Engineering DNA Delivery Polymers using Combinatorial and Cheminformatics Methods

使用组合和化学信息学方法设计 DNA 递送聚合物

• 批准号: 8212217
• 负责人: Kaushal Rege
• 金额: $ 28.89万
• 依托单位: ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-01-12 至 2015-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8212217
• 关键词: Affinity; Amines; Aminoglycosides; Apoptosis; Biocompatible; Biodistribution; Cells; Combinatorial Synthesis; Complex; Computer Simulation; DNA delivery; Data; Disease; Engineering; Enhancers; Ethers; Evaluation; Future; Gene Delivery; Gene Expression; Gene Transduction Agent; Generations; Genes; Genetic Transcription; Goals; Histones; Human; Hydrophobicity; In Vitro; Lead; Learning; Least-Squares Analysis; Libraries; Luciferases; Machine Learning; Malignant - descriptor; Malignant neoplasm of prostate; Mediating; Mediator of activation protein; Methods; Modeling; Molecular Weight; Mus; Neoplasm Metastasis; Non-Viral Vector; Phenotype; Plasmids; Polyamines; Polymers; Property; Prostatic Neoplasms; Proteins; Quantitative Structure-Activity Relationship; Relative (related person); Research; SCID Mice; Screening procedure; Structure; TNFSF10 gene; Techniques; Testing; Therapeutic; Toxic effect; Training; Transfection; Transgenes; Validation; Viral Vector; Xenograft Model; base; biomaterial compatibility; bone; cancer cell; cheminformatics; combinatorial; combinatorial chemistry; design; functional genomics; gene therapy; in vivo; inhibitor/antagonist; insight; luminescence; milligram; model design; monomer; multitask; nanoparticle; non-viral gene delivery; novel; public health relevance; small molecule; trafficking; transgene expression; vector; zeta potential

DESCRIPTION (provided by applicant): The overall goal of the proposed research is to employ chemoenzymatic monomer synthesis, parallel polymer synthesis and cheminformatic modeling for the design and evaluation of polymers for transgene delivery. Gene-based strategies, designed to manipulate cellular phenotype by introducing exogenous genes, are attractive in therapeutic and functional genomics applications. Currently available non-viral (e.g. polymeric) gene delivery vectors are limited by toxicities and suffer from low efficacies. We hypothesize that a synergistic combination of rational chemoenzymatic synthesis of monomers and combinatorial polymer synthesis will lead to the rapid identification polymers with high efficacies for delivering genes to cells (Specific Aim 1). The rapid generation of transfection data will facilitate the construction of predictive Quantitative Structure-Activity Relationship (QSAR) cheminformatic models that correlate gene delivery efficacy with polymer and polyplex physicochemical properties (e.g. molecular weight, hydrophobicity, zeta potential, etc.) using Support Vector Machine (SVM) and Kernel-Partial Least Squares (K-PLS) regression (Specific Aim 2). A novel QSAR 'model- of models' approach will be developed in which, polymer physicochemical properties will first be estimated using predictive QSAR models based on monomer structure. QSAR models for transgene expression will then be generated using these estimated properties as a result of which, predictions of transgene expression efficacy will be based directly on monomer structures. In the long-term, such predictive QSAR models will aid in the rational design of high-efficacy polymeric transfection agents, which a powerful approach for non-viral gene delivery. Recognizing that polymer-mediated transgene expression suffers from low efficacies, we will employ a combination treatment approach using mediators of intracellular trafficking and transcription (chemotherapeutic enhancers), designed to enhance transgene expression in cells (Specific Aim 3). Finally, effective polymers along with chemotherapeutic enhancers will be employed for delivering genes that encode TRAIL, which selectively induces apoptosis in cancer cells, both in vitro and in vivo (Specific Aim 4). SCID mouse xenograft models will be employed to investigate recession of 22Rv1 prostate tumors, and biodistribution and toxicity of the polymer-plasmid complexes will be investigated. It is anticipated that the proposed research will result in the identification of (1) new effective polymers for non-viral gene delivery, (2) insights into polymer physicochemical factors that influence transgene delivery, (3) predictive QSAR models that will facilitate high-throughput 'in silico' identification of effective polymers, and (4) in vivo efficacy and biodistribution evaluation of polymer-based delivery. It is anticipated that this research will significantly impact gene-based therapeutics, functional genomics, and various applications that depend on high levels of transgene expression in cells. The proposed research will develop novel non-viral (polymeric) materials for gene delivery and evaluate them in vitro and in vivo. These will find significant application in gene therapy for a number of diseases and will expand therapeutic options in these cases. PUBLIC HEALTH RELEVANCE: This proposed research describes the engineering of novel polymers using combinatorial syntheses and cheminformatic modeling for enhanced transgene expression in cells. The efficacy and biocompatibility (toxicity) of polymers and combination treatments will be evaluated in vitro and in vivo (in mice).

描述（由申请人提供）：所提议研究的总体目标是采用化学酶单体合成、平行聚合物合成和化学信息学建模来设计和评估用于转基因递送的聚合物。基于基因的策略旨在通过引入外源基因来操纵细胞表型，在治疗和功能基因组学应用中很有吸引力。目前可用的非病毒（例如聚合）基因递送载体受到毒性的限制并且功效较低。我们假设单体的合理化学酶合成和组合聚合物合成的协同组合将导致快速识别具有高效向细胞递送基因的聚合物（具体目标1）。转染数据的快速生成将有助于构建预测定量构效关系 (QSAR) 化学信息学模型，该模型使用支持向量机将基因传递功效与聚合物和复合物理化特性​​（例如分子量、疏水性、zeta 电位等）关联起来(SVM) 和核偏最小二乘法 (K-PLS) 回归（具体目标 2）。将开发一种新颖的 QSAR“模型的模型”方法，其中首先使用基于单体结构的预测 QSAR 模型来估计聚合物的物理化学性质。然后将使用这些估计的特性生成转基因表达的 QSAR 模型，因此，转基因表达功效的预测将直接基于单体结构。从长远来看，这种预测性 QSAR 模型将有助于合理设计高效聚合转染剂，这是非病毒基因传递的有力方法。认识到聚合物介导的转基因表达效率较低，我们将采用一种联合治疗方法，使用细胞内运输和转录介质（化疗增强剂），旨在增强细胞中的转基因表达（具体目标 3）。最后，有效的聚合物和化疗增强剂将用于传递编码 TRAIL 的基因，该基因在体外和体内选择性诱导癌细胞凋亡（具体目标 4）。 SCID小鼠异种移植模型将用于研究22Rv1前列腺肿瘤的衰退，并将研究聚合物-质粒复合物的生物分布和毒性。预计拟议的研究将导致识别（1）用于非病毒基因传递的新的有效聚合物，（2）深入了解影响转基因传递的聚合物理化因素，（3）预测QSAR模型，这将促进高有效聚合物的“计算机”通量鉴定，以及（4）基于聚合物的递送的体内功效和生物分布评估。预计这项研究将显着影响基于基因的治疗、功能基因组学以及依赖于细胞中高水平转基因表达的各种应用。拟议的研究将开发用于基因传递的新型非病毒（聚合）材料，并对其进行体外和体内评估。这些将在许多疾病的基因治疗中得到重要应用，并将扩大这些病例的治疗选择。 公共健康相关性：这项拟议的研究描述了使用组合合成和化学信息学模型来设计新型聚合物，以增强细胞中的转基因表达。聚合物和联合治疗的功效和生物相容性（毒性）将在体外和体内（小鼠体内）进行评估。