DRP-PSM:多级特征集成揭示了对致病同义突变预测的层次贡献
Jinsong Cai1,2, Fangfang Jin2, Na Cheng3
1Department of Mechanical and Electrical Information, Anhui Vocational College of Press and Publishing, Hefei, Anhui 230601, China.
ACS omega
|October 27, 2025
概括
预测致病同义突变是了解疾病的关键. DNA和RNA特征是最具影响力的,这表明拼接和转录效率是主要机制,而不是蛋白质变化.
科学领域:
- 遗传学 是一个遗传学.
- 分子生物学分子生物学
- 生物信息学是一种生物信息学.
背景情况:
- 同名突变不会改变氨基酸序列,但可以影响蛋白质功能.
- 这些微妙的遗传变异与疾病的发病和进展有关.
- 准确预测致病同名突变对于临床诊断和治疗至关重要.
研究的目的:
- 开发一种新的方法,DRP-PSM,用于预测致病性同名突变.
- 整合DNA,RNA和蛋白质水平的生物特征,以建立一个全面的预测框架.
- 阐明不同生物水平对同义突变致病性的贡献.
主要方法:
- 开发了DRP-PSM,一种结合DNA,RNA和蛋白质特征的预测方法.
- 从DNA,RNA和蛋白质水平系统地整合了序列和结构特征.
- 从不同的生物层面评估特征的预测能力.
主要成果:
- DNA级特征为预测准确性提供了最大的贡献,其次是RNA级特征.
- 蛋白质水平的特征提供了边际预测效用.
- DNA 保存和拼接效应是占主导地位的生物特征,优于序列/结构描述符.
结论:
- 同名突变主要通过对拼接或转录效率的影响引起病原性.
- 翻译或后翻译过程的贡献不那么重要.
- 了解这些调节机制提供了潜在的治疗目标.
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