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

• 批准号: 8137898
• 负责人: STEFAN BALAZ
• 金额: $ 26.41万
• 依托单位: ALBANY COLLEGE OF PHARMACY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8137898
• 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; Screening procedure; 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; uptake; virtual; web services

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（由申请人提供）：如果受体未知、可分离或分离后有功能，或者如果寻求细胞水平的反应，则在药物开发中使用基于细胞的筛选。未解决的贡献的药物处置和受体结合的测量效果妨碍铅结构优化。如果缓慢的转运和/或与非受体细胞成分的相互作用阻止在受体环境中达到有效药物浓度，则有价值的配体通过细胞测定时不会被注意到。为了解释细胞数据解释复杂化的因素，我们将开发一种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进行描述，并通过三维定量结构-活性关系（3D-QSAR）表示与大分子的构象特异性结合。在哺乳动物中，磷脂双层由超过50%的磷脂酰胆碱（PC）组成，其中的积累包括两种不同类型的溶剂化-在核心和头基区域。虽然十六烷（C16）是一个很好的替代溶剂的核心，药物溶剂化的头基区域，占据约三分之一的双层体积，是没有得到正确的理解。一种新的替代溶剂，二乙酰-PC（DAcPC，即PC头基与截短的脂肪酸链），水合的程度典型的流体双层，将被用来测量头基样溶剂化能的数百种药物。对于所有常见的药物片段，DAcPC和C16溶剂化能将被解卷积为片段贡献，并使用与双层数据的概念相关性进行调整以表达实验头基和核心量。我们假设，对于最大的跨双层传输速率，药物必须表现出中间的相互作用亲和力的头基，核心，它们之间的接口。基于这一假设，实验运输动力学数据将在概念上与头基和核心溶剂化能相关，以获得DF的基线形式，该DF仅使用脂质和蛋白质含量来估计细胞系统的药物处置。将使用摄取数据和概念性3D-QSAR对代表性G+和G-细菌以及两种人细胞系的基线DF进行优化，以确定与惰性蛋白质的构象特异性结合。DF将与目前的基于配体和基于受体的QSAR技术相结合，开发用于分离受体数据，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，以从细胞测定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，描述系统生物学模型中的药物处置，并通过估计双层区域中的累积和细胞内处置来注释PubChem和其他数据库中的药物结构。 公共卫生相关性：对于许多药物，转运到细胞中是治疗效果的关键过程之一。计划中的研究将发现细胞进入的速率和程度如何取决于候选药物的分子结构和理化性质。这些信息将用于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。