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Conceptual Prediction of Drug Bioactivities in Cell-Based Assays: cell-QSAR

基于细胞的检测中药物生物活性的概念预测：cell-QSAR

基本信息

批准号：
8536830
负责人：
STEFAN BALAZ
金额：
$ 25.49万
依托单位：
ALBANY COLLEGE OF PHARMACY
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-09-01 至 2016-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8536830
关键词：
3-Dimensional Accounting Affinity Amaze Bacteria Binding Biological Assay Calibration Cell Line Cell model Cell physiology Cells Cellular Assay Characteristics Classification Computer software Cytochrome P450 Data Databases Descriptor Development Diacetyl Drug Interactions Drug Receptors Drug Transport Drug usage Equation Exhibits Fatty Acids Hour Human Human Cell Line Individual Kinetics Lead Lecithin Libraries Ligands Lipids Liposomes Liquid substance Mammals Measures Membrane Proteins Metabolic Metabolism Modeling Molecular Conformation Molecular Models Molecular Structure Online Systems Output Pharmaceutical Preparations Phospholipids Plant Roots Process Property Protein Binding Proteins PubChem Publications Publishing Quantitative Structure-Activity Relationship Reaction Receptor Cell Research Role Scientist Services Solvents Structure System Systems Biology Techniques Terminology Therapeutic Effect Time Water base carrier mediated transport cell type computerized tools design drug candidate drug development drug structure efflux pump experience hexadecane macromolecule molecular modeling neglect novel passive transport prevent programs public health relevance receptor receptor binding research study response screening uptake virtual web services

项目摘要

DESCRIPTION (provided by applicant): Cell-based screening has been used in drug development, if the receptors are either not known, isolable, or functional upon isolation; or if cell-level responses are sought. Unresolved contributions of the drug disposition and receptor binding to the measured effects hamper lead structure optimization. Valuable ligands pass unnoticed through cellular assays, if slow transport and/or interactions with non-receptor cell constituents prevent the attainment of the effective drug concentration in the receptor surroundings. To account for the factors complicating the interpretation of cellular data, we will develop a structure-based computational tool, called the disposition function (DF), estimating the kinetics of intracellular drug disposition. To make the DF as general and practical as possible, conformation-averaged interactions during passive transport will be described using drug properties measured in surrogate systems, and conformation-specific binding to macromolecules will be expressed via 3-dimensional quantitative structure-activity relationships (3D-QSAR). Accumulation in phospholipid bilayers, composed of more than 50% phosphatidylcholine (PC) in mammals, comprises two distinct types of solvation - in the core and in the headgroup region. While hexadecane (C16) is a good surrogate solvent for the core, drug solvation in the headgroup regions, occupying about a third of the bilayer volume, is not understood properly. A novel surrogate solvent, diacetyl-PC (DAcPC, i.e. the PC headgroup with the truncated fatty acid chains), hydrated to the extent typical for a fluid bilayer, will be used to measure the headgroup-like solvation energies of hundreds of drugs. For all common drug fragments, the DAcPC and C16 solvation energies will be deconvoluted into fragment contributions, and adjusted to express the experimental headgroup and core quantities using conceptual correlations with the bilayer data. We hypothesize that for the maximum trans-bilayer transport rates, drugs must exhibit intermediate interaction affinities for the headgroups, core, and the interface between them. Based on this hypothesis, experimental transport kinetics data will be conceptually correlated with the headgroup and core solvation energies, to obtain a baseline form of the DF that estimates drug disposition for cellular systems, using just the lipid and protein contents. The baseline DF will be refined for representative G+ and G- bacteria, and two human cell lines using the uptake data and conceptual 3D-QSAR for conformation-specific binding to inert proteins. The DFs will be combined with current ligand-based and receptor-based QSAR techniques, developed for isolated receptor data, to provide cell-QSAR models suitable for processing cell-level bioactivities. The calibrated cell-QSAR models can be utilized by others as software or a web service to extract receptor affinities from cell-assay data, optimize drug structures individually for disposition and receptor binding, convert good binders to promising drug candidates, describe drug disposition in systems biology models, and annotate drug structures in PubChem and other databases by the estimates of accumulation in bilayer regions and intracellular disposition. PUBLIC HEALTH RELEVANCE: For many drugs, transport into the cells is one of the key processes for the therapeutic effect. The planned research will find out, how the rate and extent of the cellular entry depend on molecular structure and physicochemical properties of drug candidates. This information will be used do create software and a web service that will help other scientists to develop better and safer drugs faster.

描述(申请人提供)：基于细胞的筛选已经用于药物开发，如果受体在分离后未知、可分离或起作用；或者如果寻求细胞水平的反应。药物处置和受体结合对测量效应的未解决的贡献阻碍了铅结构的优化。如果缓慢的转运和/或与非受体细胞成分的相互作用阻碍了受体周围的有效药物浓度的获得，有价值的配体通过细胞检测而不被注意到。为了解释复杂的细胞数据的因素，我们将开发一个基于结构的计算工具，称为处置函数(DF)，估计细胞内药物处置的动力学。为了使DF尽可能通用和实用，被动转运过程中的构象平均相互作用将使用在替代系统中测量的药物性质来描述，与大分子的构象特异性结合将通过三维定量结构-活性关系(3D-QSAR)来表达。在哺乳动物体内，超过50%的磷脂酰胆碱(PC)组成的磷脂双层中的积累包括两种不同类型的溶剂化-在核心区域和在头部区域。虽然十六烷(C16)是核心的很好的替代溶剂，但占据双分子层体积约三分之一的头基区的药物溶剂化没有得到正确的理解。一种新的替代溶剂，双乙酰-PC(DAcPC，即带有截短脂肪酸链的PC头基)，其水化程度达到了流体双层的典型程度，将被用来测量数百种药物的头基状溶剂化能。对于所有常见的药物片断，DAcPC和C16的溶剂化能将被解卷积成片断的贡献，并利用与双层数据的概念关联来调整以表示实验头基和核心量。我们假设，对于最大的跨双层转运速率，药物必须表现出头基、核心以及它们之间的界面的中间相互作用亲和力。基于这一假设，实验传输动力学数据将在概念上与头基和核心溶剂化能相关联，以获得仅使用脂肪和蛋白质含量来估计细胞系统药物处置的DF的基线形式。利用摄取数据和构象特异性结合惰性蛋白质的概念3D-QSAR，将精炼具有代表性的G+和G-细菌以及两个人类细胞系的基线DF。DFS将与目前基于配体和基于受体的QSAR技术相结合，这些技术是为分离的受体数据开发的，以提供适合处理细胞水平生物活性的细胞-QSAR模型。校准的细胞-QSAR模型可以被其他人用作软件或网络服务，以从细胞分析数据中提取受体亲和力，针对处置和受体结合单独优化药物结构，将良好的结合剂转化为有希望的候选药物，在系统生物学模型中描述药物处置，并通过双分子层区域累积和细胞内处置的估计来注释PubChem和其他数据库中的药物结构。与公共健康相关：对于许多药物来说，进入细胞的转运是治疗效果的关键过程之一。计划中的研究将找出，细胞进入的速度和程度如何取决于候选药物的分子结构和物理化学性质。这些信息将被用来创建软件和网络服务，帮助其他科学家更快地开发更好、更安全的药物。