使用进化背景来分类难以折叠的蛋白质
Jimin Pei1,2,3, R Dustin Schaeffer2, Qian Cong1,2,3
1Eugene McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.
PLoS computational biology
|December 1, 2025
概括
蛋白质结构预测的进步揭示了新的蛋白质域. 整合结构和进化方法,如DPAM,有助于分类这些领域,并发现遥远的进化联系.
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.
- 进化生物学是进化的生物学.
背景情况:
- 最近的蛋白质结构预测工具,如AlphaFold2,已经确定了许多具有独特结构的新型蛋白质域.
- 域名百科全书 (TED) 项目根据结构分类编目了超过7400个候选新 (CNF) 域名.
研究的目的:
- 使用一种新方法分析TED CNF领域的进化和结构背景.
- 将TED和DPAM的域解析结果进行比较,以了解它们之间的关系并完善蛋白质域分类.
主要方法:
- 应用DPAM (AlphaFold模型的域解析器),它将AlphaFold信任分数与序列和结构相似性搜索集成.
- 在包含TED CNF域的AlphaFold模型中解析域.
- 在TED和DPAM之间比较域边界和分类.
主要成果:
- 确定了8044个与TED CNF域重叠的DPAM域;2490个在ECOD层次结构中被安全地分类.
- 有相当一部分TED CNF域是已知的ECOD域的远方同类.
- 在TED和DPAM之间观察到不同的域边界模式,TED域经常嵌入DPAM域内,表明插入或扩展.
结论:
- 结构和进化方法是蛋白质域注释的补充.
- 像DPAM这样的整合方法对于完善复杂蛋白质折叠的分类和识别远程进化关系来说非常强大.
- 这项研究完善了我们对新型蛋白质折叠及其进化联系的理解.
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