Hydration patterns of rings in drugs and relationship to lipophilicity: A DFT study

Quantum chemical studies on the binding domain of SARS-CoV-2 S-protein: human ACE2 interface complex

A two-layer ONIOM(B3LYP/6-31G*:PM7) method is used to model the binding of several drug/drug-like molecules (L) at the SARS-CoV-2 S-protein: human ACE2 protein interface cavity. The selected molecules include a set of thirty-five ligands from the study of Smith and Smith which showed a high docking score in the range of -7.0 to -7.7 kcal/mol and another set of seven repurposing drugs, viz. favipiravir, remdesivir, EIDD, galidesivir, triazavirin, ruxolitinib, and baricitinib. The ONIOM model of the cavity (M) showed a highly polarized electron distribution along its top-to-bottom direction while Ls with lengths in the range 1.0 - 1.5 nm fitted well inside the cavity in a head-to-tail fashion to yield ML complexes. The ligands showed a large variation in the ONIOM-level binding energy (Eb), in the range -2.7 to -85.4 kcal/mol. The Eb of ML complexes better than -40.0 kcal/mol is observed for myricetin, fidarestat, protirelin, m-digallic acid, glucogallin, benserazide hydrochlorideseradie, remdesivir, tazobactum, sapropterin, nitrofurantoin, quinonoid, pyruvic acid calcium isoniazid, and aspartame, and among them the highest Eb -85.4 kcal/mol is observed for myricetin. A hydroxy substitution is suggested for the phenyl ring of aspartame to improve its binding behavior at the cavity, and the resulting ligand 43 showed the best Eb -84.5 kcal/mol. The ONIOM-level study is found to be effective for the interpretation of the noncovalent interactions resulting from residues such as arginine, histidine, tyrosine, lysine, carboxylate, and amide moieties in the active site and suggests rational design strategies for COVID-19 drug development.Communicated by Ramaswamy H. Sarma.

A density fitting scheme for the fast evaluation of molecular electrostatic potential

Molecular electrostatic potential (MEP) is a significant and crucial physical quantity that can be applied to a large number of scenarios, such as the prediction of nucleophilic or electrophilic attacks, fitting atomic charges, σ-hole, and so forth. The computational cost for the MEP has an O(N² ) scaling with the increase of atoms, which is intractable and laborious for macromolecules. Herein, a density fitting molecular electrostatic potential (DF-MEP) is used to reduce the computational costs for the macromolecular MEP. It is found that the accuracy of DF-MEP is almost identical to the conventional molecular electrostatic potential (Conv-MEP), while the computational costs can be reduced to an O(N) scaling, for example, the computational time of 699,200 grids for the Trp-cage molecule (304 atoms) only takes 16.6 s at the B3LYP-D3(BJ)/def2-SVP level of theory with 16 CPU cores compared with 3060.2 s for the Conv-MEP method.