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Thesis Advisor周家驹
Degree Grantor中国科学院研究生院
Abstract本论文重点对建立受体模型方法的方法进行了研究,在前人的工作基础上,改进并独立建立了两种受体模型方法。一种是建立基于虚拟受体作用位点模型的PARM算法。PARM算法中,定义了15种虚拟受体原子类型,利用遗传算法来建立原子水平的受体模型,并计算配体分子和受体模型之间的相互作用能,建立了生物活性和相互作用能之间的QSAR回归方程。另一种是基于点表面的虚拟受体表面模型Recepsurf。Recepsurf算法根据训练集分子中的高活性分子建立封闭的或开放的受体表面模型。训练集分子可以在受体模型中进行分子力学优化计算,并计算优化构象与受体模型之间的相互作用能,进而建立QSAR方程。同时,Recepsurf还能近似计算受体表面性质的分布,并实现受体表面及其表面性质的可视化表达。另一方面,还开展了钾离子通道开放剂(KCO)体系和ALS酶抑制剂体系的QSAR研究,建立了KCO分子的药效团模型并推测了ALS酶抑制剂与受体的可能的空间结合模式。我们还结合虚拟现实模型化语言(VRML)和ISAPI(Internet Server Application Program Interface)技术开发了基于Web的分子三维立体显示模块。
Other AbstractIn practical drug discovery, it is common to do molecular design under the condition that the three dimensional structure of target protein is unknown. The focus of this dissertation is concentrated in the methodology of building the receptor model, while the receptor protein structure is unavailable. Following other scientists' research work, two algorithms to build receptor model have been improved and put forward. A PARM(Pseudo Atomic Receptor Model) algorithm which can be used to build receptor model on atomic level was put forward. In the PARM, a knowledge-based genetic algorithm was utilized to build atomic receptor model. The interaction energy between receptor model and ligand was computed. To every model, the QSAR regression equation between bioactivity and interaction energy was established. On the other hand, Recepsurf, an algorithm which can be used to construct pseudo receptor surface model by using point surface was implemented. Recepsurf build pseudo receptor surface model based on the high active molecules. The model can be closed or even open by the definition of user himself. The molecules in training set can be minimized in the receptor model by way of molecular machenics computation and the interaction energy between the minimized conformation and receptor model was obtained. In this way, the QSAR equation between bioactivity datas and the interaction energies can be established. On the other hand, the surface properties and their distributions on the receptor surface can be computed roughly and visualized. At the same time, by combining the molecular field information and the artificial neural network, a new algorithm called MFANN(Molecular Field based Artificial Neural Network) was put forward to use ANN to analyze the molecular field information. On the other hand, the QSAR studies on the KCO and ALS enzyme inhibitors were carried out. The quantitative pharmacophore model of the KCO molecules was established and the possible binding mode between inhibitor and ALS enzyme was deduced by the conformational analysis of ALS enzyme inhibitors. Besides, a Web-based molecular three-dimensional display module had been developed by combining the VRML and ISAPI (Internet Server Application Program Interface) technology.
Document Type学位论文
Recommended Citation
GB/T 7714
陈红明. 药物设计中的受体模型方法[D]. 中国科学院研究生院,1998.
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