集群化内在无序蛋白质的异构形态组合,具有t分布的随机邻居嵌入
Rajeswari Appadurai1, Jaya Krishna Koneru2, Massimiliano Bonomi3
1Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka 560012, India.
Journal of chemical theory and computation
|June 20, 2023
概括
这项研究引入了t分布式随机邻居嵌入 (t-SNE) 来集群内在无序蛋白质 (IDP) 构造. 这种方法揭示了有序子状态,并有助于理解用于药物设计的IDP-连接物相互作用.
科学领域:
- 生物化学和结构生物学
- 计算生物学 计算生物学
- 药物发现 药物发现 药物发现
背景情况:
- 内在无序的蛋白质 (IDP) 存在于异质的构成组合中.
- 由于其高维度,分析和可视化IDP构造空间具有挑战性.
- 当前的减少技术往往产生模两可的IDP结构的分类.
研究的目的:
- 开发一种可靠的方法,用于将IDP构造物群集成到同质群体中.
- 想象和解释IDP集合中的构造异质性.
- 为了获得关于IDP-连接体结合的结构和机制见解.
主要方法:
- 应用t分布式随机邻居嵌入 (t-SNE) 进行维度缩小和集群.
- 分析内在无序的蛋白质构造,包括Aβ42和α-synuclein.
- 在APO状态中对蛋白质构造的比较与与小分子连接体结合的比较.
主要成果:
- t-SNE成功地从异质的IDP集群中生成了同质的集群.
- 在无序的形态景观中识别了有序的子状态.
- 提供了对影响IDP连接体特异性和亲属性的特定结合模式的见解.
结论:
- t-SNE提供了一个强大的框架来分析IDP的结构动态.
- 该方法使可解释的可视化和定量化构造变化的方法.
- 这种方法可以推进针对境内流离失所者的合理药物设计.
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