QSAR STUDIES BY LIPOSOME ELECTROKINETIC CHROMATOGRAPHY

脂质体电动色谱的 QSAR 研究

• 批准号: 6385692
• 负责人: MORTEZA G KHALEDI
• 金额: $ 15.39万
• 依托单位: NORTH CAROLINA STATE UNIVERSITY RALEIGH
• 依托单位国家: 美国
• 财政年份: 1989
• 资助国家: 美国
• 起止时间: 1989-04-01 至 2003-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6385692
• 关键词: analytical chemistry; aniline; benzoates; beta antiadrenergic agent; chemical models; chemical structure function; computer simulation; corticosteroids; hydropathy; intermolecular interaction; liposomes; liquid chromatography; micelles; penicillins; phenols; phenylacetates; phenylamide; physical chemical interaction; sulfonamides; thermodynamics

A primary goal of this project is to investigate the usefulness of Micellar Electrokinetic Capillary Chromatography (MECC) and Micellar Liquid Chromatography (MLC) for prediction of bioactivity through Quantitative Retention -Activity Relationships (QRAR) and for quantitation of lipophilic character of molecules. The development of quantitative relationships between chemical structural properties and biological activity has had a tremendous impact in the fields of drug design, toxicology, and environmental monitoring. Our aim is to achieve a better understanding of the common underlying molecular interactions that influence retention in MECC and MLC and cause biological activity, partitioning into biomembranes, or binding to proteins. These goals will be realized through parallel studies of correlating MECC / MLC retention, octanol-water partition coefficient, proteins binding, and liposomes partitioning to the Solvatochromic Parameters of solutes through Linear Solvation Energy Relationships (LSER). In order to! fully explore the multidimensional nature of these problems, we will investigate the usefulness of the factor - based, multivariate analysis chemometric techniques such as principal component regression and partial least square in QRAR modeling. This research should lead to the development of unique methodologies for characterization of physicochemical properties of biomolecules. The combination of biomimicry of micellar aggregates due to their amphiphilic and organized nature, the enormous capabilities of MECC and MLC techniques in physicochemical analysis, their flexibility and versatility for incorporation of different types of interactions, and the computional power of the mutivariate analysis techniques for treatment of a large set of data in a multidimensional space should provide exciting opportunities in structure - activity modeling. Another major goal is to explore the enormous capabilities of these two micellar mediated techniques for solving complex bioseparation problems. We will take advantage of the predictive power of the quantitatve models that have been developed in our laboratory, and will extend the range of these models in order to achieve a better understanding of migration behavior of a variety of small biomolecules in MECC and MLC. This will include systematic studies of the chromatographic parameters that influence separation of solutes of general interest in bioanalysis, specifically pharmaceutically important compounds and small peptides. We will investigate the usefulness of computer assisted modeling and, simulation in developing rapid and effective methods for optimization of MECC and MLC separations.

该项目的主要目标是研究 胶束电动毛细管色谱 (MECC) 和胶束 液相色谱 (MLC) 通过以下方式预测生物活性 定量保留-活性关系 (QRAR) 和定量 分子的亲脂特性。量化的发展 化学结构性质与生物学特性之间的关系 活动对药物设计领域产生了巨大影响， 毒理学和环境监测。 我们的目标是更好地理解共同的基础 影响 MECC 和 MLC 保留并导致 生物活性，分配到生物膜中，或结合 蛋白质。这些目标将通过平行研究来实现 关联 MECC / MLC 保留、辛醇-水分配系数、 蛋白质结合和脂质体分配至溶剂化显色剂 通过线性溶剂化能关系的溶质参数 （LSER）。为了！充分探索这些事物的多维本质 问题，我们将研究基于因素的有用性， 多变量分析化学计量技术，例如主成分 QRAR 建模中的回归和偏最小二乘。 这项研究应该会导致开发独特的方法 生物分子的物理化学性质的表征。这 由于其两亲性，胶束聚集体的仿生学组合 和组织性，MECC 和 MLC 技术的巨大能力 在物理化学分析中，它们的灵活性和多功能性 结合不同类型的交互和计算 多变量分析技术处理大量数据的能力 多维空间中的数据应该提供令人兴奋的机会 在结构-活动建模中。 另一个主要目标是探索这两者的巨大能力 用于解决复杂生物分离问题的胶束介导技术。 我们将利用定量模型的预测能力 我们实验室开发的，并将扩展范围 这些模型是为了更好地理解迁移 MECC 和 MLC 中各种小生物分子的行为。这将 包括对色谱参数的系统研究 影响生物分析中普遍关注的溶质的分离， 特别是药学上重要的化合物和小肽。我们 将研究计算机辅助建模的有用性，并且， 模拟开发快速有效的方法来优化 MECC 和 MLC 分离。