A linear free-energy relationship (LFER) equation that is able to provide a valid prediction of the skin permeability coefficients (log K_p) of neutral molecules, ions and ionic species has recently been constructed and optimized. This study aimed to evaluate the feasibility of predicting the skin-permeating components (SPCs) of externally applied herbs using the LFER equation, with Evodiae fructus (EF) taken as a model herb. The log K_p values of the reported chemical components of EF at pH 4.0 were calculated using the LFER equation and their structural descriptors. The results showed that the essential oils, quinolone, acridone and indole alkaloids of EF are more permeable when compared to other main components, such as phenylpropanoids, furoquinoline alkaloids, limonoids and flavonoids. The SPCs of EF were further collected via ex vivo skin permeation experiments, and analyzed by liquid chromatography-high resolution tandem mass spectrometry. A total of 80 SPCs were detected, and part of them were tentatively identified based on their empirical molecular formulae and MS/MS spectra. The SPCs are made up of 58 alkaloids, including 23 or more quinolone alkaloids, 14 or more indole alkaloids and 1 acridone alkaloid, and 22 non-alkaloids, including 7 or more essential oils and 1 flavonoid, which is in good agreement with the prediction by the LFER equation. It is suggested that a log K_p of −7.0 may be considered as a borderline, above which are potential SPCs and below which are non-SPCs. Very interestingly, the primary SPCs give a good explanation to the antihypertensive action of externally applied EF. To sum up, the LFER equation can be used to predict the SPCs of externally applied herbs, and thus to narrow the range of their potential effective components and speed up the pharmacological study.

中文翻译：

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预测外用草药的皮肤渗透成分：一个新构建的线性自由能关系方程对人体皮肤渗透的应用†

最近已经构建并优化了线性自由能关系（LFER）方程，该方程可提供对中性分子，离子和离子物种的皮肤渗透系数（log K _p）的有效预测 。本研究旨在评估预测使用LFER方程外加药材的皮肤渗透成分（的SPC），具有可行性吴茱萸（EF）作为模型草本植物。使用LFER方程及其结构描述符，计算了pH为4.0时EF的已报告化学成分的log  K _p值。结果表明，EF的精油，喹诺酮，a啶酮和吲哚生物碱与其他主要成分（例如苯基丙烷，呋喃喹啉生物碱，柠檬苦素和类黄酮）相比，它们具有更好的渗透性。EF的SPC通过离体皮肤渗透实验进一步收集，并通过液相色谱-高分辨率串联质谱法进行分析。共检测到80种SPC，并根据其经验分子式和MS / MS谱图初步鉴定了其中的一部分。SPC由58种生物碱组成，其中包括23种以上喹诺酮生物碱，14种以上吲哚生物碱和1种1啶酮生物碱，以及22种非生物碱，包括7种以上精油和1种黄酮，与预测相符。通过LFER方程。建议对数 K _p-7.0的边界可以视为边界，在其之上是潜在的SPC，在其之下是非SPC。非常有趣的是，主要的SPC很好地解释了外用EF的降压作用。综上所述，LFER方程可用于预测外用草药的SPC，从而缩小其潜在有效成分的范围并加快药理研究。