Abstract
Accumulated evidence suggests that binding kinetic properties—especially dissociation rate constant or drug-target residence time—are crucial factors affecting drug potency. However, quantitative prediction of kinetic properties has always been a challenging task in drug discovery. In this study, the VolSurf method was successfully applied to quantitatively predict the koff values of the small ligands of heat shock protein 90α (HSP90α), adenosine receptor (AR) and p38 mitogen-activated protein kinase (p38 MAPK). The results showed that few VolSurf descriptors can efficiently capture the key ligand surface properties related to dissociation rate; the resulting models demonstrated to be extremely simple, robust and predictive in comparison with available prediction methods. Therefore, it can be concluded that the VolSurf-based prediction method can be widely applied in the ligand-receptor binding kinetics and de novo drug design researches.
Highlights
Thermodynamic properties (e.g., IC50, EC50 and equilibrium dissociation constant) have been regarded as key indicators of drug potency, mounting evidence suggests that thermodynamic properties may not be the only measures of drug potency
The results showed that the kinetic properties of 37 HIV-1 protease inhibitors are closely related to the nine VolSurf descriptors derived from water (OH2) and hydrophobic (DRY) probes
In a recent research, we found that it can be used for predicting the pharmacodynamics properties such as dissociation rate constants, which are closely related to the molecular surface properties
Summary
Thermodynamic properties (e.g., IC50, EC50 and equilibrium dissociation constant (kd)) have been regarded as key indicators of drug potency, mounting evidence suggests that thermodynamic properties may not be the only measures of drug potency. It has become increasingly apparent that kinetic properties—especially dissociation rate constant (koff) or drug-target residence time (τ)—are more important for drug potency and are gradually being used in real-world lead optimization and drug design [1,2,3,4,5]. With the development of computational chemistry, molecular simulation techniques have been successfully applied to predict the binding kinetic properties of small molecules. One of the most common methods is molecular dynamics. By using τ-random acceleration molecular dynamics (τRAMD), Kokh et al [10] proposed a protocol to predict the residence time of 70 inhibitors of human heat shock protein 90α (HSP90α). A strong correlation (R2 = 0.66) was observed between the predicted and measured residence time in 59 samples after removing 11 samples. The results showed that the predicted R2 of the 80 inhibitors was 0.75 with MAPE of 0.39 [11]
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