2 (TMPRSS2) is a SARS CoV-2 enzyme that is essential for viral fusion with the host cell. Inhibition of TMPRSS2 may block or lessen the severity of SARS-CoV-2 infection. In this study, we aimed to perform an in silico drug repurposing to identify drugs that can effectively inhibit SARS-CoV-2 TMPRSS2. As there is no 3D structure of TMPRSS2 available, homology modeling was performed to build the 3D structure of human TMPRSS2. 3848 world-approved drugs were screened against the target. Based on docking scores and visual outcomes, the best-fit drugs were chosen. Molecular dynamics (MD) and density functional theory (DFT) studies were also conducted. Five potential drugs (Amikacin, isepamicin, butikacin, lividomycin, paromomycin) exhibited promising binding affinities. In conclusion, these findings empower purposing these agents.

No abstract

The global expansion of COVID-19 and the mutations of severe acute respiratory syndrome coronavirus necessitate quick development of treatment and vaccination. Because the androgen-responsive serine protease TMPRSS2 is involved in cleaving the SARS-CoV-2 spike protein allowing the virus to enter the cell, therefore, direct TMPRSS2 inhibition will inhibit virus activation and disease progression which make it an important target for drug discovery. In this study, a homology model of TMPRSS2 protein was initially developed. Then, we used the fragment-based drug design (FBDD) technique to develop effective TMPRSS2 inhibitors. Over a half-million fragments from the enamine database, were screened for their binding ability to target protein, and then best-scoring fragments were linked to building new molecules with a good binding affinity. XP docking and MM-GBSA studies revealed 10 new-formed molecules with docking score ≤ −14.982 kcal/mol compared to ambroxol (control) with a docking score of −6.464 kcal/mol. Finally, molecular dynamics (MD) and density functional theory (DFT) were calculated for the top 3 molecules.

Schistosomiasis is a neglected tropical disease with a significant socioeconomic impact. It is caused by several species of blood trematodes from the genus Schistosoma, with S. mansoni being the most prevalent. Praziquantel (PZQ) is the only drug available for treatment, but it is vulnerable to drug resistance and ineffective in the juvenile stage. Therefore, identifying new treatments is crucial. SmHDAC8 is a promising therapeutic target, and a new allosteric site was discovered, providing the opportunity for the identification of a new class of inhibitors. In this study, molecular docking was used to screen 13,257 phytochemicals from 80 Saudi medicinal plants for inhibitory activity on the SmHDAC8 allosteric site. Nine compounds with better docking scores than the reference were identified, and four of them (LTS0233470, LTS0020703, LTS0033093, and LTS0028823) exhibited promising results in ADMET analysis and molecular dynamics simulation. These compounds should be further explored experimentally as potential allosteric inhibitors of SmHDAC8.

Background: Schistosomiasis is the world's second most devastating disease after malaria and the leading cause of disease and mortality for more than 200 million people in developing countries. Cysteine proteases, in particular SmCB1, are the most well-researched biological targets for this disorder. Objective: To apply computational techniques to design new antischistosomal agents against SmCB1 protein with favorable pharmacokinetic properties. Methods: The smCB1 receptor-based pharmacophore model was created and used to screen 567,000 fragments from the Enamine library. The best scoring fragments have been linked to build novel compounds that were subjected to molecular docking, MM-GBSA free energy estimation, ADME prediction, and molecular dynamics. Results: A seven-point pharmacophore hypothesis ADDDRRR was created. The developed hypothesis was used to screen 1.3 M fragment conformations. Among them, 23,732 fragments matched the hypothesis and screened against the protein. The top 50 fragments were used to design new 7745 compounds using the Breed ligand panel which were subjected to docking and MMGBSA binding energy. This led to the identification of 10 compounds with better docking scores (−8.033-−7.483 kcal/mol) and lower-bound free energies (−58.49 -−40.02 kcal/mol) compared to the reference bound ligand. Most of the designed compounds demonstrated good drug-like properties. Concerning Molecular dynamics (MD) simulation results, a low root mean square deviation (RMSD) range (0.25-1.2 Å) was found for the top 3 complexes which indicated their stability. Conclusion:We identified compounds that could be potential candidates in the search for novel Schistosoma mansoni inhibitors by targeting SmCB1 utilizing various computational tools. Three newly designed compounds namely breed 1, 2, and 3 showed promising affinity to the target as well as favorable drug-like properties which might be considered potential anti-schistosomal agents.