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相关概念视频

Mutations01:35

Mutations

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Mutations are changes in the sequence of DNA. These changes can occur spontaneously or they can be induced by exposure to environmental factors. Mutations can be characterized in a number of different ways: whether and how they alter the amino acid sequence of the protein, whether they occur over a small or large area of DNA, and whether they occur in somatic cells or germline cells.
Chromosomal Alterations Are Large-Scale Mutations
While point mutations are changes in a single nucleotide in...
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Mutations01:39

Mutations

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Overview
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Mutations in Microorganisms01:18

Mutations in Microorganisms

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Mutations are heritable changes in an organism’s genome involving alterations in the base sequence of DNA or RNA. These changes can influence cellular processes and phenotypic traits, potentially transforming the unaltered wild type into a mutant form. Such changes, termed forward mutations, are pivotal in shaping the genetic diversity of organisms.RNA viruses exhibit the highest mutation rates due to the absence of robust proofreading mechanisms during genome replication. In contrast,...
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Mismatch Repair01:20

Mismatch Repair

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Organisms are capable of detecting and fixing nucleotide mismatches that occur during DNA replication. This sophisticated process requires identifying the new strand and replacing the erroneous bases with correct nucleotides. Mismatch repair is coordinated by many proteins in both prokaryotes and eukaryotes.
The Mutator Protein Family Plays a Key Role in DNA Mismatch Repair
The human genome has more than 3 billion base pairs of DNA per cell. Prior to cell division, that vast amount of genetic...
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Mismatch Repair01:36

Mismatch Repair

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Protein Networks02:26

Protein Networks

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
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相关实验视频

Updated: Mar 10, 2026

Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms
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MutPPI+:通过基于突变路径的数据增强来预测蛋白质-蛋白质相互作用的突变影响的多式框架.

Juntao Deng1, Miao Gu1, Pengyan Zhang1

  • 1Department of Automation, Tsinghua University, Shuangqing Road 30, Haidian District, Beijing, 100084, China.

Briefings in bioinformatics
|March 8, 2026
PubMed
概括
此摘要是机器生成的。

预测突变如何影响蛋白质与蛋白质相互作用 (PPI) 对了解疾病至关重要. 新的深度学习模型MutPPI和MutPPI-plus准确地预测了这些稳定性变化 (ΔΔG),有助于蛋白质工程.

关键词:
有约束力的自由能源变更.数据增强数据增强深度学习是一种深度学习.突变是一种突变.蛋白质蛋白质相互作用

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科学领域:

  • 计算生物学 计算生物学
  • 结构生物学 结构生物学
  • 生物信息学是一种生物信息学.

背景情况:

  • 蛋白与蛋白相互作用 (PPI) 是细胞过程的基础.
  • PPI的失调与许多疾病有关.
  • 对PPI稳定性 (ΔΔG) 突变影响的准确预测对于阐明疾病机制和蛋白质工程至关重要.

研究的目的:

  • 开发和验证先进的计算模型,用于预测突变对蛋白质-蛋白质相互作用稳定性的影响.
  • 通过整合结构,进化和多模式数据来提高预测准确性.
  • 引入一种新的数据增强策略,以改善模型通用化.

主要方法:

  • 开发 MutPPI,一个基于图形的深度学习模型,利用GIN-GAT从蛋白质复杂结构中提取特征.
  • 从蛋白质语言模型中整合进化信息以创建MutPPI-plus.
  • 实施基于突变路径的数据增强策略,以丰富输入模式.
  • 对基准数据集的性能评估,包括单点 (S645) 和多点突变数据集 (SM_ZEMu,SM595,SM1124).

主要成果:

  • 在S645数据集上,MutPPI在12种现有方法中表现出优越的性能.
  • 结合进化信息的MutPPI-plus实现了更高的预测准确度.
  • 突变路径数据增强策略改善了这两种模型的概括性.
  • 使用数据增强的 MutPPI-plus 在多个数据集上取得了最先进的结果,显著超过了 DDMut-PPI.

结论:

  • 开发的多式联机深度学习模型 (MutPPI和MutPPI-plus) 为预测ΔΔG提供了多功能和准确的计算工具.
  • 物理信息化的数据增强方法增强了模型的概括性和预测能力.
  • 这些进展促进了合理的蛋白质设计,并加深了对疾病背景中的突变效应的理解.