Isoflavone compounds are potent inhibitors against mitochondrial aldehyde dehydrogenase (ALDH2) for the treatment of alcoholism and drug addiction, and an in-depth understanding of the underlying structural basis helps design new inhibitors for enhanced binding. Here, we investigated the binding poses and strengths of eight isoflavone analogues (including CVT-10216 and daidzin) with ALDH2 via computational methods of molecular docking, molecular dynamics (MD) simulation, molecular mechanics Poisson-Boltzmann surface area (MM-PBSA), steered MD, and umbrella sampling. Neither the Vina scoring of docked and MD-sampled complexes nor the nonbonded protein-inhibitor interaction energy from MD simulations is able to reproduce the relative binding strength of the inhibitors compared to experimental IC₅₀ values. Considering the solvation contribution, MM-PBSA and relatively expensive umbrella sampling yield good performance for the relative binding (free) energies. The isoflavone skeleton prefers to form π-π stacking, π-sulfur, and π-alkyl interactions with planar (Phe and Trp) or sulfur-containing (Cys and Met) residues. The enhanced inhibition of CVT-10216 originates from both end groups of the isoflavone skeleton offering strong van der Waals contacts and from the methylsulfonamide group at the 4' position by hydrogen bonding (HB) with neighboring receptor residues. These results indicate that the hydrophobic binding tunnel of ALDH2 is larger than the isoflavone skeleton in length and thus an extended hydrophobic core is likely a premise for potent inhibitors.

The behavior of biomolecules in crowded environments remains largely unknown due to the accuracy of simulation models and the limited experimental data for comparison. Here we chose a small crowder of tetraethylene glycol (PEG-4) to investigate the self-crowding of PEG-4 solutions and molecular crowding effects on the structure and diffusion of lysozyme at varied concentrations from dilute water to pure PEG-4 liquid. Two Amber-like force fields of Amber14SB and a99SB-disp were examined with TIP3P (fast diffusivity and low viscosity) and a99SB-disp (slow diffusivity and high viscosity) water models, respectively. Compared to the Amber14SB protein simulations, the a99SB-disp model yields more coordinated water and less PEG-4 molecules, less intramolecular hydrogen bonds (HBs), more protein–water HBs, and less protein–PEG HBs as well as stronger interactions and more hydrophilic and less hydrophobic contacts with solvent molecules. The a99SB-disp model offers comparable protein–solvent interactions in concentrated PEG-4 solutions to that in pure water. The PEG-4 crowding leads to a slow-down in the diffusivity of water, PEG-4, and protein, and the decline in the diffusion from atomistic simulations is close to or faster than the hard sphere model that neglects attractive interactions. Despite these differences, the overall structure of lysozyme appears to be maintained well at different PEG-4 concentrations for both force fields, except a slightly large deviation at 370 K at low concentrations with the a99SB-disp model. This is mainly attributed to the strong intramolecular interactions of the protein in the Amber14SB force field and to the large viscosity of the a99SB-disp water model. The results indicate that the protein force fields and the viscosity of crowder solutions affect the simulation of biomolecules under crowding conditions.

Hydration free energy (HFE) as the most important solvation parameter is often targeted in ion model development, even though the reported values differ by dozens of kcal mol⁻¹ mainly due to the experimentally undetermined HFE of the proton ΔG°(H⁺). The choice of ΔG°(H⁺) obviously affects the hydration of single ions and the relative HFE between the ions with different (magnitude or sign) charges, and the impacts of targeted HFEs on the ion solvation and ion–ion interactions are largely unrevealed. Here we designed point charge models of K⁺, Mg²⁺, Al³⁺, and Cl⁻ ions targeting a variety of HFE references and then investigated the HFE influences on the simulations of dilute and concentrated ion solutions and of the salt ion pairs in gas, liquid, and solid phases. Targeting one more property of ion–water oxygen distances (IOD) leaves the ion–water binding distance invariant, while the binding strength increases with the decreasing (more negative) HFE of ions as a result of a decrease in ΔG°(H⁺) for the cation and an increase in ΔG°(H⁺) for the anion. The increase in ΔG°(H⁺) leads to strengthened cation–anion interactions and thus to close ion–ion contacts, low osmotic pressures, and small activity derivatives in concentrated ion solutions as well as too stable ion pairs of the salts in different phases. The ion diffusivity and water exchange rates around the ions are simply not HFE dependent but rather more complex. Targeting both the aqueous IOD and salt crystal properties of KCl was also attempted and the comparison between different models indicates the complexity and challenge in obtaining a balanced performance between different phases using classical force fields. Our results also support that a real ΔG°(H⁺) value of −259.8 kcal mol⁻¹ recommended by Hünenberger and Reif guides ion models to reproduce ion–water and ion–ion interactions reasonably at relatively low salt concentrations. Simulations of a metalloprotein show that a relatively more positive ΔG°(H⁺) for Mg²⁺ model is better for a reasonable description of the metal binding network.