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CCR5 receptor antagonists modeling and support vector regression in QSARs.

机译：CSAR5受体拮抗剂在QSAR中建模和支持向量回归。

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摘要

In the first section of this dissertation, Quantitative Structure-Retention Relationship (QSAR) and Quantitative Structure-Property Relationship (QSPR) models are developed to predict Caco-2 permeability of drugs and protein retention times in anion-exchange chromatography systems. The physicochemical, topological, subdivided surface area, and Transferable Atom Equivalent (TAE) electron-density-based descriptors are computed directly from molecular structural geometries. A novel algorithm based on Support Vector Machine (SVM) regression was employed to obtain mathematical prediction models. A visualization scheme was also used to display the relative importance of each selected descriptor in the final models. Once these predictive models are validated, they can be used as an automated prediction tool for virtual high-throughput screening (VHTS).; Recently, the CCR5 chemokine receptor has been found to play a crucial role in the viral entry stage of HIV infection. This discovery has motivated intensive efforts for the development of small molecule CCR5 antagonists as a new class of anti-HIV therapeutics. In the second section of this dissertation, both ligand-based and structure-based approaches were performed to model the interaction between the CCR5 receptor and its small molecular antagonists at the atomic level. The initial three-dimensional (3D) structure of the CCR5 receptor was constructed using a homology modeling approach. Subsequently, recently published CCR5 piperidine-based antagonists were docked into potential binding site of the CCR5 receptor and the resulting complexes were refined by means of classical molecular dynamics (MD) simulation in a lipid bilayer environment. The binding modes between the receptor and antagonists were analyzed. In addition, 3D-QSAR, Comparative Molecular Field Analysis (CoMFA) and Comparative Similarity Indices Analysis (CoMSIA) studies were conducted on a series of piperidine-based CCR5 antagonists. Such computer-aided techniques were used to provide insight into the physicochemical factors crucial for CCR5 receptor-antagonist binding, which could in turn be used to guide the rational design of potential new anti-viral drugs. This procedure is also applicable to other GPCRs protein targets.
机译：在本文的第一部分，建立了定量结构-保留关系（QSAR）和定量结构-性质关系（QSPR）模型，以预测药物在阴离子交换色谱系统中的Caco-2渗透性和蛋白质保留时间。物理化学，拓扑，细分表面积和可转移原子当量（TAE）基于电子密度的描述子是直接从分子结构几何中计算出来的。基于支持向量机（SVM）回归的新算法被用来获得数学预测模型。可视化方案还用于显示最终模型中每个选定描述符的相对重要性。这些预测模型通过验证后，就可以用作虚拟高通量筛选（VHTS）的自动化预测工具。最近，已经发现CCR5趋化因子受体在HIV感染的病毒进入阶段起关键作用。这一发现促使人们为开发小分子CCR5拮抗剂作为一类新型的抗HIV治疗药物付出了巨大的努力。在本文的第二部分中，基于配体和基于结构的方法都在原子水平上模拟了CCR5受体与其小分子拮抗剂之间的相互作用。使用同源建模方法构建了CCR5受体的初始三维（3D）结构。随后，将最近发表的基于CCR5哌啶的拮抗剂对接至CCR5受体的潜在结合位点，并通过脂质双层环境中的经典分子动力学（MD）模拟精制所得复合物。分析了受体和拮抗剂之间的结合方式。此外，对一系列基于哌啶的CCR5拮抗剂进行了3D-QSAR，比较分子场分析（CoMFA）和比较相似性指标分析（CoMSIA）研究。此类计算机辅助技术可用于洞察对于CCR5受体-拮抗剂结合至关重要的物理化学因素，进而可用于指导潜在的新抗病毒药物的合理设计。此过程也适用于其他GPCR蛋白靶标。

著录项

  • 作者

    Song, Minghu.;

  • 作者单位

    Rensselaer Polytechnic Institute.;

  • 授予单位 Rensselaer Polytechnic Institute.;
  • 学科 Chemistry Organic.
  • 学位 Ph.D.
  • 年度 2004
  • 页码 125 p.
  • 总页数 125
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 有机化学;
  • 关键词

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