Compatibility optimization of the traditional Chinese medicines 'Eczema mixture' based on back-propagation artificial neural network and non-dominated sorting genetic algorithm.

IF 4.4 2区 医学 Q1 PHARMACOLOGY & PHARMACY
Frontiers in Pharmacology Pub Date : 2025-05-02 eCollection Date: 2025-01-01 DOI:10.3389/fphar.2025.1593783
Xin He, Zhijie Song, Yanqun Yang, Siqi Wu, Shuo Meng, Huanyu E, Hongfei Li, Guoyu Ding
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Abstract

Introduction: Chinese medicine formulas (CMF) are an important aspect of traditional Chinese medicine (TCM) and are formulated based on strict compatibility proportions guided by TCM theory. Due to the complex chemical constituents of TCM and the diversity of evaluation indicators for a certain disease, the research strategy on how to obtain the optimal combination of these crude extracts, homologous compounds or even the specific compounds mixture becomes the key step in the study of compatibility proportion research. Therefore, in this research, the "Eczema mixture" (EM) which includes six kinds of Chinese medicinal materials for the treatment of atopic dermatitis was cited as an example to illustrate the proposed compatibility optimization strategy.

Methods: Ultra-performance liquid chromatography-quadrupole/time-of-flight (UPLC-Q/TOF) technology was used to analyze the chemical components in the EM formula, and a total of 136 chemical compounds were identified. 76 formulas with different compatibility ratios were generated with the simplex centroid mixture design (SCMD). Two defined objective functions, the maximum of the anti-inflammatory and anti-allergic activity were used to evaluate the bioactivities of all the formulas. The 6-n-2 three-layers of back-propagation artificial neural network (BP-ANN) was employed to model the two defined objective functions. With the predictive models, the Pareto front was determined by a variant of non-dominated sorting genetic algorithm II(VNSGAII) to provide the optimal prescription set.

Results: The 6-n-2 three-layers of artificial neural networks demonstrated a satisfactory fitting effect for the nonlinear activity relationship. In the EM formula, Huangbai and Kushen were identified as the main botanical drugs with anti-inflammatory and anti-allergic roles. The results were consistent with the clinical application of the 113 prescriptions involving 230 botanical drugs for the treatment of AD from the 'Dictionary of Traditional Chinese Medicine Prescription'.

Conclusion: The proposed SCMD-ANN-VNSGAII is a powerful approach that may facilitate future compatibility optimization of homologous compounds or specific component mixtures.

基于反向传播人工神经网络和非支配排序遗传算法的中药“湿疹合剂”配伍优化
中药方剂(CMF)是中医的一个重要方面,在中医理论的指导下,根据严格的配伍比例配制。由于中药化学成分复杂,对某一疾病的评价指标多样,如何获得这些粗提物、同源化合物甚至特定化合物混合物的最佳组合成为配伍比例研究的关键步骤。因此,本研究以6种中药治疗特应性皮炎的“湿疹合剂”(EM)为例,说明所提出的配伍优化策略。方法:采用超高效液相色谱-四极杆/飞行时间(UPLC-Q/TOF)技术对EM配方中的化学成分进行分析,共鉴定出136种化合物。采用单形质心混合设计(SCMD),得到了76个不同配伍比的配方。用抗炎活性最大值和抗过敏活性最大值两个确定的目标函数来评价各制剂的生物活性。采用6-n-2三层反向传播人工神经网络(BP-ANN)对两个定义的目标函数进行建模。在预测模型的基础上,利用非支配排序遗传算法ⅱ(VNSGAII)的一种变体确定Pareto前沿,以提供最优处方集。结果:6-n-2三层人工神经网络对非线性活动关系的拟合效果较好。EM方中,黄柏和苦参为主要的植物性抗炎、抗过敏药物。结果与《中药方剂大辞典》中治疗AD的113个方剂230个植物性药物的临床应用一致。结论:所建立的SCMD-ANN-VNSGAII是一种有效的方法,可为未来同源化合物或特定组分混合物的相容性优化提供便利。
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来源期刊
Frontiers in Pharmacology
Frontiers in Pharmacology PHARMACOLOGY & PHARMACY-
CiteScore
7.80
自引率
8.90%
发文量
5163
审稿时长
14 weeks
期刊介绍: Frontiers in Pharmacology is a leading journal in its field, publishing rigorously peer-reviewed research across disciplines, including basic and clinical pharmacology, medicinal chemistry, pharmacy and toxicology. Field Chief Editor Heike Wulff at UC Davis is supported by an outstanding Editorial Board of international researchers. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians and the public worldwide.
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