مشخصات پژوهش

عنوان	Identifying SARS-CoV-2 main protease inhibitors by applying the computer screening of a large database of molecules
نوع پژوهش	مقاله چاپ‌شده در مجلات علمی
کلیدواژه‌ها	COVID-19; SARS-CoV-2; virtual screening; similarity search; molecular docking; molecular dynamics simulations
چکیده	The outbreak of coronavirus disease 2019 (COVID-19) at the end of 2019 affected global health. Its infection agent was called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Wearing a mask, maintaining social distance, and vaccination are effective ways to prevent infection of SARS-CoV-2, but none of them help infected people. Targeting the enzymes of SARS-CoV-2 is an effective way to stop the replication of the virus in infected people and treat COVID-19 patients. SARS-CoV-2 main protease is a therapeutic target which the inhibition of its enzymatic activity prevents from the replication of SARS-CoV-2. A large database of molecules has been searched to identify new inhibitors for SARS-CoV-2 main protease enzyme. At the first step, ligand screening based on similarity search was used to select similar compounds to known SARS-CoV-2 main protease inhibitors. Then molecules with better predicted pharmacokinetic properties were selected. Structurebased virtual screening based on the application of molecular docking and molecular dynamics simulation methods was used to select more effective inhibitors among selected molecules in previous step. Finally two compounds were considered as SARS-CoV-2 main protease inhibitors.
پژوهشگران	دانیال مرادی (نفر ششم به بعد)، رویا احمدی (گروه شیمی) (نفر پنجم)، مهدی ایرانی (نفر چهارم)، فاطمه محمودی (نفر سوم)، رئوف قوامی زروان (نفر دوم)، بختیار سپهری (نفر اول)