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涉及神经退行性疾病的TREM2误解变体的生物物理特征

Joshua Pillai^1,2, Kijung Sung², Linda Shi³

¹School of Biological Sciences, University of California, San Diego, 9301 S Scholars Dr, La Jolla, CA 92093, USA.

Computational and structural biotechnology journal

|July 21, 2025

概括

在骨髓细胞表达的触发受体2 (TREM2) 变体与阿尔茨海默病有关. 这项研究使用结构生物信息学来分类44种TREM2变异,识别影响蛋白质稳定性和功能的关键突变.

科学领域:

神经科学是一个神经科学.
遗传学是一个遗传学.
结构生物信息学结构生物信息学

背景情况:

在骨髓细胞2表达的触发受体 (TREM2) 是微质上的免疫受体,被认为是阿尔茨海默病 (AD) 的风险因素.
错误的TREM2变体与神经退行性疾病有关,如前性痴呆症和纳苏-哈科拉病 (NHD).
大多数已识别的TREM2变异的致病性仍然在很大程度上没有表征,阻碍了疾病机制研究和治疗开发.

研究的目的:

使用结构生物信息学对44种TREM2误解变异的病原性进行分类.
评估这些TREM2变体的结构,稳定性和潜在的功能影响.
为未知TREM2变异的实验分类提供基线生物化学数据.

主要方法:

使用AlphaFold2进行TREM2变体的结构预测.
员工制定了协议,以确定结构,稳定性和功能影响.
根据疾病关联 (NHD),位置 (跨膜域,IgV类域表面,埋藏) 和预测可靠性进行分类变异.

主要成果:

对NHD隐含变异的分析表明V126G对TREM2结构的影响最大,而T66M对TREM2结构的影响最小.
在TREM2跨膜域内的变体没有显著改变3D结构.
鉴定出了IgV类域之外的10种新型变异,可显著破坏TREM2结构的稳定性.

结论:

结构生物信息学为分类未知意义的TREM2变异提供了有价值的方法.
特定的TREM2变种表现出不同程度的结构和稳定性影响,为疾病相关性提供了洞察力.
生成的生物化学数据可以指导未来在神经退行性疾病研究中对TREM2变体的实验验证.

关键词:

在AlphaFold2中,我们使用了AlphaFold2.阿尔茨海默氏症是阿尔茨海默氏症的一种疾病.神经退行性疾病神经退行性疾病在TREM2中,我们可以使用TREM2.

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