运用CADD探讨穿心莲内酯衍生物抑制ALPHA-葡萄糖苷酶的构效关系及构建其跨膜转运预测系统
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摘要
穿心莲内酯是中药穿心莲的主要有效成分之一,有关其消炎、抗菌、抗疟疾、抗肿瘤、免疫调节、保肝护肝等多种药理活性早有报道。随着研究的不断深入,穿心莲内酯更多的药理活性正在被人们所认识,相关临床应用也得以不断拓展。近年研究发现,穿心莲内酯具有降低糖尿病大鼠血糖的作用,同时发现穿心莲内酯衍生物通过抑制小肠内α-葡萄糖苷酶的活性,延缓肠道对葡萄糖的吸收,能有效降低餐后高血糖,对于糖尿病的有效防治具有积极的作用。但是,目前尚未有一种穿心莲内酯衍生物来源的α-葡萄糖苷酶抑制剂被推向市场。据此,目前有多个研究小组正在以穿心莲内酯为母核,对其进行结构修饰与改造,以期得到具有活性更强,毒性更低的α-葡萄糖苷酶抑制剂。
迄今已有众多具有明显α-葡萄糖苷酶抑制活性穿心莲内酯衍生物问世。这为穿心莲内酯衍生物来源的α-葡萄糖苷酶抑制剂的研究与开发奠定了坚实的基础。然而,现行有关穿心莲内酯衍生物来源的α-葡萄糖苷酶抑制剂的研发模式仍主要沿用传统的新药筛选及设计的技术路线。因其周期长、耗资巨大而限制了穿心莲内酯衍生物来源的α-葡萄糖苷酶抑制剂的研发进程。
随着计算机科学的不断发展以及各种药学类数据库的不断扩充,计算机辅助药物设计凭借其高效、低耗、应用范围广,重新获得了广大药物研发工作者的青睐。利用计算机辅助药物设计(Computer Aided Drug Design, CADD)逐渐成为一种趋势,目前已经有不少借助计算机辅助药物设计的新药推向市场。因此,倘若能够有效地将CADD应用于穿心莲内酯衍生物来源的α-葡萄糖苷酶抑制剂的研发,无疑对其研发进程产生积极地促进作用。
研究目的：
了解全面、完整的构效关系信息对于提高穿心莲内酯衍生物来源的α-葡萄糖苷酶抑制剂的研发效率十分必要,但目前这类信息尚不完善。基于此因,本研究拟通过构建穿心莲内酯衍生物抑制α-葡萄糖苷酶的2D、3D定量构效关系模型,探讨穿心莲内酯衍生物结构中与其抑制α-葡萄糖苷酶的活性密切相关的分子碎片及其空间分布；并采用对接方法搜寻α-葡萄糖苷酶与穿心莲内酯衍生物相互作用的活性位点和关键残基,阐明它们之间的相互作用关系。
表征候选化合物的药物代谢动力学特性,尤其早期考察其小肠吸收能力和跨越血脑屏障等跨膜转运能力是新药筛选与开发的必要环节,影响着新药研发的方向与决策。鉴于化合物的结构及理化性质决定了其跨膜转运能力,为此,本研究拟运用CADD建立穿心莲内酯衍生物跨膜转运能力预测系统,以期从大量的穿心莲内酯衍生物中高效率地获得有研究价值的候选化合物。
研究方法：
第一部分穿心莲内酯衍生物抑制α-葡萄糖苷酶的构效关系研究
1利用HQSAR构建穿心莲内酯衍生物来源的α-葡萄糖苷酶抑制剂2D-QSAR模型,同时利用CoMFA以及CoMSIA构建3D-QSAR模型。进一步利用所构建的QSAR模型预测新型穿心莲内酯衍生物AL-1对α-葡萄糖苷酶的抑制活性,并通过体外实验加以验证。
2利用Lineweaver方程法初步探讨穿心莲内酯衍生物抑制α-葡萄糖苷酶反应类型。并通过同源模建法预测α-葡萄糖苷酶的三维立体结构。在此基础上,进一步采用对接的方法搜寻α-葡萄糖苷酶与穿心莲内酯衍生物相互作用的活性位点及关键残基。
第二部分穿心莲内酯衍生物跨膜转运预测系统的构建
1运用Volsurf构建药物HIA的虚拟模型,以期预测穿心莲内酯衍生物跨小肠膜被吸收的能力。
2运用Volsurf构建药物跨BBB的虚拟模型,以期预测穿心莲内酯衍生物跨血脑屏障的能力。
结果：
第一部分穿心莲内酯衍生物抑制α-葡萄糖苷酶的构效关系研究
1、由2D-QSAR模型的交叉验证系数(0.730)、测试集预测值与实验值线性回归相关系数(0.945)、斜率(1.01)以及标准差(0.104)均显示该模型具备良好解释构效关系和进行预测的能力；通过3D-QSAR模型的交叉验证系数(0.794)、测试集预测值与实验值线性回归系数(0.941)、斜率(0.933)以及标准差(0.104)等指标也进一步提示本研究所构建的3D-QSAR模型具备良好描述构效关系及进行预测能力。
2、用同源模建法所构建的α-葡萄糖苷酶三维立体结构与其模板分子1UOK叠合得到它们骨架间差距的均方差(RMSD)仅为1.745A。而在此α-葡萄糖苷酶三维立体结构基础上,利用对接的方法搜寻所得的两个潜在活性位点对强α-葡萄糖苷酶抑制剂的识别准确度(AR)分别达到88.9%和77.8%。
第二部分穿心莲内酯衍生物跨膜转运机制的研究
1、虚拟HIA模型的交叉验证系数(0.72),测试集的预测值与实验值的线性回归相关系数(0.932)和斜率(0.938)均显示虚拟HIA模型具备良好的定量描述能力和预测能力。
2、虚拟BBB模型的交叉验证系数(0.64),测试集的预测准确度(78%)均支持虚拟BBB模型具有良好的定性描述能力和预测能力这一结论。
结论：
1、2D-QSAR模型能够通过穿心莲内酯衍生物分子中原子的连接方式描述其抑制α-葡萄糖苷酶的构效关系；3D-QSAR模型能够通过穿心莲内酯衍生物分子周围力场的差异来描述其构效关系。而将2D模型与3D-QSAR模型相结合,能够得到更为全面准确的构效关系结果。
2、在采用同源模建法构建合理的α-葡萄糖苷酶三维结构基础上,利用对接法搜寻得到两个潜在的活性位点均能很好识别具有α-葡萄糖苷酶强抑制活性的穿心莲内酯衍生物。
3、利用虚拟HIA模型可为穿心莲内酯衍生物来源的α-葡萄糖苷酶抑制剂的小肠吸收率的评估提供有价值的参考意见。
4、利用虚拟BBB模型可为穿心莲内酯衍生物来源的α-葡萄糖苷酶抑制剂的跨血脑屏障能力的评估提供有价值的参考意见。
Andrographolide is the main active ingredient of Andrographis paniculate. It has been reported that andrographolide has broad pharmacological activities, such as an anti-bacterial, anti-malarial, anti-inflammatory, anti-tumor, immunological regulation and hepatoprotective effects. Further researches about andrographolide reveal more application of this compound. Recent studies exhibited that andrographolide could reduce blood glucose of diabetes rats and andrographolide derivatives might decrease blood glucose level by inhibiting a-glucosidase after meal. Such pharmacological activity of inhibiting a-glucosidase would greatly contribute to the treatment for diabetes. So far, however, there has been little andrographolide derivative coming into the market as a-glucosidase inhibitor at present, while lots of researches have modified the structures of andrographolide derivatives to develop more potent inhibitors of a-glucosidase.
In this background, more and more andrographolide derivatives with inhibitory activity to a-glucosidase have been synthesized. These preceding works will promote the development of a-glucosidase inhibitors. Nevertheless, the traditional procedure to develop drug would to some extent block the development of andrographolide derivatives due to long research circle, high-cost and poor pharmacokinetics characters.
Along with the development of computer technique and extension of pharmaceutical databases, computer aided drug design (CADD) has earned re-interesting because of high efficiency, low-cost and extensive application. CADD is frequently utilized to assist the development of drug and there have been lots of drugs designed by CADD in the market. In this context, CADD would significantly contribute to the development of andrographolide derivatives as a-glucosidase inhibitors.
Objective:
QSAR information will greatly promote the development of andrographolide derivatives, but there is not enough data about this at present. Hence, this research would build the 2D and 3D-QSAR model of andrographolide derivatives as a-glucosidase inhibitors. These models could be utilized to investigate the important fragments and distribution of different force fields which are closely related to the inhibitory activity. Moreover, the potential active sites and key residues were obtained by homology modeling and docking. Information about the active sites and key residues should greatly contribute to the discovery of new a-glucosidase inhibitors.
Pharmacokinetic characteristics of candidates, especially the action of crossing human intestinal membrane and blood brain barrier, are the necessary aspect for developing new drug. In the light of the close relationship between compounds' structure and their pharmacokinetic characters, this research built the human intestinal absorption (HIA) prediction system and blood brain barrier (BBB) prediction system to predict the pharmacokinetic features of andrographolide derivatives by using CADD and specific cells'model.
Method:
1 QSAR studies on andrographolide derivatives as a-glucosidase inhibitors
(1) HQSAR was used to build the 2D-QSAR of andrographolide derivatives as a-glucosidase inhibitors and 3D-QSAR models were constructed by both CoMFA and CoMSIA methods. The best QSAR model was used to predict the inhibitory activity of Al-1 which was a new andrographolide derivative.
(2) Lineweaver-Burk method was utilized to judge the enzyme reaction style of andrographolide derivatives inhibiting a-glucosidase. And then, the potential active sites and key residues were explored by homology modeling and docking method.
2 The establishment of systems to predict andrographolide derivatives' action of crossing human intestinal membrane and blood brain barrier.
(1) Volsurf was employed to construct virtual HIA model, which was applied to predict the HIA values of andrographolide derivatives.
(2) Volsurf was used to establish virtual BBB model, which was applied to predict the andrographolide derivatives' possibillities to across the BBB.
Results:
1 QSAR studies on andrographolide derivatives as a-glucosidase inhibitors
(1) The 2D-QSAR model was successfully built and the result was supported by cross-validation coefficient (0.730), correlation coefficient (0.945), standard error (0.104) and slope (1.01); the best 3D-QSAR model was validated by cross-validation coefficient (0.794), correlation coefficient (0.941), slope (0.933) and standard error (0.104).
(2) The homology model of a-glucosidase was validated by RMSD (1.745 A) of structural alignment. The predicted strong inhibitors'ARs of the two potential active sites were 88.9% and 77.8% respectively.
2 The establishment of systems to predict andrographolide derivatives' action of crossing human intestinal membrane and blood brain barrier.
(1) The virtual HIA model was verified by cross-validation coefficient (0.72), correlation coefficient (0.932) and slope (0.938).
(2) The virtual BBB model was confirmed by cross-validation coefficient (0.64), accuracy rate of test set (78%).
Conclusion:
(1) The 2D-QSAR model exhibited the important fragments of andrographolide derivatives, which were closely related to bio-activity; the 3D-QSAR model could exhibit the distribution of different force fields, which is closely related to bio-activity. Combining 2D and 3D-QSAR model, the information from QSAR models would be more comprehensive and precise.
(2) The homology model ofα-glucosidase could be used to explore the potential active sites and key residues. And the two potential active sites had great recognition to andrographolide derivatives with strong inhibitory activities toα-glucosidase.
(3) The virtual HIA model would contribute to the prediction of the pharmacokinetic characteristics of andrographolide derivatives asα-glucosidase inhibitors.
(4) The virtual BBB model would contribute to the prediction of the pharmacokinetic characteristics of andrographolide derivatives as a-glucosidase inhibitors.
迄今已有众多具有明显α-葡萄糖苷酶抑制活性穿心莲内酯衍生物问世。这为穿心莲内酯衍生物来源的α-葡萄糖苷酶抑制剂的研究与开发奠定了坚实的基础。然而,现行有关穿心莲内酯衍生物来源的α-葡萄糖苷酶抑制剂的研发模式仍主要沿用传统的新药筛选及设计的技术路线。因其周期长、耗资巨大而限制了穿心莲内酯衍生物来源的α-葡萄糖苷酶抑制剂的研发进程。
随着计算机科学的不断发展以及各种药学类数据库的不断扩充,计算机辅助药物设计凭借其高效、低耗、应用范围广,重新获得了广大药物研发工作者的青睐。利用计算机辅助药物设计(Computer Aided Drug Design, CADD)逐渐成为一种趋势,目前已经有不少借助计算机辅助药物设计的新药推向市场。因此,倘若能够有效地将CADD应用于穿心莲内酯衍生物来源的α-葡萄糖苷酶抑制剂的研发,无疑对其研发进程产生积极地促进作用。
研究目的：
了解全面、完整的构效关系信息对于提高穿心莲内酯衍生物来源的α-葡萄糖苷酶抑制剂的研发效率十分必要,但目前这类信息尚不完善。基于此因,本研究拟通过构建穿心莲内酯衍生物抑制α-葡萄糖苷酶的2D、3D定量构效关系模型,探讨穿心莲内酯衍生物结构中与其抑制α-葡萄糖苷酶的活性密切相关的分子碎片及其空间分布；并采用对接方法搜寻α-葡萄糖苷酶与穿心莲内酯衍生物相互作用的活性位点和关键残基,阐明它们之间的相互作用关系。
表征候选化合物的药物代谢动力学特性,尤其早期考察其小肠吸收能力和跨越血脑屏障等跨膜转运能力是新药筛选与开发的必要环节,影响着新药研发的方向与决策。鉴于化合物的结构及理化性质决定了其跨膜转运能力,为此,本研究拟运用CADD建立穿心莲内酯衍生物跨膜转运能力预测系统,以期从大量的穿心莲内酯衍生物中高效率地获得有研究价值的候选化合物。
研究方法：
第一部分穿心莲内酯衍生物抑制α-葡萄糖苷酶的构效关系研究
1利用HQSAR构建穿心莲内酯衍生物来源的α-葡萄糖苷酶抑制剂2D-QSAR模型,同时利用CoMFA以及CoMSIA构建3D-QSAR模型。进一步利用所构建的QSAR模型预测新型穿心莲内酯衍生物AL-1对α-葡萄糖苷酶的抑制活性,并通过体外实验加以验证。
2利用Lineweaver方程法初步探讨穿心莲内酯衍生物抑制α-葡萄糖苷酶反应类型。并通过同源模建法预测α-葡萄糖苷酶的三维立体结构。在此基础上,进一步采用对接的方法搜寻α-葡萄糖苷酶与穿心莲内酯衍生物相互作用的活性位点及关键残基。
第二部分穿心莲内酯衍生物跨膜转运预测系统的构建
1运用Volsurf构建药物HIA的虚拟模型,以期预测穿心莲内酯衍生物跨小肠膜被吸收的能力。
2运用Volsurf构建药物跨BBB的虚拟模型,以期预测穿心莲内酯衍生物跨血脑屏障的能力。
结果：
第一部分穿心莲内酯衍生物抑制α-葡萄糖苷酶的构效关系研究
1、由2D-QSAR模型的交叉验证系数(0.730)、测试集预测值与实验值线性回归相关系数(0.945)、斜率(1.01)以及标准差(0.104)均显示该模型具备良好解释构效关系和进行预测的能力；通过3D-QSAR模型的交叉验证系数(0.794)、测试集预测值与实验值线性回归系数(0.941)、斜率(0.933)以及标准差(0.104)等指标也进一步提示本研究所构建的3D-QSAR模型具备良好描述构效关系及进行预测能力。
2、用同源模建法所构建的α-葡萄糖苷酶三维立体结构与其模板分子1UOK叠合得到它们骨架间差距的均方差(RMSD)仅为1.745A。而在此α-葡萄糖苷酶三维立体结构基础上,利用对接的方法搜寻所得的两个潜在活性位点对强α-葡萄糖苷酶抑制剂的识别准确度(AR)分别达到88.9%和77.8%。
第二部分穿心莲内酯衍生物跨膜转运机制的研究
1、虚拟HIA模型的交叉验证系数(0.72),测试集的预测值与实验值的线性回归相关系数(0.932)和斜率(0.938)均显示虚拟HIA模型具备良好的定量描述能力和预测能力。
2、虚拟BBB模型的交叉验证系数(0.64),测试集的预测准确度(78%)均支持虚拟BBB模型具有良好的定性描述能力和预测能力这一结论。
结论：
1、2D-QSAR模型能够通过穿心莲内酯衍生物分子中原子的连接方式描述其抑制α-葡萄糖苷酶的构效关系；3D-QSAR模型能够通过穿心莲内酯衍生物分子周围力场的差异来描述其构效关系。而将2D模型与3D-QSAR模型相结合,能够得到更为全面准确的构效关系结果。
2、在采用同源模建法构建合理的α-葡萄糖苷酶三维结构基础上,利用对接法搜寻得到两个潜在的活性位点均能很好识别具有α-葡萄糖苷酶强抑制活性的穿心莲内酯衍生物。
3、利用虚拟HIA模型可为穿心莲内酯衍生物来源的α-葡萄糖苷酶抑制剂的小肠吸收率的评估提供有价值的参考意见。
4、利用虚拟BBB模型可为穿心莲内酯衍生物来源的α-葡萄糖苷酶抑制剂的跨血脑屏障能力的评估提供有价值的参考意见。
Andrographolide is the main active ingredient of Andrographis paniculate. It has been reported that andrographolide has broad pharmacological activities, such as an anti-bacterial, anti-malarial, anti-inflammatory, anti-tumor, immunological regulation and hepatoprotective effects. Further researches about andrographolide reveal more application of this compound. Recent studies exhibited that andrographolide could reduce blood glucose of diabetes rats and andrographolide derivatives might decrease blood glucose level by inhibiting a-glucosidase after meal. Such pharmacological activity of inhibiting a-glucosidase would greatly contribute to the treatment for diabetes. So far, however, there has been little andrographolide derivative coming into the market as a-glucosidase inhibitor at present, while lots of researches have modified the structures of andrographolide derivatives to develop more potent inhibitors of a-glucosidase.
In this background, more and more andrographolide derivatives with inhibitory activity to a-glucosidase have been synthesized. These preceding works will promote the development of a-glucosidase inhibitors. Nevertheless, the traditional procedure to develop drug would to some extent block the development of andrographolide derivatives due to long research circle, high-cost and poor pharmacokinetics characters.
Along with the development of computer technique and extension of pharmaceutical databases, computer aided drug design (CADD) has earned re-interesting because of high efficiency, low-cost and extensive application. CADD is frequently utilized to assist the development of drug and there have been lots of drugs designed by CADD in the market. In this context, CADD would significantly contribute to the development of andrographolide derivatives as a-glucosidase inhibitors.
Objective:
QSAR information will greatly promote the development of andrographolide derivatives, but there is not enough data about this at present. Hence, this research would build the 2D and 3D-QSAR model of andrographolide derivatives as a-glucosidase inhibitors. These models could be utilized to investigate the important fragments and distribution of different force fields which are closely related to the inhibitory activity. Moreover, the potential active sites and key residues were obtained by homology modeling and docking. Information about the active sites and key residues should greatly contribute to the discovery of new a-glucosidase inhibitors.
Pharmacokinetic characteristics of candidates, especially the action of crossing human intestinal membrane and blood brain barrier, are the necessary aspect for developing new drug. In the light of the close relationship between compounds' structure and their pharmacokinetic characters, this research built the human intestinal absorption (HIA) prediction system and blood brain barrier (BBB) prediction system to predict the pharmacokinetic features of andrographolide derivatives by using CADD and specific cells'model.
Method:
1 QSAR studies on andrographolide derivatives as a-glucosidase inhibitors
(1) HQSAR was used to build the 2D-QSAR of andrographolide derivatives as a-glucosidase inhibitors and 3D-QSAR models were constructed by both CoMFA and CoMSIA methods. The best QSAR model was used to predict the inhibitory activity of Al-1 which was a new andrographolide derivative.
(2) Lineweaver-Burk method was utilized to judge the enzyme reaction style of andrographolide derivatives inhibiting a-glucosidase. And then, the potential active sites and key residues were explored by homology modeling and docking method.
2 The establishment of systems to predict andrographolide derivatives' action of crossing human intestinal membrane and blood brain barrier.
(1) Volsurf was employed to construct virtual HIA model, which was applied to predict the HIA values of andrographolide derivatives.
(2) Volsurf was used to establish virtual BBB model, which was applied to predict the andrographolide derivatives' possibillities to across the BBB.
Results:
1 QSAR studies on andrographolide derivatives as a-glucosidase inhibitors
(1) The 2D-QSAR model was successfully built and the result was supported by cross-validation coefficient (0.730), correlation coefficient (0.945), standard error (0.104) and slope (1.01); the best 3D-QSAR model was validated by cross-validation coefficient (0.794), correlation coefficient (0.941), slope (0.933) and standard error (0.104).
(2) The homology model of a-glucosidase was validated by RMSD (1.745 A) of structural alignment. The predicted strong inhibitors'ARs of the two potential active sites were 88.9% and 77.8% respectively.
2 The establishment of systems to predict andrographolide derivatives' action of crossing human intestinal membrane and blood brain barrier.
(1) The virtual HIA model was verified by cross-validation coefficient (0.72), correlation coefficient (0.932) and slope (0.938).
(2) The virtual BBB model was confirmed by cross-validation coefficient (0.64), accuracy rate of test set (78%).
Conclusion:
(1) The 2D-QSAR model exhibited the important fragments of andrographolide derivatives, which were closely related to bio-activity; the 3D-QSAR model could exhibit the distribution of different force fields, which is closely related to bio-activity. Combining 2D and 3D-QSAR model, the information from QSAR models would be more comprehensive and precise.
(2) The homology model ofα-glucosidase could be used to explore the potential active sites and key residues. And the two potential active sites had great recognition to andrographolide derivatives with strong inhibitory activities toα-glucosidase.
(3) The virtual HIA model would contribute to the prediction of the pharmacokinetic characteristics of andrographolide derivatives asα-glucosidase inhibitors.
(4) The virtual BBB model would contribute to the prediction of the pharmacokinetic characteristics of andrographolide derivatives as a-glucosidase inhibitors.
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