Leveraging machine learning to predict drug permeation: impact of menthol and limonene as enhancers.

IF 3.9 2区 化学 Q2 CHEMISTRY, APPLIED Molecular Diversity Pub Date : 2024-12-16 DOI:10.1007/s11030-024-11062-w
Manisha Yadav, Baddipadige Raju, Gera Narendra, Jasveer Kaur, Manoj Kumar, Om Silakari, Bharti Sapra
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Abstract

The present study aimed to develop robust machine learning (ML) models to predict the skin permeability of poorly water-soluble drugs in the presence of menthol and limonene as penetration enhancers (PEs). The ML models were also applied in virtual screening (VS) to identify hydrophobic drugs that exhibited better skin permeability in the presence of permeation enhancers i.e. menthol and limonene. The drugs identified through ML-based VS underwent experimental validation using in vitro skin penetration studies. The developed model predicted 80% probability of permeability enhancement for Sumatriptan Succinate (SS), Voriconazole (VCZ), and Pantoprazole Sodium (PS) with menthol and limonene. The in vitro release studies revealed that menthol increased penetration by approximately 2.49-fold, 2.25-fold, and 4.96-fold for SS, VCZ, and PS, respectively, while limonene enhanced permeability by approximately 1.32-fold, 2.27-fold, and 3.7-fold for SS, VCZ, and PS. The results from in silico and in vitro studies were positively correlated, indicating that the developed ML models could effectively reduce the need for extensive in vitro and in vivo experimentation.

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本研究旨在开发稳健的机器学习(ML)模型,以预测水溶性差的药物在作为渗透促进剂(PE)的薄荷醇和柠檬烯存在时的皮肤渗透性。这些 ML 模型还被应用于虚拟筛选(VS),以确定在有渗透促进剂(即薄荷醇和柠檬烯)存在时皮肤渗透性更好的疏水性药物。通过体外皮肤渗透研究对基于 ML 的虚拟筛选确定的药物进行了实验验证。所开发的模型预测,琥珀酸舒马曲普坦(SS)、伏立康唑(VCZ)和泮托拉唑钠(PS)与薄荷醇和柠檬烯的渗透性增强概率为 80%。体外释放研究表明,薄荷醇可使 SS、VCZ 和 PS 的渗透性分别提高约 2.49 倍、2.25 倍和 4.96 倍,而柠檬烯可使 SS、VCZ 和 PS 的渗透性分别提高约 1.32 倍、2.27 倍和 3.7 倍。硅学和体外研究的结果呈正相关,表明所开发的 ML 模型可有效减少大量体外和体内实验的需要。
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来源期刊
Molecular Diversity
Molecular Diversity 化学-化学综合
CiteScore
7.30
自引率
7.90%
发文量
219
审稿时长
2.7 months
期刊介绍: Molecular Diversity is a new publication forum for the rapid publication of refereed papers dedicated to describing the development, application and theory of molecular diversity and combinatorial chemistry in basic and applied research and drug discovery. The journal publishes both short and full papers, perspectives, news and reviews dealing with all aspects of the generation of molecular diversity, application of diversity for screening against alternative targets of all types (biological, biophysical, technological), analysis of results obtained and their application in various scientific disciplines/approaches including: combinatorial chemistry and parallel synthesis; small molecule libraries; microwave synthesis; flow synthesis; fluorous synthesis; diversity oriented synthesis (DOS); nanoreactors; click chemistry; multiplex technologies; fragment- and ligand-based design; structure/function/SAR; computational chemistry and molecular design; chemoinformatics; screening techniques and screening interfaces; analytical and purification methods; robotics, automation and miniaturization; targeted libraries; display libraries; peptides and peptoids; proteins; oligonucleotides; carbohydrates; natural diversity; new methods of library formulation and deconvolution; directed evolution, origin of life and recombination; search techniques, landscapes, random chemistry and more;
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