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活性数据离散分布下的瑞香狼毒抗肿瘤活性成分筛选研究
杨乾栩1,程孟春1,王莉1,阚晓溪2,朱晓新2F,肖红斌1, 2
1中国科学院大连化学物理研究所,中科院分离分析化学重点实验室,辽宁 大连 116023
2中国中医科学院中药研究所,北京100700
摘要:活性数据离散分布下的瑞香狼毒抗肿瘤活性部位和成分的筛选、提取、验证研究。分别采用HPD大孔树脂柱和聚酰胺柱获得具有成分差异的瑞香狼毒部位,并用MTT法考察不同部位对人肺癌细胞A549的抑制活性。结果显示不同部位的A549抑制活性呈现离散分布。权重分析表明,色谱图上的33.97 min成分及30-39 min部位对A549抑制作用较大。活性实验表明,30-39 min部位要优于瑞香狼毒醇提物,33.97 min成分在100 μg/mL水平内,与阳性药顺铂作用相当,但作用方式完全不同。在离散活性条件下,权重分析方法对中药活性成分或部位,具有较好的筛选效果。
关键词:瑞香狼毒;离散活性数据;权重分析;活性成分;抗肿瘤
Antitumor components screening in Stellera chamaejasme L. under the case of discrete distribution of active data
YANG Qian-xu1, CHENG Meng-chun1, WANG Li1, KAN Xiao-xi2, XIAO Hong-bin1*,ZHU Xiao-xin2F
1CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Dalian 116023, China
2Institute of Chinese Materia Medica Academy, China Academy of Chinese Medical Sciences, Beijing 100700, China
Abstract: Screening, extracting and validating antitumor components and compounds in Stellera chamaejasme L. under the case of discrete distribution of active data. In this work, different components in Stellera chamaejasme L. were collected by HPD macroporous resin and polyamide resin column, and their antitumor activity to A549 were tested by MTT assay. Activity results indicate that activity of components in 30-39 min are prior to Stellera chamaejasme L. extract, and activity of components in 33.97 min are equivalent to positive drug, cis-platinum at 100 μg/mL, but with totally different mode of action. Under the case of discrete activity, the weight analysis is capable of screening active components and compounds of natural product.
Key words: Stellera chamaejasme L.; Discrete-active data; Weight analysis; Bioactive components; Antitumor
癌症是人类最主要的“杀手”之一,抗癌药物的发现,一直是药物研究工作者的不朽使命。
瑞香狼毒,瑞香科狼毒属植物狼毒(Stellera chamaejasme L.)的干燥根,俗名又叫断肠草,其味苦辛,性平,具有逐水祛痰,破积杀虫之效,在我国具有悠久的用药历史[1]。现代药理表明,瑞香狼毒提取物具有较强的抗肿瘤,抗病毒,抗真菌,酶抑制等活性[2]。然而瑞香狼毒成分复杂,已报道的主要包括香豆素类、生物碱类、二萜类和黄酮类[3, 4]。而相关的活性报道,大部分集中在狼毒提取物的活性研究[5, 6],单体活性研究相对偏少,其药效物质基础研究薄弱,尚需要进一步挖掘。
谱效学研究是建立指纹谱与相应活性之间的关系,进而用于发掘中药有效成分或成分群 [7, 8],或基于此的质量控制研究[9]。目前已有的谱效学相关研究,大部分集中在采用回归建模为基础的方法[10, 11],在模型的基础上,通过不同的策略实现活性成分的挖掘。对于采用模型回归分析结合变量筛选的谱效学分析方法,其风险性在于对数据要求较为严格,包括1)离散点对结果影响较大。离域值较大的实验数据,会使回归曲线向离散点偏移,从而造成预测结果的不准确;2)活性数据要具有较好的连续性。连续性较差的活性数据,其构造的回归模型可信度较低。而目前的中药分离手段相对较为粗犷,分离能力有限,导致成分差异较为严重,从而造成不同部位的活性差异较大。另外由于生物活性的药效曲线特点,尤其是当药物作用为S型药效曲线,此时随机获取组分的活性往往呈现高低活性较多,适中活性较少的分布特点,因而造成了活性数据分布相对离散的特点。
在本文,我们针对中药部位活性差异较大的特点,提出了针对离散活性数据的活性成分筛选方法。将化学计量学中的权重模型[12],引入并应用在瑞香狼毒的抗肿瘤活性成分分析,筛选出一个活性较高的部位和一个化合物,并对结果进行了验证,取得了有意义的结果。
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