预测未表征的KCNQ1和KCNE1变种的有害潜力
Svetlana I Tarnovskaya1, Boris S Zhorov1,2
1Sechenov Institute of Evolutionary Physiology & Biochemistry, Russian Academy of Sciences, St. Petersburg 194223, Russia.
International journal of molecular sciences
|July 29, 2025
概括
像AlphaMissense这样的计算工具对于预测Kv7.1通道中的遗传变异的影响至关重要,有助于诊断诸如长QT综合征等心脏疾病.
科学领域:
- 心血管遗传学 心血管遗传学
- 离子通道生物学 离子通道生物学
- 计算生物学 计算生物学
背景情况:
- 电压通道,特别是Kv7.1 (KCNQ1),对于心脏动作潜力的再极化至关重要.
- 许多KCNQ1变异与长QT综合征有关,但许多仍然具有不确定的临床意义 (VUS).
- 准确预测KCNQ1变异的致病性对于诊断和治疗心脏病至关重要.
研究的目的:
- 评估26种生物信息学工具在识别致病性Kv通道变异方面的性能.
- 使用性能最佳的计算工具,预测Kv7.1通道中VUS的临床意义.
- 用冷电子显微镜和AlphaFold3模型研究变异性致病性的结构基础.
主要方法:
- 从ClinVar,Humsavar和Ensembl变异数据库收集了1750种良性和致病性误解变体.
- 测试了26种生物信息学工具,以测试它们对已知致病或可能致病 (P/LP) 变体的分类能力.
- 使用AlphaMissense,ClinPred和paralogue注释用于VUS病原性预测和结构分析.
主要成果:
- 阿尔法Missense表现出卓越的性能,预测了195 Kv7.1 VUSs的致病性.
- 结构分析揭示了野生型残留物 (WTRs) 和变体之间的跨细分接触,表明了功能障碍的机制.
- ClinPred和paralogue注释在KCNE1中发现了34个具有破坏潜力的VUS,其中8个接触Kv7.1变种.
结论:
- AlphaMissense是一种强大的工具,可以将VUS分类为Kv7.1通道,从而提高诊断准确度.
- 来自cryo-EM和AlphaFold3模型的结构洞察力为变异效应提供了原子层次的理解.
- 这项研究增强了对Kv7.1基因变异的解释,有助于临床管理相关心脏疾病.
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