Key Laboratory of Theory of TCM, Ministry of Education of China , Shandong University of Traditional Chinese Medicine , Jinan 250355 , China.
J Chem Inf Model. 2019 Dec 23;59(12):5065-5073. doi: 10.1021/acs.jcim.9b00682. Epub 2019 Dec 10.
Cold-hot nature theory is the core basic theory of traditional Chinese medicine (TCM). "Treating the hot syndrome with cold nature medicine and treating cold syndrome with hot nature medicine" indicates that correct classification of medical properties (cold or hot nature) of Chinese herbal medicines (CHMs) is an important basis for TCM treatment. In this study, we propose a novel multisolvent similarity measure retrieval scheme (MSSMRS) for discriminating CHMs as cold or hot. We explore a multisolvent distance metric learning algorithm to calculate similarity measure of CHM ingredients, and a retrieval scheme for nature identification. First, four solvents (chloroform, distilled water, absolute ethanol, and petroleum ether) are applied to extract ultraviolet (UV) spectrum data of CHM ingredients. Second, we study quantifying the similarity of CHM ingredients to fingerprint similarity. We explore a multisolvent distance metric learning (MSDML) algorithm to measure the similarity of CHM ingredients. MSDML can discover complementary characteristics of different solvent data sets through an optimization algorithm. Finally, a retrieval scheme is designed to analyze the relationship between the CHM ingredients and cold-hot nature. Extensive experimental results demonstrate that CHMs with similar compositions of substances have similar medicinal natures. Experimental evaluations based on the proposed retrieval scheme suggest the effectiveness of MSDML in the identification of the nature of CHMs.
寒-热性质理论是中医（TCM）的核心基础理论。“用寒性质的药物治疗热证，用热性质的药物治疗寒证”表明，正确分类中药（CHM）的药性（寒或热）是 TCM 治疗的重要基础。在这项研究中，我们提出了一种新的多溶剂相似性度量检索方案（MSSMRS），用于区分 CHM 的寒-热性质。我们探索了一种多溶剂距离度量学习算法来计算 CHM 成分的相似性度量，并提出了一种用于性质识别的检索方案。首先，使用四种溶剂（氯仿、蒸馏水、无水乙醇和石油醚）提取 CHM 成分的紫外（UV）光谱数据。其次，我们研究了量化 CHM 成分指纹相似性的方法。我们探索了一种多溶剂距离度量学习（MSDML）算法来测量 CHM 成分的相似性。MSDML 可以通过优化算法发现不同溶剂数据集的互补特征。最后，设计了一种检索方案来分析 CHM 成分与寒-热性质之间的关系。广泛的实验结果表明，具有相似物质成分的 CHM 具有相似的药性。基于所提出的检索方案的实验评估表明，MSDML 在 CHM 性质识别方面是有效的。
