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相关概念视频

The Two-State Receptor Model01:29

The Two-State Receptor Model

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The two-state receptor model explains a drug's interaction with receptors, such as G protein-coupled receptors and ligand-gated ion channels, to induce or inhibit a biological response. When no natural ligands are present, a receptor exists in an equilibrium of inactive (Ri) and active (Ra) conformations. The inactive form does not produce a response, while the active form generates a basal effect known as constitutive activity.
The binding affinity of a drug determines its interaction with...
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Quantitative Aspects of Drug-Receptor Interaction01:30

Quantitative Aspects of Drug-Receptor Interaction

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The receptor occupancy theory connects a drug's response to the number of occupied receptors. With higher drug concentrations, more receptors are occupied, leading to increased responses. The formation of drug-receptor complexes involves association and dissociation rates, which reach equilibrium when the forward and backward reactions are equal. The equilibrium association constant (Ka) and its inverse, the equilibrium dissociation constant (Kd), indicate drug affinity. Higher Ka and lower...
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G Protein-coupled Receptors01:15

G Protein-coupled Receptors

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G Protein-Coupled Receptors or GPCRs are membrane-bound receptors that transiently associate with heterotrimeric G proteins and induce an appropriate response to sensory stimuli such as light, odors, hormones, cytokines, or neurotransmitters.
GPCRs are also called heptahelical, 7TM, or serpentine receptors, and consist of seven (H1-H7) transmembrane alpha-helices that span the bilayer to form a cylindrical core. The transmembrane helices are connected by three extracellular loops and three...
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Ribosome Profiling02:24

Ribosome Profiling

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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
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瑞登:数据驱动的从转录组数据推断受体活性.

Szilvia Barsi1,2, Eszter Varga2, Daniel Dimitrov3

  • 1Institute of Molecular Life Sciences, Centre of Excellence of the Hungarian Academy of Sciences, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary.

PLoS computational biology
|June 16, 2025
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概括
此摘要是机器生成的。

RIDDEN通过分析基因表达变化来预测受体活性,而不是连接体或受体水平. 这种计算工具有助于识别细胞特异性受体变化,并了解疾病中的细胞通信.

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科学领域:

  • 计算生物学 计算生物学
  • 系统生物学 系统生物学
  • 基因组学就是基因组学.

背景情况:

  • 受体信号传递对生理调节和疾病至关重要,使受体成为关键药物点.
  • 对于联体受体相互作用的现有计算方法通常侧重于联体或基因共同表达,这可能不反映功能活动.
  • 需要工具直接推断受体活性从下游基因表达变化.

研究的目的:

  • 开发一种计算工具,RIDDEN (受体行为数据驱动推断),用于预测受体活动.
  • 从受体调节的基因表达特征直接推断受体活性.
  • 为了使细胞和疾病特异性受体活性变化的系统级分析.

主要方法:

  • 在229个受体中使用14463个扰乱基因表达特征训练了RIDDEN模型.
  • RIDDEN推断受体活性来自下游基因表达,而不是连接体或受体基因表达.
  • 在独立的体外和体外受体扰动数据集上验证了模型.

主要成果:

  • RIDDEN有效地预测了批量和单细胞转录组学数据中的受体活性.
  • 模型重量与已知的受体-转录因子调节相互作用保持一致.
  • 预测的受体活动与体内数据中的受体和连接体表达相关.
  • 在接受免疫检查点封锁治疗的癌症患者队列中,RIDDEN确定了机械生物标志物.

结论:

  • 到目前为止,RIDDEN是迄今为止最大的基于转录组学的受体活动推断模型.
  • 该工具可以识别具有受体活性改变的细胞群.
  • 瑞登 (RIDDEN) 通过转录组学数据促进了细胞与细胞通信的研究.
  • 这种方法促进了对生理和疾病状态中的受体功能的理解.