通过AlphaFold2系统识别有条件折叠的内在无序区域
T Reid Alderson1,2, Iva Pritišanac3,4,5, Đesika Kolarić5
1Department of Biochemistry, University of Toronto, Toronto, ON M5S 1A8, Canada.
概括
AlphaFold2令人惊地预测了有条件折叠的内在无序区域 (IDR) 的结构. 这些区域与人类疾病有关,并且在原核生物中很丰富,但不是在真核生物中.
科学领域:
- 结构生物学是结构生物学.
- 生物信息学是一种生物信息学.
- 计算生物学是一种计算生物学.
背景情况:
- 阿尔法蛋白质结构数据库提供了数以百万计的预测蛋白质结构.
- 本质上无序的区域 (IDR) 缺乏稳定的结构,通常被认为具有较低的预测信心.
- 条件折叠描述了在特定条件 (如绑定) 上采用结构的IDR.
研究的目的:
- 调查AlphaFold2对内在无序区域 (IDR) 的信任分数.
- 评估AlphaFold2能够预测条件折叠IDR的结构的能力.
- 探索条件折叠IDRs,疾病突变和家族遗传分布之间的关系.
主要方法:
- 对人类内在无序区域 (IDR) 的 AlphaFold2 置信度评分的分析.
- 将AlphaFold2预测与条件折叠IDR实验核磁共振 (NMR) 数据进行比较.
- 使用已知条件折叠IDRs的数据库评估AlphaFold2的性能.
- 在条件折叠的IDR中对人类疾病突变丰富的分析.
- 在 prokaryotic 和 eukaryotic IDR 中预测条件折叠的比较分析.
主要成果:
- AlphaFold2将可靠的结构预测赋予了近15%的人类内在无序区域 (IDR).
- AlphaFold2准确地预测了NMR数据验证的条件折叠IDR子集的折叠状态结构.
- 鉴定条件折叠IDR的估计精度高达88%,假阳性率为10%.
- 人类疾病突变在有条件折叠的IDR中显著丰富 (几乎是五倍).
- 预计高达80%的 prokaryotic IDRs 会有条件折叠,相比之下,只有不到20%的真核IDRs.
结论:
- 尽管训练数据有限,但AlphaFold2能够非常准确地识别有条件折叠的内在无序区域 (IDR).
- 有条件折叠的IDR是人类疾病突变的热点.
- 条件折叠在 prokaryotes 中普遍存在,但在 eukaryotes 中不太常见,这表明不同的功能角色.
- AlphaFold2的预测不能完全捕捉到IDR的功能可塑性或组合性质.
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