Computationally driven discovery of SARS-CoV-2 M<sup>pro</sup>inhibitors: from design to experimental validation
Léa El Khoury, Zhifeng Jing, Alberto Cuzzolin, Alessandro Deplano, Daniele Loco, Boris Sattarov, Florent Hédin, Sebastian Wendeborn, Chris Ho, Dina El Ahdab, Théo Jaffrelot Inizan, Mattia Sturlese, Alice Sosic, Martina Volpiana, Angela Lugato, Marco Barone, Barbara Gatto, Maria Ludovica Macchia, Massimo Bellanda, Roberto Battistutta, Cristiano Salata, Ivan S. Kondratov, Rustam T. Iminov, Andrii Khairulin, Yaroslav Mykhalonok, Anton Pochepko, Volodymyr Chashka-Ratushnyi, Iaroslava Kos, Stefano Moro, Matthieu Montès, Pengyu Ren, Jay W. Ponder, Louis Lagardère, Jean‐Philip Piquemal, Davide Sabbadin
Abstract
The dominant binding mode of the QUB-00006-Int-07 main protease inhibitor during absolute binding free energy simulations.
Topics & Concepts
In silicoMolecular dynamicsDrug discoveryChemistryLigand efficiencyForce field (fiction)Ligand (biochemistry)Combinatorial chemistryComputational chemistryComputer scienceBiochemistryArtificial intelligenceGeneReceptorComputational Drug Discovery MethodsProtein Structure and DynamicsMachine Learning in Materials Science