A 3D linear solvation energy model to quantify the affinity of flavonoid derivatives toward P-glycoprotein

Abstract

P-glycoprotein (Pgp/ABCB1) both accounts for multidrug resistance (MDR) in chemotherapy and contributes to reduce oral bioavailability and brain distribution of drugs. Flavonoids, reported as potent Pgp inhibitors, are able to bind to the cytosolic ATP-binding site and a vicinal hydrophobic pocket. In order to explore the interaction forces governing the affinity of flavonoids towards Pgp, the 3D quantitative structure-activity relationship (QSAR) approach was used to analyze a set of flavonoid derivatives. The variation of affinity towards Pgp was investigated by VolSurf descriptors of Molecular Interaction Fields (MIFs) related to hydrophobic interaction forces, polarizability, and hydrogen-bonding capacity. The 3D linear solvation energy VolSurf model developed here identifies shape parameters and hydrophobicity as the major physicochemical parameters responsible for the affinity of flavonoid derivatives towards Pgp and hydrogen-bonding capacities as minor modulators of this activity. Furthermore, this predictive model (q(2) of 0.71) was also validated by use of an external set of 10 flavones.

Simple graph-theoretical model for flavonoid binding to P-glycoprotein / Jednostavan graf-teorijski model vezivanja flavonoida za P-glikoprotein / Jednostavan graf-teorijski model vezivanja flavonoida za P-glikoprotein

“…The search for effective and safe P-gp inhibitors is in progress, and flavonoids seem very promising as MDR modulators. Investigations of flavonoid binding to P-glycoprotein using pharmacophore modelling (DISCOtech, CoMFA, CoIMFA, MIF) (16)(17)(18) have yielded a fair agreement with experimental findings and showed the dominance of steric and hydrophobic interactions (fields) in flavonoid binding to P-glycoprotein (17).…”

“…The third set (marked c in Table 1) consisted of 78 flavonoids, including calcone (compounds 1-22), flavone (compounds 23-64), and aurone derivatives (compounds 65-78) (18). We excluded the derivatives of dehydrosylibin and xanthone (18) and compounds 14, 34, and 67 because of their unrelated structure and flavone 42 because of the same structure as flavone 23.…”

“…We excluded the derivatives of dehydrosylibin and xanthone (18) and compounds 14, 34, and 67 because of their unrelated structure and flavone 42 because of the same structure as flavone 23.…”

“…For this purpose, we used three sets of flavonoid derivatives and their dissociation constants (pK d ), which describe flavonoid affinity toward P-glycoprotein (16)(17)(18). The best fitting models and the best internal and external (cross-validation and test set) predictions for all sets were obtained with zero-order connectivity index ( 0 χ v ).…”

Modelling of Protective Mechanism of Iron(II)-polyphenol Binding with OH-related Molecular Descriptors

“…[22,23] There is yet no general regression model (QSAR or QSPR) for the activity and physicochemical properties of polyphenols, despite many models with various molecular descriptors were tried. The binding of flavonoids to P-glycoprotein was modelled by sophisticated CoMFA and CoMSIA methods [24] and MIFs and VolSurf descriptors, [25] but also using a simple linear model based on zero-order valence molecular connectivity index. [26] The flavonoid toxicity (log cL50) to HL-60 and lamb embrio kidney fibroblast (FLK) cells were correlated to polarographic oxidation half-peak potential (E2/p) and water / octanol partition coefficient (log P) yielding in two-variable linear regression satisfactory correlation for HL-60 (r 2 = 0.915), but not for FLK cells (r 2 = 0.674).…”