ZINC000085536956 for COVID-19
ZINC000085536956 has been reported as potentially beneficial for treatment of COVID-19. We have not reviewed these studies. See all other treatments.
Drug Repurposing Targeting COVID-19 3CL Protease using Molecular Docking and Machine Learning Regression Approach, arXiv, doi:10.48550/arXiv.2305.18088 ,
The COVID-19 pandemic has created a global health crisis, driving the need for the rapid identification of potential therapeutics. In this study, we used the Zinc database to screen the world-approved including FDA-approved 5903 drugs for repurposing as potential COVID-19 treatments targeting the main protease 3CL of SARS-CoV-2. We performed molecular docking using Autodock-Vina to check the efficacy of drug molecules. To enhance the efficiency of drug repurposing approach, we modeled the binding affinities using several machine learning regression approaches for QSAR modeling such as decision tree, extra trees, MLP, KNN, XGBoost, and gradient boosting. The computational results demonstrated that Decision Tree Regression (DTR) model has improved statistical measures of R2 and RMSE. These simulated results helped to identify drugs with high binding affinity and favorable binding energies. From the statistical analysis, we shortlisted 13 promising drugs with their respective Zinc IDs (ZINC000003873365, ZINC000085432544, ZINC000203757351, ZINC000085536956, ZINC000085536990, ZINC000008214470, ZINC000261494640, ZINC000169344691, ZINC000094303244, ZINC000095618608, ZINC000095618689, ZINC000095618743, and ZINC000253684767) within the range of -15.1 kcal/mol to -12.7 kcal/mol. Further, we analyzed the physiochemical properties of these selected drugs with respect to their best binding interaction to specific target protease. Our study has provided an efficient framework for drug repurposing against COVID-19. This highlights the potential of combining molecular docking with machine learning regression approaches to accelerate the identification of potential therapeutic candidates.
Please send us corrections, updates, or comments. c19early involves the extraction of 100,000+ datapoints from thousands of papers. Community updates help ensure high accuracy. Vaccines and treatments are complementary. All practical, effective, and safe means should be used based on risk/benefit analysis. No treatment, vaccine, or intervention is 100% available and effective for all current and future variants. We do not provide medical advice. Before taking any medication, consult a qualified physician who can provide personalized advice and details of risks and benefits based on your medical history and situation. FLCCC and WCH provide treatment protocols.
Thanks for your feedback! Please search before submitting papers and note that studies are listed under the date they were first available, which may be the date of an earlier preprint.