Understanding Aldose Reductase-Inhibitors interactions with free energy simulation

Aldose Reductase (AR) reduces a variety of substrates, such as aldehydes, aldoses and corticosteroids. It is the first and rate-limiting enzyme of the polyol pathway and is an important target enzyme for diabetes-associated complications, including retinopathy, neuropathy, and nephropathy. Inhibitors targeting this enzyme are structurally different and some of them have side effects. In existing publications, computational techniques are applied to investigate the binding affinities of existing inhibitors and predicting the affinities of newly designed ligands. However, these calculations only employ coarse and approximated methods such as docking and MM/PBSA. Brute force simulations are employed to study the dynamics of the system but no converged statistics is obtained. As a result, these computations provide results not consistent with experimental values and large discrepancies exist. In the current work, we employ the enhanced sampling technique of alchemical free energy simulation to calculate the binding affinities of several ligands targeting AR. The statistical error is defined with care and the correlation in the time-series data is fully considered. The statistically optimal estimators are used to extract the free energy estimates and the predicted results are in agreement with the experimental values. Less computationally demanding end-point free energy methods are also performed to compare their efficiency with the alchemical methods. As is expected, the end-point methods are of less accuracy and reliability compared with the alchemical free energy methods. The decomposition of the free energy difference in each alchemical transformation into the enthalpic and entropic components gives further insights on the thermodynamics. The enthalpy-entropy compensation is observed in this case. As the structural data obtained from experiments are only snapshots and more details are needed to understand the dynamics of the protein-ligand system, the conformational ensemble is analyzed. We identify important residues involved in the protein-ligand binding case and short-lived interactions formed due to fluctuations in the conformational ensemble. The current work shed light on the atomic detailed understanding of the dynamics of AR-inhibitors interactions.