Fantastic AAV Gene Therapy Vectors and How to Find Them-Random Diversification, Rational Design and Machine Learning.
Fantastic AAV Gene Therapy Vectors and How to Find Them-Random Diversification, Rational Design and Machine Learning.
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DOI：
10.3390/pathogens11070756
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发表时间：
2022-07-03
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影响因子：
--
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细小病毒是一个小的、无包膜的DNA病毒家族，可感染多种物种、组织和细胞类型。半个多世纪以来，它们耐人寻味的生物学和病理生理学推动了旨在剖析潜在病毒和细胞机制的密集研究。同时，它们广泛的宿主特异性(趋向性)促使人们努力开发细小病毒作为人类癌症或基因治疗应用的基因递送载体。虽然临床前和临床数据的总和一致地证明了这些载体的巨大潜力，但这些发现也说明了在所需细胞类型中增强和限制体内转基因表达的重要性。为此，已经取得了重大进展，特别是基于腺相关病毒(AAV)的载体，其衣壳具有高度的生物工程能力，可以改变和扩大其自然趋向性。在这里，我们提供了一个最先进的方法，以创造新的AAV变异体，具有更高的特异性和效率的基因转移的目标细胞。我们首先回顾了传统的和新的定向进化方法，包括高通量筛选AAV衣壳文库。接下来，我们讨论可编程受体介导的靶向，重点是利用高亲和力结合的两项最新技术。最后，我们重点介绍了理性AAV载体表征和优化的最新策略之一，即机器学习，它有望促进和加速识别下一代、安全和精确的基因输送工具。
Parvoviruses are a diverse family of small, non-enveloped DNA viruses that infect a wide variety of species, tissues and cell types. For over half a century, their intriguing biology and pathophysiology has fueled intensive research aimed at dissecting the underlying viral and cellular mechanisms. Concurrently, their broad host specificity (tropism) has motivated efforts to develop parvoviruses as gene delivery vectors for human cancer or gene therapy applications. While the sum of preclinical and clinical data consistently demonstrates the great potential of these vectors, these findings also illustrate the importance of enhancing and restricting in vivo transgene expression in desired cell types. To this end, major progress has been made especially with vectors based on Adeno-associated virus (AAV), whose capsid is highly amenable to bioengineering, repurposing and expansion of its natural tropism. Here, we provide an overview of the state-of-the-art approaches to create new AAV variants with higher specificity and efficiency of gene transfer in on-target cells. We first review traditional and novel directed evolution approaches, including high-throughput screening of AAV capsid libraries. Next, we discuss programmable receptor-mediated targeting with a focus on two recent technologies that utilize high-affinity binders. Finally, we highlight one of the latest stratagems for rational AAV vector characterization and optimization, namely, machine learning, which promises to facilitate and accelerate the identification of next-generation, safe and precise gene delivery vehicles.
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发表时间：
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期刊：
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