Assessment of an Electrostatic Energy-Based Charge Model for Modeling the Electrostatic Interactions in Water Solvent.

The protein force field based on the restrained electrostatic potential (RESP) charges has limitations in accurately describing hydrogen bonding interactions in proteins. To address this issue, we propose an alternative approach called the electrostatic energy-based charges (EEC) model, which shows improved performance in describing electrostatic interactions (EIs) of hydrogen bonds in proteins. In this study, we further investigate the performance of the EEC model in modeling EIs in water solvent. Our findings demonstrate that the fixed EEC model can effectively reproduce the quantum mechanics/molecular mechanics (QM/MM)-calculated EIs between a water molecule and various water solvent environments. However, to achieve the same level of computational accuracy, the electrostatic potential (ESP) charge model needs to fluctuate according to the electrostatic environment. Our analysis indicates that the requirement for charge adjustments depends on the specific mathematical and physical representation of EIs as a function of the environment for deriving charges. By comparing with widely used empirical water models calibrated to reproduce experimental properties, we confirm that the performance of the EEC model in reproducing QM/MM EIs is similar to that of general purpose TIP4P-like water models such as TIP4P-Ew and TIP4P/2005. When comparing the computed 10,000 distinct EI values within the range of -40 to 0 kcal/mol with the QM/MM results calculated at the MP2/aug-cc-pVQZ/TIP3P level, we noticed that the mean unsigned error (MUE) for the EEC model is merely 0.487 kcal/mol, which is remarkably similar to the MUE values of the TIP4P-Ew (0.63 kcal/mol) and TIP4P/2005 (0.579 kcal/mol) models. However, both the RESP method and the TIP3P model exhibit a tendency to overestimate the EIs, as evidenced by their higher MUE values of 1.761 and 1.293 kcal/mol, respectively. EEC-based molecular dynamics simulations have demonstrated that, when combined with appropriate van der Waals parameters, the EEC model can closely reproduce oxygen-oxygen radial distribution function and density of water, showing a remarkable similarity to the well-established TIP4P-like empirical water models. Our results demonstrate that the EEC model has the potential to build force fields with comparable accuracy to more sophisticated empirical TIP4P-like water models.

Molecular Mechanism of the Non-Covalent Orally Targeted SARS-CoV-2 Mpro Inhibitor S-217622 and Computational Assessment of Its Effectiveness against Mainstream Variants.

Convenient and efficient therapeutic agents are urgently needed to block the continued spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, the mechanism for the novel orally targeted SARS-CoV-2 main protease (Mpro) inhibitor S-217622 is revealed through a molecular dynamics simulation. The difference in the movement modes of the S-217622-Mpro complex and apo-Mpro suggested S-217622 could inhibit the motility intensity of Mpro, thus maintaining their stable binding. Subsequent energy calculations showed that the P2 pharmacophore possessed the highest energy contribution among the three pharmacophores of S-217622. Additionally, hot-spot residues H41, M165, C145, E166, and H163 have strong interactions with S-217622. To further investigate the resistance of S-217622 to six mainstream variants, the binding modes of S-217622 with these variants were elucidated. The subtle differences in energy compared to that of the wild type implied that the binding patterns of these systems were similar, and S-217622 still inhibited these variants. We hope this work will provide theoretical insights for optimizing novel targeted Mpro drugs.