Advances in the Prediction of Protein Aggregation Propensity

doi:10.2174/0929867324666170705121754

摘要

背景：发现蛋白质聚集到富含β-折叠的不溶性组装物中，与越来越多的使人衰弱的人体疾病（例如阿尔茨海默氏病或2型糖尿病）有关，但也与早衰有关。此外，蛋白质聚集代表了基于蛋白质的疗法的生产和销售中的主要瓶颈。因此，开发准确预测某种蛋白质聚集倾向的方法具有很大的价值。方法/结果：大量的体外和体内聚集研究表明，某些多肽序列的聚集倾向高度依赖于其固有特性，并且在大多数情况下，是由高聚集倾向的特定短区驱动的。这些观察结果促进了旨在从蛋白质序列预测蛋白质聚集倾向的第一代算法的发展。能够在蛋白质结构上绘制蛋白质聚集图的第二代程序正在兴起。在此，我们回顾最具代表性的在线可访问预测工具，重点介绍其主要特色和应用范围。结论：在这篇综述中，我们描述了代表性的生物计算方法，以评估蛋白质序列和结构的聚集特性，同时说明了它们如何成为非常有用的工具，可用于靶向生物医学和生物技术中的蛋白质聚集。

关键词: 淀粉样蛋白，生物信息学，蛋白质聚集，蛋白质结构，治疗性蛋白质，生物计算方法。

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DOI https://dx.doi.org/10.2174/0929867324666170705121754	Print ISSN 0929-8673
Publisher Name Bentham Science Publisher	Online ISSN 1875-533X

当代药物化学

蛋白质聚集倾向的预测研究进展

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当代药物化学

蛋白质聚集倾向的预测研究进展

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