Predicting and repurposing of drug and drug-like compounds for inhibition of the COVID-19 and its cytokine storm by computational methods
Azhar Salari-Jazi, Karim Mahnam, Sayed Hossein Hejazi, Mohammad Sadegh Damavandi, Parisa Sadeghi, Mehrdad Zeinalian, Faezeh Tabesh, Seyedeh Mahnaz Mirbod, Hossein Khanahmad
Received date: 20th May 2020
The SARS-CoV-2 virus is a new, highly pathogen virus able to suppress cell innate immune response (Poly ADPR process and interferon release in the infected cell) by viral macrodomain and creating fatal pneumonia. Cytokine storm phenomenon, capable of creating the consequent of SARS-CoV-2 through increasing the performance of human TRPM2, is a dangerous condition for human body organs such as kidney, heart, and liver. In this study, drug and drug-like databases were used to inhibit the viral macrodomain and human TRPM2 that can initiate the viral cell cycle infection and human cytokine storm, respectively. Ligand-based drug design, pharmacophore modeling, docking, and molecular dynamic simulation were further performed. Among up to a billion compounds as the library for infiniSee, 20 compounds were screened by the infiniSee program. Via pharmacophore modeling, seven compounds were then selected, among which five were removed because of high similarity to the ADPR and the possibility of toxicity for human RNA and DNA polymerase. One compound, losartan, was selected for docking and molecular dynamic simulation. Losartan earned a proper dock score and binding affinity for generating complexes with TRPM2 and macrodomain. Molecular dynamic simulation showed that losartan had adequate binding free energy for human TRPM2 and viral macrodomain. The inhibitory effect of losartan on these proteins indicated its ability to interfere at several points (PARP, PARG-macrodomain, and TRPM2) and decrease oxidative stress, apoptosis, cytokine storm in COVID-19.
This is an abstract of a preprint hosted on a preprint server, which is currently undergoing peer review at Scientific Reports. The findings have yet to be thoroughly evaluated, nor has a decision on ultimate publication been made. Therefore, the results reported should not be considered conclusive, and these findings should not be used to inform clinical practice, or public health policy, or be promoted as verified information.