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相关概念视频

Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

7.1K
Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome.  Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form...
7.1K
Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

2.4K
2.4K
Conserved Binding Sites01:49

Conserved Binding Sites

5.0K
Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
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Transcription Factors02:16

Transcription Factors

82.2K
Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...
82.2K
General Transcription Factors01:30

General Transcription Factors

6.7K
Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...
6.7K

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相关实验视频

Updated: Jan 13, 2026

Identifying Transcription Factor Olig2 Genomic Binding Sites in Acutely Purified PDGFRα+ Cells by Low-cell Chromatin Immunoprecipitation Sequencing Analysis
12:29

Identifying Transcription Factor Olig2 Genomic Binding Sites in Acutely Purified PDGFRα+ Cells by Low-cell Chromatin Immunoprecipitation Sequencing Analysis

Published on: April 16, 2018

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使用AlphaFold 3进行转录因子结合的非编码变异评估的结构导向方法.

Lukas Gerasimavicius1, Simon C Biddie1,2, Joseph A Marsh1

  • 1MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, United Kingdom.

Nucleic acids research
|January 7, 2026
PubMed
概括

使用AlphaFold 3和FoldX的结构建模为影响转录因子结合的非编码变体提供了洞察力. 这种方法,评估接口预测模板建模 (ipTM) 得分,补充了基于序列的方法,用于疾病变体分析.

科学领域:

  • 基因组学就是基因组学.
  • 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:

  • 非编码单核酸变体 (SNVs) 可以通过影响转录因子 (TF) 结合来改变基因表达,从而导致疾病.
  • 目前针对TF结合的基于序列的预测方法存在局限性,包括依赖训练数据和TF特定偏差.

研究的目的:

  • 开发和评估一种以结构为导向的方法,用于预测非编码SNV对TF结合的影响.
  • 评估AlphaFold 3 (AF3) 和FoldX在建模TF-DNA复合体和评估变异效应中的实用性.

主要方法:

  • 利用AlphaFold 3 (AF3) 来建模转录因子-DNA复合体.
  • 使用FoldX进行基于物理的评估,以评估变异对TF结合亲缘关系的影响.
  • 对六个转录因子的实验SNP-SELEX数据进行基准预测.

主要成果:

  • 基于FoldX的策略与实验性等位基偏好有很好的一致性.
  • AlphaFold 3的界面预测模板建模 (ipTM) 得分与实验数据密切结合,通常表现优于基于能源的指标.
  • 对DipTM和FoldX能量的综合分析提高了与疾病相关的变异的可靠性.

更多相关视频

Genome-wide Profiling of Transcription Factor-DNA Binding Interactions in Candida albicans: A Comprehensive CUT&RUN Method and Data Analysis Workflow
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Genome-wide Profiling of Transcription Factor-DNA Binding Interactions in Candida albicans: A Comprehensive CUT&RUN Method and Data Analysis Workflow

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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

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相关实验视频

Last Updated: Jan 13, 2026

Identifying Transcription Factor Olig2 Genomic Binding Sites in Acutely Purified PDGFRα+ Cells by Low-cell Chromatin Immunoprecipitation Sequencing Analysis
12:29

Identifying Transcription Factor Olig2 Genomic Binding Sites in Acutely Purified PDGFRα+ Cells by Low-cell Chromatin Immunoprecipitation Sequencing Analysis

Published on: April 16, 2018

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Genome-wide Profiling of Transcription Factor-DNA Binding Interactions in Candida albicans: A Comprehensive CUT&RUN Method and Data Analysis Workflow
07:48

Genome-wide Profiling of Transcription Factor-DNA Binding Interactions in Candida albicans: A Comprehensive CUT&RUN Method and Data Analysis Workflow

Published on: April 1, 2022

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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

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结论:

  • 结构建模提供了对非编码变体如何影响TF结合的可解释的见解.
  • 拟议的结构导向方法为监管变体提供了一个补充的评估方法.
  • 突出了AF3在分析影响TF结合的非编码变体方面的潜力和局限性.