Free Energy Calculations Based on Coupling Proximal Distribution Functions and Thermodynamic Cycles

Influence of the pKa value on the antioxidant activity of licorice flavonoids under solvent-mediated effects

Licorice flavonoids (LCFs) have been widely used in food care and medical treatment due to their significant antioxidant activities. However, the molecular mechanism of their antioxidant activity remains unclear. Therefore, network pharmacology, ADMET, density functional theory (DFT), molecular docking, and molecular dynamics (MD) simulation were employed to explore the molecular mechanism of the antioxidant effects of LCF. The network pharmacology and ADMET studies showed that the active molecules of kumatakenin (pK_a  = 6.18), licoflavonol (pK_a  = 6.86), and topazolin (pK_a  = 6.21) in LCF are key antioxidant components and have good biosafety. Molecular docking and MD simulation studies demonstrated that active molecules interacted with amino acid residues in target proteins to form stable protein-ligand complexes and exert their antioxidant effects. DFT studies showed that the antioxidant activity of LCF could be significantly modulated under the solvent-mediated effect. In addition, based on the derivation of the Henderson-Hasselbalch and van't Hoff formulas, the functional relationships between the reaction-free energy (ΔG) of LCF and the pH and pK_a values were established. The results showed that active molecules with larger pK_a values will be more conducive to the improvement of their antioxidant activity under solvent-mediated effects. In conclusion, this study found that increasing the pK_a value of LCF would be an effective strategy to improve their antioxidant activity under the effect of solvent mediation. The pK_a value of an LCF will be a direct standard to evaluate its solvent-mediated antioxidant activity. This study will provide theoretical guidance for the development of natural antioxidants.

Contributions of higher-order proximal distribution functions to solvent structure around proteins

The proximal distribution function (pDF) quantifies the probability of finding a solvent molecule in the vicinity of solutes. The approach constitutes a hierarchically organized theory for constructing approximate solvation structures around solutes. Given the assumption of universality of atom cluster-specific solvation, reconstruction of the solvent distribution around arbitrary molecules provides a computationally convenient route to solvation thermodynamics. Previously, such solvent reconstructions usually considered the contribution of the nearest-neighbor distribution only. We extend the pDF reconstruction algorithm to terms including next-nearest-neighbor contribution. As a test, small molecules (alanine and butane) are examined. The analysis is then extended to include the protein myoglobin in the P6 crystal unit cell. Molecular dynamics simulations are performed, and solvent density distributions around the solute molecules are compared with the results from different pDF reconstruction models. It is shown that the next-nearest-neighbor modification significantly improves the reconstruction of the solvent number density distribution in concave regions and between solute molecules. The probability densities are then used to calculate the solute-solvent non-bonded interaction energies including van der Waals and electrostatic, which are found to be in good agreement with the simulated values.