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: 8602837
• 负责人: Kaushal Rege
• 金额: $ 30.73万
• 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/8602837
• 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; 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; prostate cancer cell; public health relevance; screening; 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.

描述（由申请人提供）：拟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形式的建模，以设计和评估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应用中具有吸引力。目前可用的非病毒（例如聚合物）基因递送载体受毒性的限制，并且患有低效率。我们假设，单体和联合聚合物合成的合理化学化学合成合成的协同组合将导致具有高效的快速鉴定聚合物，以将基因输送到细胞（特定AIM 1）。转染数据的快速生成将促进预测定量结构活性关系（QSAR）化学形式模型，这些模型将基因递送疗效与聚合物和多种物理化学特性（例如，使用支持载体机器（SVM）的分子量，疏水性，ZETA电位等）相关联（例如，分子量，疏水性，ZETA势能等）和特定目的（Kernel-prssife）（K-kernel-Pressials（kernel-prssectial）（kernel Alige）。将开发一种新型的QSAR“模型模型”方法，其中首先使用基于单体结构的预测QSAR模型来估算聚合物物理化学特性。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模型将有助于高效能聚合物转染剂的合理设计，这是非病毒基因递送的强大方法。认识到聚合物介导的转基因表达受到低效率的影响，我们将使用细胞内运输和转录的介体（化学治疗增强剂）采用组合治疗方法，旨在增强细胞中的转基因表达（特定目标3）。最后，将采用有效的聚合物以及化学治疗增强剂以及在体外和体内有选择地诱导癌细胞中凋亡的基因（特定的目标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（1）鉴定（1）新的非病毒基因递送的有效聚合物，（2）对影响转基因递送的聚合物物理化学因素的见解，（3）预测QSAR模型，这些模型将促进高压式的“在硅基验证中”的硅基识别和（4）在Vivo incive和（4）In vivo的识别中。预计这项研究将显着影响基于基因的治疗剂，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递送的新型非病毒（聚合物）材料，并在体外和体内评估它们。这些将在基因治疗中发现多种疾病中的大量应用，并将在这些情况下扩大治疗选择。