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相关概念视频

Ligand Binding Sites02:40

Ligand Binding Sites

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Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
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Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

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Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence...
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Ligand Binding and Linkage00:49

Ligand Binding and Linkage

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Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence...
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Targets for Drug Action: Overview01:26

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Drugs target macromolecules to modify ongoing cellular processes. Primary drug targets include receptors, ion channels, transporters, and enzymes.
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The Two-State Receptor Model01:29

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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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Ligand-gated ion channels are transmembrane proteins that play a vital role in intercellular communication and functions of the nervous system. They allow the influx of ions across the membrane once the neurotransmitter binds, allowing the subsequent transmission of electrical excitation across the neurons. Other ligand-gated ion channels, like the γ-aminobutyric acid (GABA) receptor, permit anions like chloride into the cells on the binding of the GABA molecule. Their entry into the cell...
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相关实验视频

Updated: Jun 14, 2025

Development of Inhibitors of Protein-protein Interactions through REPLACE: Application to the Design and Development Non-ATP Competitive CDK Inhibitors
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CLigOpt:通过针对特定目标的优化,可控制的连接体设计.

Yutong Li1, Pedro Henrique da Costa Avelar1,2, Xinyue Chen1

  • 1Department of Informatics, King's College London, London WC2B 4BG, United Kingdom.

Bioinformatics (Oxford, England)
|September 4, 2024
PubMed
概括
此摘要是机器生成的。

我们开发了CLigOpt,一种可控制的基于碎片的药物设计 (FBDD) 模型,以生成具有所需性质的向分子. 这种方法增强了用于药物开发的可行活性分子的发现.

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Creating Highly Specific Chemically Induced Protein Dimerization Systems by Stepwise Phage Selection of a Combinatorial Single-Domain Antibody Library
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Development of Inhibitors of Protein-protein Interactions through REPLACE: Application to the Design and Development Non-ATP Competitive CDK Inhibitors
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Creating Highly Specific Chemically Induced Protein Dimerization Systems by Stepwise Phage Selection of a Combinatorial Single-Domain Antibody Library
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Creating Highly Specific Chemically Induced Protein Dimerization Systems by Stepwise Phage Selection of a Combinatorial Single-Domain Antibody Library

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科学领域:

  • 计算化学是一种计算化学.
  • 药品化学 药品化学 是一个
  • 人工智能在药物发现中的作用

背景情况:

  • 深度生成模型面临着在药物设计的巨大分子空间中导航的挑战.
  • 基于碎片的药物设计 (FBDD) 提供了一种有限的方法来产生生物活性分子.
  • 优化方法对于识别具有特定所需性质的分子至关重要.

研究的目的:

  • 介绍CLigOpt,一种可控制的FBDD模型,用于从碎片对中生成具有所需性质的分子.
  • 为了利用变化自编码器和共同嵌入来进行全面的分子图形信息挖掘.
  • 通过多目标可控生成模块实现属性控制的分子生成.

主要方法:

  • 使用了变化自编码器 (VAE) 架构.
  • 用于分子图表表示的节点和边缘特征的共同嵌入.
  • 实施了一种多目标可控发电模块,用于物质导向发电.

主要成果:

  • 在6个指标中,CLigOpt在生成有效分子方面表现强.
  • 产生了hDHFR的配体候选者,使可行的活性分子增加了10%.
  • 应用分子对接和合成性预测来优先考虑潜在的化合物.

结论:

  • 使用可控制的FBDD方法,CLigOpt有效地产生具有所需特性的分子.
  • 该模型显示了高效的特定目标连接体设计的前景.
  • 确定优先级的方法有助于从产生的分子中提取潜在的化合物.