Multivariate quantitative structure-pharmacokinetic relationships (QSPKR) analysis of adenosine A(1) receptor agonists in rat

The aim of this study was to investigate the feasibility of a quantitative structure-pharmacokinetic relationships (QSPKR) method based on contemporar y three-dimensional (3D) molecular characterization and multivariate statis tical analysis. For this purpose, the programs SYBYL/CoMFA, GRID, and Palla s, in combination with the multivariate statistical technique principal com ponent analysis were employed to generate a total of 16 descriptor variable s for a series of 12 structurally related adenosine A(1) receptor agonists. Subsequently, the multivariate regression method, partial least squares, w as used to predict clearance (CL), volume of distribution (Vd(SS)) and prot ein binding (fraction unbound, fu). The QSPKR models obtained could account for mast of the variation in CL, Vd(SS), and f(U) (R-2 = 0.82, 0.61 and 0. 78, respectively). Cross-validation confirmed the predictive ability of the models (Q(2) = 0.59, 0.41 and 0.62 far CL, Vd(SS), and fu, respectively). In conclusion, we have developed a multivariate 3D QSPKR model that could a dequately predict overall pharmacokinetic behavior of adenosine A(1) recept or agonists in rat. This methodology can also be used for other classes of compounds and may facilitate the further integration of QSPKR in drug disco very and preclinical development.