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相关概念视频

Leaky Scanning02:28

Leaky Scanning

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During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA.  Marilyn Kozak discovered that the sequence RCCAUGG (where R...
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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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The Upf proteins that carry out nonsense-mediated decay (NMD) are found in all eukaryotic organisms, including humans. Each protein has an individual role, but they need to work in collaboration. Upf1 is an ATP-dependent RNA helicase that unwinds the RNA helix. Because Upf1 can unwind any RNA, Upf2 and Upf3 are required to help Upf1 discriminate between nonsense and normal mRNAs.
Usually, Upf3 binds to an Exon Junction Complex (EJC) at mRNA splice sites. If a ribosome fully translates the mRNA,...
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PTMs_Closed_Search:多个翻译后修改 封闭搜索使用减少的搜索空间和转移的FDR.

Yury Yu Strogov1, Sergey A Spirin2,3,4, Mark V Ivanov5

  • 1Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow 119991, Russia.

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|February 20, 2026
PubMed
概括

本研究引入了针对MS/MS数据的翻译后修改 (PTM) 分析的优化Python管道,改善了标识和蛋白质覆盖. 这种新方法提高了错误发现率 (FDR) 估计,以实现更可靠的PTM检测.

关键词:
算法算法是一种算法.封闭搜索 封闭搜索一个特定集团的FDR.后翻译修改后的修改

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科学领域:

  • 蛋白质组学是指蛋白质组学.
  • 计算生物学 计算生物学
  • 生物信息学是一种生物信息学.

背景情况:

  • 目前在MS/MS数据中进行的翻译后修改 (PTM) 搜索使用开放修改搜索 (OMS) 或封闭搜索 (CS) 算法.
  • OMS允许许多PTM和未知的质量转移,而CS更敏感,但PTM范围有限.
  • 需要更全面和敏感的PTM识别方法.

研究的目的:

  • 为自动化,顺序的PTM搜索开发一个优化的Python算法.
  • 为了提高错误发现率 (FDR) 估计对PTM分析的意义.
  • 改进MS/MS数据中的类鉴定和蛋白质覆盖率.

主要方法:

  • 基于IdentiPy搜索引擎的优化Python算法被开发用于自动连续的PTM搜索.
  • 该算法利用公共数据库和定制蛋白质列表进行PTM注释.
  • 修改的FDR计算与spline近似和错误传播被实施用于数据过.

主要成果:

  • 该管道展示了与未经修改的和蛋白质的现有方法相似的结果.
  • 确定了13种不同类型的PTM,增加了相对蛋白质覆盖范围.
  • 与单独的FDR计算相比,基于spline的FDR过方法产生了更多的鉴定.

结论:

  • 开发的管道为MS/MS数据中的多个PTM搜索提供了强大的解决方案.
  • 它可以作为独立应用程序使用,也可以集成到现有的数据分析平台中.
  • 该方法提高了PTM识别的准确性和效率.