Computationally-Inspired Design of Non-Viral Gene Delivery Vehicles for mRNA-Based Cystic Fibrosis Therapies

用于基于 mRNA 的囊性纤维化治疗的非病毒基因传递载体的计算启发设计

基本信息

批准号：
10760605
负责人：
Shashi Murthy
金额：
$ 30万
依托单位：
NANITE INC.
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-08-10 至 2024-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10760605
关键词：
Address Affect Binding Biotechnology Breathing Businesses Cell Line Cell membrane Cells Chemicals Complex Computational Biology Cystic Fibrosis Cystic Fibrosis Transmembrane Conductance Regulator Development Diagnosis Disease Drug Delivery Systems Electrolytes Encapsulated Environment Epithelial Cells Epithelium Foundations Gene Delivery Genetic Diseases Glycopeptides Human Immune Immune Evasion Immunologics Impairment In Vitro Infection Investigation Lectin Letters Libraries Life Liquid substance Lung Machine Learning Macrophage Mechanics Messenger RNA Methodology Methods Modality Modeling Mucous Membrane Mucous body substance Mutation Nucleic Acids Pathogenicity Patients Penetration Peptides Performance Persons Phase Polymers Polysaccharides Process Production Prognosis Pulmonary Cystic Fibrosis Pulmonary Pathology Regulator Genes Respiratory Failure Sodium Channel Specificity Structure System Therapeutic Agents Toxic effect Universities Viral Vector airway obstruction autosome bronchial epithelium chronic infection delivery vehicle design expectation functional group gene therapy imaging modality immunogenicity improved innovation lipid nanoparticle mRNA delivery manufacture mucus clearance non-viral gene delivery novel strategies novel therapeutics nucleic acid-based therapeutics patient population recessive genetic trait respiratory virus screening small molecule survival outcome uptake virtual

项目摘要

PROJECT SUMMARY Cystic fibrosis (CF) is a debilitating and life-shortening disease affecting more than 70,000 people worldwide, with ~1,000 new cases expected to be diagnosed every year. This disease is an autosomal recessive genetic disorder associated with mutations in the CF transmembrane conductance regulator (CFTR). These mutations impairs the ionic transport across the cell membrane. In the pulmonary epithelium, this impairment results in an overproduction and accumulation of mucus, leading to airway obstructions and leaving patients vulnerable to persistent pathogenic infections and severe respiratory failure. In recent years, treatment of CF with small molecule therapies has been very impactful, however not all patients can be treated with these commercially available therapies. More recently, advances in gene therapy enable new approaches to the greatment of CF, such as target the underlying cause of CF lung pathology, and even restore or replace the CFTR gene, with expectations of improved prognosis and survival outcomes. However, these therapies are typically large, complex molecules, such as mRNA, which require specialized delivery systems. Viral vectors and lipid nanoparticles represent the current state of the art in gene delivery, however these methods are limited by immunogenicity, complex manufacturing, and most crucially, limited ability to traverse the mucus layerThe three principal obstacles of CF localized delivery are the need to (i) overcome entrapment within the mucosal barrier, (ii) avoiding recognition and disruption by immune cells such as lung macrophages, and finally, (iii) effective intracellular entry. We propose to leverage computational optimization and structure-dynamics modeling to design polymer-based delivery vehicles for mRNA payloads to overcome these obstacles. This project brings together Nanite’s advanced capabilities in high throughput polymer synthesis and machine learning together with design of glycopeptides using first-principles computational biology approaches pioneered by Dr. Srirupa Chakraborty at Northeastern University. The availability of effective delivery vehicles across virtually all modes of gene therapies across all indications is a well-recognized commercial need. Nanite’s approach is to address this need by covering the broadest possible design space using a combination of computational design, high throughput synthesis and screening, and machine learning-based optimization. Successful completion of this Phase I project will enable us to extend this approach to CF.

项目概要囊性纤维化 (CF) 是一种使人衰弱、缩短寿命的疾病，影响着全世界 70,000 多人，预计每年约有 1,000 例新病例被诊断出来。这种疾病是一种常染色体隐性遗传病。与 CF 跨膜电导调节因子 (CFTR) 突变相关的疾病。损害肺上皮细胞膜上的离子运输，这种损害会导致粘液过度产生和积聚，导致气道阻塞，使患者变得脆弱近年来CF治疗以持续性病原感染和严重呼吸衰竭为主。分子疗法非常有影响力，但并非所有患者都能接受商业化治疗最近，基因治疗的进步为治疗 CF 提供了新的方法，例如针对 CF 肺部病理的根本原因，甚至恢复或替换 CFTR 基因，改善预后和生存结果的期望然而，这些疗法通常规模较大，复杂的分子，例如 mRNA，需要专门的病毒载体和脂质。纳米颗粒代表了基因传递领域的最新技术，但是这些方法受到以下限制：免疫原性、制造复杂，最重要的是，穿过粘液层的能力有限 CF 局部递送的三个主要障碍是需要 (i) 克服粘膜内的截留屏障，(ii) 避免被肺巨噬细胞等免疫细胞识别和破坏，最后，(iii) 我们建议利用计算优化和结构动力学。建模以设计基于聚合物的 mRNA 有效负载递送载体，以克服这些障碍。项目汇集了 Nanite 在高通量聚合物合成和机器方面的先进能力使用第一原理计算生物学方法一起学习和设计糖肽由东北大学 Srirupa Chakraborty 博士首创有效的运载工具的可用性。涵盖几乎所有适应症的基因治疗模式是公认的商业需求。 Nanite 的方法是通过使用组合覆盖尽可能广泛的设计空间来满足这一需求计算设计、高通量合成和筛选以及基于机器学习的优化。第一阶段项目的成功完成将使我们能够将这种方法扩展到CF。