Targeting the Coronavirus SARS-CoV-2: computational insights into the mechanism of action of the protease inhibitors Lopinavir, Ritonavir, and Nelfinavir. Giovanni Bolcato Maicol Bissaro Matteo Pavan Mattia Sturlese Stefano Moro 10.6084/m9.figshare.12011940.v1 https://springernature.figshare.com/articles/dataset/Targeting_the_Coronavirus_SARS-CoV-2_computational_insights_into_the_mechanism_of_action_of_the_protease_inhibitors_Lopinavir_Ritonavir_and_Nelfinavir_/12011940 <p>This dataset consists of three videos in<b> .mp4 </b>format. The videos were generated using the computational technique of Supervised Molecular Dynamics (SuMD) to provide molecular insight on the whole interaction pathway of lopinavir, ritonavir, and nelfinavir, three potential C30 Endopeptidase inhibitors, with the last one taken into consideration due to the promising in-vitro activity shown against the structurally related SARS-CoV protease.</p><p>These videos are supporting materials for the related publication.<br></p><p><br></p><p>Details of each video are as follows:</p><p>- <b>Video_1: Lopinavir binding pathway against SARS-CoV-2 main protease.</b><br></p><p>The video is composed of four synchronized and animated panels that summarized a putative molecular recognition mechanism of HIV protease inhibitor <b>Lopinavir </b>against SARS-CoV-2 main protease. In the first panel (upper-left), the SuMD binding trajectory is reported. The backbone of SARS-CoV-2 main protease is represented using ribbon style (pink colour) and the protein residues within 4 Å of <b>Lopinavir </b>(rendered by green carbon atoms) are dynamically shown. In the second panel (upper-right), the distance between the inhibitor center of mass (CM) and the protein catalytic binding site during the entire trajectory is reported. The time evolution is reported in a ns scale. In the third panel (lower-left), the MMGBSA energy profile describing the binding event is reported. In the fourth panel (lower-right) cumulative electrostatic interactions are reported for the 15 protease residues most contacted by <b>Lopinavir </b>during the whole binding simulation.</p><p>- <b>Video_2: Ritonavir binding pathway against SARS-CoV-2 main protease.</b><br></p><p>As above, but for the protease inhibitor <b>Ritonavir </b>against SARS-CoV-2 main protease. The protein residues within 4 Å of <b>Ritonavir </b>are rendered by orange carbon atoms.</p><p>- <b>Video_3: Nelfinavir binding pathway against SARS-CoV-2 main protease.</b><br></p><p>As above, but for the protease inhibitor <b>Nelfinavir </b>against SARS-CoV-2 main protease. The protein residues within 4 Å of <b>Nelfinavir </b>are rendered by cyan carbon atoms.</p><p><br></p><p><b>Software</b></p><p>All the SuMD trajectories have been carried out using AceMD engine and analyzed by an in-house tool written in tcl and python programming languages. MMGBSA protocol as implemented in AMBER 2014 was exploited to estimate protein-ligand interaction energy. NAMD engine was used for post-processing computation of electrostatic interactions, using AMBER ff14SB forcefield.<br></p><div><br></div> 2020-03-30 15:29:22 molecular modeling coronavirus COVID-2019 Supervised Molecular Dynamics SuMD lopinavir ritonavir C30 Endopeptidase SARS-CoV-2 COVID-19 2019-nCoV