Searching and designing potential inhibitors for SARS-CoV-2 Mpro from natural sources using atomistic and deep-learning calculations
Nguyễn Minh Tâm, Duc-Hung Pham, Đinh Minh Hiệp, Phuong‐Thao Tran, Dương Tuấn Quang, Sơn Tùng Ngô
Abstract
atomistic simulations. The compound tomatine, thevetine, and tribuloside could bind to SARS-CoV-2 Mpro with nanomolar/high-nanomolar affinities. Secondly, the deep-learning (DL) calculations were performed to chemically alter the top-lead natural compounds to improve ligand-binding affinity. The obtained results were then validated by free energy calculations using atomistic simulations. The outcome of the research will probably boost COVID-19 therapy.
Topics & Concepts
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Coronavirus disease 2019 (COVID-19)Natural (archaeology)2019-20 coronavirus outbreakComputer scienceChemistryComputational biologyVirologyBiologyMedicinePathologyDiseasePaleontologyOutbreakInfectious disease (medical specialty)Machine Learning in Materials ScienceComputational Drug Discovery MethodsProtein Structure and Dynamics