摘要
Nucleic acid-based therapies have shown enormous effectiveness as vaccines against the recent COVID19 pandemics and hold great promises in the fight of a broad spectrum of diseases ranging from viral infections to cancer up to genetically transmitted pathologies. Due to their highly degradable polyanionic nature, nucleic acids need to be packed in sophisticate delivery vehicles which compact them up, protect them from early degradation and help delivery them to the right tissue/cells. Lipid-based nanoparticles (LNP) represent, at present, the main solution for nucleic acid delivery. They are made of a mixture of lipids whose key ingredient is an ionizable cationic lipid. Indeed, the interactions between the polyanionic nucleic acids and the ionizable cationic lipids, and their pH-dependent regulation in the life cycle of the nanoparticle, from production to cargo delivery, mostly determine the effectiveness of the therapeutic approach. Notwithstanding the large improvements in the delivery efficiency of LNPs in the last two decades, it is estimated that only a small fraction of the cargo is actually delivered, stimulating further research for the design of more effective LNP formulations. A rationally driven design would profit from the knowledge of the precise molecular structure of these materials, which is however still either missing or characterized by poor spatial resolution. Computational approaches have often been used as a molecular microscope either to enrich the available experimental data and provide a molecular-level picture of the LNPs or even simulate specific processes involving the formation and/or the molecular mechanisms of action of the LNP. Here, I review the recent literature in the field.
摘要译文
基于核酸的疗法表现出对最近的Covid19大流行病的疫苗的巨大有效性，并在从病毒感染到癌症再到遗传性传播病理的广泛疾病的战斗中拥有巨大的承诺。由于其高度降解的聚苯故性质，需要将核酸包装在柔软的递送车辆中，以压缩它们，保护它们免受早期降解，并帮助将它们递送到正确的组织/细胞中。目前，基于脂质的纳米颗粒（LNP）代表了核酸递送的主要解决方案。它们由脂质的混合物制成，其关键成分是可离子的阳离子脂质。实际上，从生产到货物递送，聚苯基核酸与可离子阳离子脂质之间的相互作用及其在纳米颗粒生命周期中的pH依赖性调节之间的相互作用，主要决定了治疗方法的有效性。尽管在过去的二十年中，LNP的交付效率有了很大的提高，据估计，实际上只提供了一小部分货物，从而刺激了对更有效的LNP配方设计的进一步研究。理性驱动的设计将从对这些材料的精确分子结构的知识中获利，但是，这些材料仍然缺少或以不良的空间分辨率为特征。计算方法通常被用作分子显微镜，以丰富可用的实验数据，并提供LNP的分子级图像，甚至模拟涉及LNP作用的形成和/或分子机制的特定过程。在这里，我回顾了该领域的最新文献。
Settanni; Giovanni[1]. Computational approaches to lipid-based nucleic acid delivery systems[J]. The European Physical Journal E, 2023,46(12): 1-13