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相关概念视频

Phosphorylation01:02

Phosphorylation

50.4K
The addition or removal of phosphate groups from proteins is the most common chemical modification that regulates cellular processes. These modifications can affect the structure, activity, stability, and localization of proteins within cells as well as their interactions with other proteins.
During phosphorylation, protein kinases transfer the terminal phosphate group of ATP to specific amino acid side chains of substrate proteins. Serine, threonine, and tyrosine are the most commonly...
50.4K
Covalently Linked Protein Regulators02:04

Covalently Linked Protein Regulators

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Proteins can undergo many types of post-translational modifications, often in response to changes in their environment. These modifications play an important role in the function and stability of these proteins. Covalently linked molecules include functional groups, such as methyl, acetyl, and phosphate groups, and also small proteins, such as ubiquitin. There are around 200 different types of covalent regulators that have been identified.
These groups modify specific amino acids in a protein....
6.8K
Protein Kinases and Phosphatases02:54

Protein Kinases and Phosphatases

13.2K
Proteins undergo chemical modifications that trigger changes in the charge, structure, and conformation of the proteins. Phosphorylation, acetylation, glycosylation, nitrosylation, ubiquitination, lipidation, methylation, and proteolysis are various protein modifications that regulate protein activity. Such modifications are usually enzyme-driven.
Protein kinases
Many proteins in the cell are regulated by phosphorylation, the addition of a phosphate group. A family of enzymes called kinases...
13.2K

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相关实验视频

Updated: Jul 11, 2025

Resin-Assisted Capture Coupled with Isobaric Tandem Mass Tag Labeling for Multiplexed Quantification of Protein Thiol Oxidation
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使用XGBoost预测酸化后的氨酸反应性变化.

Jing Cao1, Yan Xu1

  • 1Department of Statistics, University of Science and Technology Beijing, China.

FEBS open bio
|November 15, 2023
PubMed
概括
此摘要是机器生成的。

机器学习预测了酸化如何改变蛋白质中的氨酸反应性,有助于理解蛋白质功能和疾病联系. 这种方法加速了全蛋白质组分析以获得临床见解.

关键词:
在XGBoost中使用.半氨酸的反应活性机器学习是机器学习.光化蛋白质的光化蛋白质.蛋白质的功能 蛋白质的功能

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科学领域:

  • 生物化学 生物化学
  • 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:

  • 半氨酸的反应性对蛋白质功能至关重要,并通过酸化来调节.
  • 目前研究这些变化的实验方法规模有限.
  • 机器学习为加速这些调查提供了一个有希望的途径.

研究的目的:

  • 开发一种机器学习模型,以预测因酸化而导致的氨酸活性变化.
  • 为了确定受酸化诱导的氨酸反应性变化影响的蛋白质和途径.
  • 提供一种计算工具,用于对氨酸反应性的全蛋白质分析.

主要方法:

  • 利用蛋白质序列,酸化位点的近距离和内在无序区域得分来表示囊蛋白.
  • 采用弹性网用于特征选择和XGBoost用于构建二进制分类器.
  • 对预测的蛋白质进行了功能丰富分析,该蛋白质具有改变的囊反应性.

主要成果:

  • 在独立测试中,XGBoost获得了高性能,AUC为0.8192 (发生) 和0.9203 (方向).
  • 一个连续的两种分类器方法产生了0.7568的准确度,用于预测反应性没有变化,增加或减少.
  • 丰富分析将改变的囊反应性与癌症,自体主导性疾病和病毒感染联系起来.

结论:

  • 酸化诱导的氨酸反应性变化是特定于位点的,并且可以使用XGBoost算法进行预测.
  • 开发的模型提供了一种有效的方法,用于蛋白质组范围内的氨酸反应性的探索.
  • 这有助于更深入地了解蛋白质功能和潜在的临床应用.