Electron Density Analysis of SARS-CoV-2 RNA-Dependent RNA Polymerase Complexes

Abstract

The work is devoted to the study of the complementarity of the electronic structures of the ligands and SARS-CoV-2 RNA-dependent RNA polymerase. The research methodology was based on determining of 3D maps of electron densities of complexes using an original quantum free-orbital AlteQ approach. We observed a positive relationship between the parameters of the electronic structure of the enzyme and ligands. A complementarity factor of the enzyme-ligand complexes has been proposed. The console applications of the AlteQ complementarity assessment for Windows and Linux (alteq_map_enzyme_ligand_4_win.exe and alteq_map_enzyme_ligand_4_linux) are available for free at the ChemoSophia webpage.

A Computational Pipeline to Identify and Characterize Binding Sites and Interacting Chemotypes in SARS-CoV-2

“…Cases in which there are differences between PDB structural templates, for example, 7CTT and 7AAP (lower left diagram in Figure 5), highlight the natural biological variation in protein conformations that introduces changes to the binding pocket. 33 Since the consensus pockets are defined by a comprehensive search of over multiple protein conformations and multiple ligands, they cover the natural variability and still report a majority of residues in contact with antiviral drugs, plus additional residues of potential importance. The fact that our method can discern significant binding pockets without some of the original data is another sign of its robustness.…”

“…The consensus pockets cover over 50% of the contact residues for all ten templates and often a much higher percentage, up to 100% for four templates. Cases in which there are differences between PDB structural templates, for example, 7CTT and 7AAP (lower left diagram in Figure ), highlight the natural biological variation in protein conformations that introduces changes to the binding pocket . Since the consensus pockets are defined by a comprehensive search of over multiple protein conformations and multiple ligands, they cover the natural variability and still report a majority of residues in contact with antiviral drugs, plus additional residues of potential importance.…”

A Computational Pipeline to Identify and Characterize Binding Sites and Interacting Chemotypes in SARS-CoV-2

“…6), highlight the natural biological variation in protein conformations that introduces changes to the binding pocket. 35 Since the consensus pockets are defined by a comprehensive search of over multiple protein conformations and multiple ligands, the consensus pockets cover the natural variability and still report a majority of residues in contact with antiviral drugs, plus additional residues of potential importance. The fact that our method can discern significant binding pockets without some of the original data is another indication that our method is performing well and could be trusted to identify significant conserved pockets in other new viruses.…”

Chrysin Inhibits Indonesian Serotype Foot-and-Mouth-Disease Virus Replication: Insights from DFT, Molecular Docking and Dynamics Analyses

“…The objective of molecu-lar docking is to predict the binding affinity between a ligand and a protein. As it influences the distribution of electrons in the ligand and the protein, the electronegativity of a ligand may influence its binding affinity to a protein (Palko et al 2021). Employing quantum mechanical method to predict the electronegativity, as DFT does, would be useful in improving binding affinity estimations (Ryde & Söderhjelm 2016).…”