消栓通络方临床上主治脑血栓引起的精神呆滞、言语迟涩等症状,疗效显著,但其作用机制尚不明确。本文通过搜集消栓通络方中的化学成分和治疗脑卒中相关靶点,获得1251个化学成分和10个脑卒中相关靶点,采用朴素贝叶斯和递归分割等机器学习...消栓通络方临床上主治脑血栓引起的精神呆滞、言语迟涩等症状,疗效显著,但其作用机制尚不明确。本文通过搜集消栓通络方中的化学成分和治疗脑卒中相关靶点,获得1251个化学成分和10个脑卒中相关靶点,采用朴素贝叶斯和递归分割等机器学习算法,基于分子指纹和分子描述符,结合分子对接方法,构建了脑卒中10个相关靶点的18个化合物-靶点相互作用预测模型。应用这些模型预测了消栓通络方的活性化学成分及其作用靶点,发现了153个潜在活性化学成分,其中22个可以与2个以上脑卒中药物靶点相互作用。在此基础上,利用网络构建专业软件,构建了化学成分-靶点网络,并通过Gene-Ontology(GO)富集分析,确证了靶点重要的生物过程,如凝血(blood coagulation)、血管生成正调控(positive regulation of angiogenesis)和离子转运正调控(positive regulation of ion transport)等。在此基础上,构建了靶点-通路网络。本研究利用机器学习、分子对接、虚拟筛选、数据挖掘及网络构建等技术方法,探索并部分揭示了消栓通络方抗脑卒中的活性物质基础及其化学成分-靶点-通路的网络作用机制,为消栓通络方的深入研究提供重要信息依据。展开更多
Cancer is a complex disease associated with multiple gene mutations and malignant phenotypes,and multi-target drugs provide a promising therapy idea for the treatment of cancer.Natural products with abundant chemical ...Cancer is a complex disease associated with multiple gene mutations and malignant phenotypes,and multi-target drugs provide a promising therapy idea for the treatment of cancer.Natural products with abundant chemical structure types and rich pharmacological characteristics could be ideal sources for screening multi-target antineoplastic drugs.In this paper,50 tumor-related targets were collected by searching the Therapeutic Target Database and Thomson Reuters Integrity database,and a multi-target anti-cancer prediction system based on mt-QSAR models was constructed by using naïve Bayesian and recursive partitioning algorithm for the first time.Through the multi-target anti-cancer prediction system,some dominant fragments that act on multiple tumor-related targets were analyzed,which could be helpful in designing multi-target anti-cancer drugs.Anti-cancer traditional Chinese medicine(TCM)and its natural products were collected to form a TCM formula-based natural products library,and the potential targets of the natural products in the library were predicted by multi-target anti-cancer prediction system.As a result,alkaloids,flavonoids and terpenoids were predicted to act on multiple tumor-related targets.The predicted targets of some representative compounds were verified according to literature review and most of the selected natural compounds were found to exert certain anti-cancer activity in vitro biological experiments.In conclusion,the multi-target anti-cancer prediction system is very effective and reliable,and it could be further used for elucidating the functional mechanism of anti-cancer TCM formula and screening for multi-target anti-cancer drugs.The anti-cancer natural compounds found in this paper will lay important information for further study.展开更多
文摘消栓通络方临床上主治脑血栓引起的精神呆滞、言语迟涩等症状,疗效显著,但其作用机制尚不明确。本文通过搜集消栓通络方中的化学成分和治疗脑卒中相关靶点,获得1251个化学成分和10个脑卒中相关靶点,采用朴素贝叶斯和递归分割等机器学习算法,基于分子指纹和分子描述符,结合分子对接方法,构建了脑卒中10个相关靶点的18个化合物-靶点相互作用预测模型。应用这些模型预测了消栓通络方的活性化学成分及其作用靶点,发现了153个潜在活性化学成分,其中22个可以与2个以上脑卒中药物靶点相互作用。在此基础上,利用网络构建专业软件,构建了化学成分-靶点网络,并通过Gene-Ontology(GO)富集分析,确证了靶点重要的生物过程,如凝血(blood coagulation)、血管生成正调控(positive regulation of angiogenesis)和离子转运正调控(positive regulation of ion transport)等。在此基础上,构建了靶点-通路网络。本研究利用机器学习、分子对接、虚拟筛选、数据挖掘及网络构建等技术方法,探索并部分揭示了消栓通络方抗脑卒中的活性物质基础及其化学成分-靶点-通路的网络作用机制,为消栓通络方的深入研究提供重要信息依据。
基金supported by the National Great Science Technology Projects(2018ZX09711001-003-002,2018ZX09711001-012)the National Natural Science Foundation of China(No.81673480)+2 种基金the Beijing National Science Foundation(7192134)CAMS Initiative for Innovative Medicine(CAMS-IZM)(2016-IZM-3-007)CAMS Major collaborative innovation fund for major frontier research(2020-I2M-1-003).
文摘Cancer is a complex disease associated with multiple gene mutations and malignant phenotypes,and multi-target drugs provide a promising therapy idea for the treatment of cancer.Natural products with abundant chemical structure types and rich pharmacological characteristics could be ideal sources for screening multi-target antineoplastic drugs.In this paper,50 tumor-related targets were collected by searching the Therapeutic Target Database and Thomson Reuters Integrity database,and a multi-target anti-cancer prediction system based on mt-QSAR models was constructed by using naïve Bayesian and recursive partitioning algorithm for the first time.Through the multi-target anti-cancer prediction system,some dominant fragments that act on multiple tumor-related targets were analyzed,which could be helpful in designing multi-target anti-cancer drugs.Anti-cancer traditional Chinese medicine(TCM)and its natural products were collected to form a TCM formula-based natural products library,and the potential targets of the natural products in the library were predicted by multi-target anti-cancer prediction system.As a result,alkaloids,flavonoids and terpenoids were predicted to act on multiple tumor-related targets.The predicted targets of some representative compounds were verified according to literature review and most of the selected natural compounds were found to exert certain anti-cancer activity in vitro biological experiments.In conclusion,the multi-target anti-cancer prediction system is very effective and reliable,and it could be further used for elucidating the functional mechanism of anti-cancer TCM formula and screening for multi-target anti-cancer drugs.The anti-cancer natural compounds found in this paper will lay important information for further study.
