Digital one-disc-one-compound array for high-throughput discovery of cancer-targe

用于高通量发现癌症靶标的数字化一盘一化合物阵列

基本信息

批准号：
8721896
负责人：
Tingrui Pan
金额：
$ 22.11万
依托单位：
UNIVERSITY OF CALIFORNIA AT DAVIS
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-09-01 至 2016-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8721896
关键词：
Address Affinity Amino Acids Area Binding Biological Biological Assay Biology Biomedical Engineering Cell Surface Receptors Cells Chemicals Chemistry Code Combinatorial Synthesis Complex Coupling Data Drug Delivery Systems Equipment Exploratory/Developmental Grant Generic Drugs High-Throughput Nucleotide Sequencing Hour Integrins Isomerism Laboratories Lead Libraries Ligands Malignant Neoplasms Maps Mass Spectrum Analysis Medicine Methods Microfabrication Microfluidic Analytical Techniques Microfluidics Microscopy Molecular Nature Optics Peptide Library Process Quantitative Evaluations Reagent Research Research Proposals Resolution Signal Transduction Solutions Specificity Structural Chemistry Structure-Activity Relationship Surface Technology anticancer research cancer cell chemical reaction chemical synthesis combinatorial combinatorial chemistry cost design digital drug discovery high throughput technology in vivo innovation novel operation public health relevance receptor screening theories tool

项目摘要

DESCRIPTION (provided by applicant): The objective of the proposed research is to develop a microfluidics-guided digitally encoded combinatorial method, referred to as digital one-disc-one-compound (ODOC) array, integrating state-of-the-art combinatorial chemistry with emerging microfluidics, microfabrication, encoding and matrix theories, for discovery of cancer-targeting molecules with high throughput, high efficiency and high accuracy at low cost. As an indispensable tool for biology and medicine, combinatorial chemistry has enabled high-efficiency modular synthesis of biomolecules and high-throughput exploration of the lead compounds for specific biological targets. However, existing combinatorial strategies only allow either large-scale synthesis or chemical addressability, but not both. Moreover, high equipment cost and complex chemical processing limit their utility to laboratories only. Under the proposed research, we aim at addressing large- scale combinatorial synthesis, digital molecular identification, synthetic throughput, parallel screening, and quantitative analysis of combinatoria chemistry as a whole, by introducing batch-fabricated microdisc carriers with digital barcodes and matrix-directed combinatorial synthesis in reconfigurable microfluidic networks. Specifically, cancer integrin-targeting peptide libraries will be designed and synthesized on the digital ODOC array, followed by microfluidic quantitative screening of the cell-ligand interactions on the array Comprehensive structure-activity relationship (SAR) data obtained by quantitative cell binding of every single compound-disc facilitates design of focused libraries for rapid optimization of cancer-targeting ligands with higher specificity and affinity than those previously discovered. In brief, the proposed digital ODOC array, once developed, will provide a transformative paradigm for high-throughput high-efficiency screening, optimization, and characterization of biomolecules targeting at various types of cancer cell receptors.

DESCRIPTION (provided by applicant): The objective of the proposed research is to develop a microfluidics-guided digitally encoded combinatorial method, referred to as digital one-disc-one-compound (ODOC) array, integrating state-of-the-art combinatorial chemistry with emerging microfluidics, microfabrication, encoding and matrix theories, for discovery of cancer-targeting molecules with high throughput,高效率和高精度，低成本。作为生物学和医学必不可少的工具，组合化学已使生物分子的高效模块化合成和对特定生物学靶标的铅化合物的高通量探索。但是，现有的组合策略仅允许大规模合成或化学可寻址性，但不能两者兼而有之。此外，高设备成本和复杂的化学处理仅限于实验室。在拟议的研究下，我们旨在通过在整个化学的整体中解决大规模组合合成，数字分子鉴定，合成吞吐量，并行筛选和定量分析，并通过引入批处理的微型架子载体与数字条形码和矩阵指导的组合合成网络中的批处理微型证人载体。具体而言，将在数字ODOC阵列上设计和合成癌症整合靶向肽库，然后在数字ODOC阵列上设计和合成，然后在阵列的全面结构活性关系（SAR）数据（SAR）数据上进行细胞 - 配体相互作用的微流体定量筛选。以前发现。简而言之，拟议的数字ODOC阵列曾经开发，将为靶向各种类型的癌细胞受体的生物分子的高效率筛选，优化和表征提供变革性范式。