Abstract
The relationship between the physicochemical characteristics of 27 new drug candidates and their distribution into the melanin-containing structure of the rat eye, the uveal tract, was examined. Tissue distribution data were obtained from whole-body autoradiograms of pigmented Long–Evans rats sacrificed at 5 min and 96 hr after dosing. The physicochemical parameters considered include molecular weight, pK a, degree of ionization, octanol/water partition coefficient (log P o/w), drug-melanin binding energy, and acid/base status of the functional groups within the molecule. Multiple linear regression analysis was used to describe the best model correlating physicochemical and/or biological characteristics of these compounds to their initial distribution at 5 min and to the retention of residual radioactivity in ocular melanin at 96 hr post-injection. The early distribution was a function primarily of acid/base status, pK a, binding energy, and log P (o/W), whereas uveal tract retention in rats was a function of volume of distribution (V 1), log P (o/w), pK a, and binding energy. Further, there was a relationship between the initial distribution of a compound into the uveal tract and its retention 96 hr later. More specifically, the structures most likely to be distributed and ultimately retained at high concentrations were those containing strongly basic functionalities, such as piperidine or piperazine moieties and other amines. Further, the more lipophilic and, hence, widely distributed the basic compound, the greater the likelihood that it interacts with ocular melanin. In summary, the use of multiple linear regression analysis was useful in distinguishing which physicochemical characteristics of a compound or group of compounds contributed to melanin binding in pigmented rats in vivo.
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Zane, P.A., Brindle, S.D., Gause, D.O. et al. Physicochemical Factors Associated with Binding and Retention of Compounds in Ocular Melanin of Rats: Correlations Using Data from Whole-Body Autoradiography and Molecular Modeling for Multiple Linear Regression Analyses. Pharm Res 7, 935–941 (1990). https://doi.org/10.1023/A:1015997823755
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DOI: https://doi.org/10.1023/A:1015997823755