多靶点药物能同时调节多靶点、调节疾病网络的多个环节,在获得较高疗效的同时可降低单靶点引起的毒副作用,是治疗复杂性疾病的理想药物,因此已成为药物研发的主要方向。而天然产物凭借其结构的多样性,较高的多靶点活性和较小的毒副作用...多靶点药物能同时调节多靶点、调节疾病网络的多个环节,在获得较高疗效的同时可降低单靶点引起的毒副作用,是治疗复杂性疾病的理想药物,因此已成为药物研发的主要方向。而天然产物凭借其结构的多样性,较高的多靶点活性和较小的毒副作用等优势,是多靶点药物开发的重要来源。计算机辅助药物设计(computer-aided drug design,CADD)是常用的多靶点药物研发方法,其主要包括虚拟筛选和药效团设计。该文对其进行了系统梳理,探讨了各方法用于天然产物多靶点药物研发的前景与优势。展开更多
Naodesheng(NDS) formula, which consists of Rhizoma Chuanxiong, Lobed Kudzuvine, Carthamus tinctorius, Radix Notoginseng, and Crataegus pinnatifida, is widely applied for the treatment of cardio/cerebrovascular ischemi...Naodesheng(NDS) formula, which consists of Rhizoma Chuanxiong, Lobed Kudzuvine, Carthamus tinctorius, Radix Notoginseng, and Crataegus pinnatifida, is widely applied for the treatment of cardio/cerebrovascular ischemic diseases, ischemic stroke, and sequelae of cerebral hemorrhage, etc. At present, the studies on NDS formula for Alzheimer's disease(AD) only focus on single component of this prescription, and there is no report about the synergistic mechanism of the constituents in NDS formula for the potential treatment of dementia. Therefore, the present study aimed to predict the potential targets and uncover the mechanisms of NDS formula for the treatment of AD. Firstly, we collected the constituents in NDS formula and key targets toward AD. Then, drug-likeness, oral bioavailability, and blood-brain barrier permeability were evaluated to find drug-like and lead-like constituents for treatment of central nervous system diseases. By combining the advantages of machine learning, molecular docking, and pharmacophore mapping, we attempted to predict the targets of constituents and find potential multi-target compounds from NDS formula. Finally, we built constituent-target network, constituent-target-target network and target-biological pathway network to study the network pharmacology of the constituents in NDS formula. To the best of our knowledge, this represented the first to study the mechanism of NDS formula for potential efficacy for AD treatment by means of the virtual screening and network pharmacology methods.展开更多
文摘多靶点药物能同时调节多靶点、调节疾病网络的多个环节,在获得较高疗效的同时可降低单靶点引起的毒副作用,是治疗复杂性疾病的理想药物,因此已成为药物研发的主要方向。而天然产物凭借其结构的多样性,较高的多靶点活性和较小的毒副作用等优势,是多靶点药物开发的重要来源。计算机辅助药物设计(computer-aided drug design,CADD)是常用的多靶点药物研发方法,其主要包括虚拟筛选和药效团设计。该文对其进行了系统梳理,探讨了各方法用于天然产物多靶点药物研发的前景与优势。
基金supported by the Research Special Fund for the National Great Science and Technology Projects(No.2012ZX09301002-001-001)the International Collaboration Project(No.2011DFR31240)Peking Union Medical College graduate student innovation fund(No.2013-1007-18)
文摘Naodesheng(NDS) formula, which consists of Rhizoma Chuanxiong, Lobed Kudzuvine, Carthamus tinctorius, Radix Notoginseng, and Crataegus pinnatifida, is widely applied for the treatment of cardio/cerebrovascular ischemic diseases, ischemic stroke, and sequelae of cerebral hemorrhage, etc. At present, the studies on NDS formula for Alzheimer's disease(AD) only focus on single component of this prescription, and there is no report about the synergistic mechanism of the constituents in NDS formula for the potential treatment of dementia. Therefore, the present study aimed to predict the potential targets and uncover the mechanisms of NDS formula for the treatment of AD. Firstly, we collected the constituents in NDS formula and key targets toward AD. Then, drug-likeness, oral bioavailability, and blood-brain barrier permeability were evaluated to find drug-like and lead-like constituents for treatment of central nervous system diseases. By combining the advantages of machine learning, molecular docking, and pharmacophore mapping, we attempted to predict the targets of constituents and find potential multi-target compounds from NDS formula. Finally, we built constituent-target network, constituent-target-target network and target-biological pathway network to study the network pharmacology of the constituents in NDS formula. To the best of our knowledge, this represented the first to study the mechanism of NDS formula for potential efficacy for AD treatment by means of the virtual screening and network pharmacology methods.
