Alves Vinicius M, Muratov Eugene, Fourches Denis, Strickland Judy, Kleinstreuer Nicole, Andrade Carolina H, Tropsha Alexander
Laboratory of Molecular Modeling and Design, Faculty of Pharmacy, Federal University of Goiás, Goiânia, GO 74605-220, Brazil; Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599, USA.
Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599, USA; Laboratory of Theoretical Chemistry, A.V. Bogatsky Physical-Chemical Institute NAS of Ukraine, Odessa 65080, Ukraine.
Toxicol Appl Pharmacol. 2015 Apr 15;284(2):273-80. doi: 10.1016/j.taap.2014.12.013. Epub 2015 Jan 3.
Skin permeability is widely considered to be mechanistically implicated in chemically-induced skin sensitization. Although many chemicals have been identified as skin sensitizers, there have been very few reports analyzing the relationships between molecular structure and skin permeability of sensitizers and non-sensitizers. The goals of this study were to: (i) compile, curate, and integrate the largest publicly available dataset of chemicals studied for their skin permeability; (ii) develop and rigorously validate QSAR models to predict skin permeability; and (iii) explore the complex relationships between skin sensitization and skin permeability. Based on the largest publicly available dataset compiled in this study, we found no overall correlation between skin permeability and skin sensitization. In addition, cross-species correlation coefficient between human and rodent permeability data was found to be as low as R(2)=0.44. Human skin permeability models based on the random forest method have been developed and validated using OECD-compliant QSAR modeling workflow. Their external accuracy was high (Q(2)ext=0.73 for 63% of external compounds inside the applicability domain). The extended analysis using both experimentally-measured and QSAR-imputed data still confirmed the absence of any overall concordance between skin permeability and skin sensitization. This observation suggests that chemical modifications that affect skin permeability should not be presumed a priori to modulate the sensitization potential of chemicals. The models reported herein as well as those developed in the companion paper on skin sensitization suggest that it may be possible to rationally design compounds with the desired high skin permeability but low sensitization potential.
皮肤渗透性在化学诱导的皮肤致敏作用中被广泛认为具有机制上的牵连。尽管许多化学物质已被鉴定为皮肤致敏剂，但很少有报告分析致敏剂和非致敏剂的分子结构与皮肤渗透性之间的关系。本研究的目标是：（i）汇编、整理和整合关于皮肤渗透性研究的最大的公开可用化学物质数据集；（ii）开发并严格验证用于预测皮肤渗透性的定量构效关系（QSAR）模型；（iii）探索皮肤致敏和皮肤渗透性之间的复杂关系。基于本研究汇编的最大公开可用数据集，我们发现皮肤渗透性与皮肤致敏之间没有总体相关性。此外，发现人和啮齿动物渗透性数据之间的跨物种相关系数低至R(2)=0.44。基于随机森林方法的人体皮肤渗透性模型已使用符合经合组织（OECD）标准的QSAR建模工作流程进行了开发和验证。它们的外部准确性很高（对于适用范围内63%的外部化合物，Q(2)ext=0.73）。使用实验测量数据和QSAR估算数据进行的扩展分析仍然证实皮肤渗透性与皮肤致敏之间不存在任何总体一致性。这一观察结果表明，不应先验地假定影响皮肤渗透性的化学修饰会调节化学物质的致敏潜力。本文报道的模型以及在关于皮肤致敏的配套论文中开发的模型表明，有可能合理设计出具有所需的高皮肤渗透性但低致敏潜力的化合物。
