Predicting percutaneous permeation for new succinimide derivatives by in vitro and in silico models

Abstract

Percutaneous permeation of twenty-four newly synthesized succinimide derivatives was evaluated using parallel artificial membrane permeability assay (PAMPA) with 70% silicone oil and 30% isopropyl myristate. Different online tools were applied for in silico predicting of their skin permeability. According to the in silico estimation of the transdermal permeation, all compounds are expected to have relatively good ability to permeate the skin, at pH=6. However, for two compounds containing carboxylic groups, the concentration in the acceptor compartment was undetectable indicating limited permeation at pH=7.4. Statistically significant association was found between in silico predicted logKp values by the PreADMET and SwissADME online tools and the percutaneous permeability estimated from the experimental results using the artificial membranes (adj. r2 = 0.371, p = 0.00158 and adj. r2=0.232, p = 0.0135, respectively). The association between permeation through artificial membranes and the calculated logP data was also statistically significant. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) took into account in silico logKp and calculated logP data. The ranking of the lipophilicity and skin permeability parameters was conducted with sum of ranking differences (SRD) analysis which was validated. Based on the obtained results, it is predicted that lipophilicity is a pivotal physico-chemical parameter of the passive permeation of succinimide derivatives through hydrophobic barriers such as the skin.