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相关概念视频

Ligand Binding Sites02:40

Ligand Binding Sites

12.8K
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...
12.8K
Conserved Binding Sites01:49

Conserved Binding Sites

4.2K
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...
4.2K
Drug Discovery: Overview01:26

Drug Discovery: Overview

7.8K
Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
7.8K
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

4.8K
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...
4.8K
Ligand-Gated Ion Channel Receptor: Gating Mechanism01:30

Ligand-Gated Ion Channel Receptor: Gating Mechanism

2.2K
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...
2.2K
The Two-State Receptor Model01:29

The Two-State Receptor Model

1.9K
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...
1.9K

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相关实验视频

Updated: Jun 27, 2025

Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps
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Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps

Published on: July 19, 2024

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物理引导的深度生成模型用于新连接体发现.

Dikshant Sagar1, Ali Risheh1, Nida Sheikh2

  • 1Department of Computer Science, California State University, Los Angeles, Los Angeles, California, USA.

ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine
|May 6, 2024
PubMed
概括

这项研究引入了一种以物理为导向的药物发现深度生成模型,提高了连接体结合的亲和力和可行性. 这种新的方法通过结合物理原理来增强分子生成,优于现有的方法.

关键词:
深度学习是一种深度学习.药物发现 药物发现生成性神经网络是一种神经网络.隐式溶剂模型中的隐式溶剂模型

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Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
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Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

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相关实验视频

Last Updated: Jun 27, 2025

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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
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Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
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科学领域:

  • 计算化学是一种计算化学.
  • 分子建模分子建模
  • 药物发现 药物发现

背景情况:

  • 基于结构的药物发现寻求向特定蛋白质的分子.
  • 深度学习模型产生类似药物的分子,但往往忽视物理结合原理.
  • 纳入基础物理对于现实的分子形成和结合至关重要.

研究的目的:

  • 开发一种以物理为导向的深度生成模型,用于新型联体发现.
  • 在结合点和基于物理的结合机制特征上条件分子生成.
  • 提高药物发现过程的准确性和效率.

主要方法:

  • 开发了一种混合深度生成模型,整合了基于物理的特征.
  • 在受体结合部位和配体-受体相互作用物理上对模型进行了条件化.
  • 对大型蛋白质连接体复合体和小型宿主-客体系统进行了模型评估.

主要成果:

  • 物理导向模型产生了更强的结合物,超过75%的结合物超过了原始连接物亲和力.
  • 与最先进的方法相比,获得了1.88 kcal/mol的平均结合亲和力 (ΔG) 改进.
  • 与传统的深度学习模型相比,生成的连接体表现出更可行的构造和方向.

结论:

  • 物理引导的深度学习为增强的连接体发现提供了一个有前途的方法.
  • 该模型在预测高亲和度结合剂方面表现出卓越的性能.
  • 未来的工作包括扩大数据集和结合更多的生物物理见解.