Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Ligand Binding Sites02:40

Ligand Binding Sites

14.9K
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...
14.9K
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...
5.0K
Molecular Models02:00

Molecular Models

43.5K
Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
43.5K
Physiological Pharmacokinetic Models: Assumption with Protein Binding01:13

Physiological Pharmacokinetic Models: Assumption with Protein Binding

216
Physiological models with protein binding in pharmacokinetics offer a sophisticated approach to understanding drug disposition. These models consider drug-protein interactions, enabling them to effectively predict drug concentrations in different organs and tissues. This precision aids in accurate drug dosing, providing a significant advantage over conventional models. A key process within these models is equilibration, which ensures that drug concentrations achieve a steady state within the...
216
Cooperative Allosteric Transitions01:58

Cooperative Allosteric Transitions

8.6K
Cooperative allosteric transitions can occur in multimeric proteins, where each subunit of the protein has its own ligand-binding site. When a ligand binds to any of these subunits, it triggers a conformational change that affects the binding sites in the other subunits; this can change the affinity of the other sites for their respective ligands. The ability of the protein to change the shape of its binding site is attributed to the presence of a mix of flexible and stable segments in the...
8.6K
The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

14.9K
The equilibrium binding constant (Kb) quantifies the strength of a protein-ligand interaction. Kb can be calculated as follows when the reaction is at equilibrium:
14.9K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Photochemical Cascade Nitrile Activation via a Carbene-Nitrene Relay.

Angewandte Chemie (International ed. in English)·2026
Same author

Synthesis of Vinyl Sulfoxides and Subsequent Construction of C,S Contiguous Stereocenters Via Thia-Stevens Rearrangement of I<sup>III</sup>/S<sup>VI</sup>-Hybrid Ylides.

Organic letters·2026
Same author

Harnessing P<sup>V</sup>-oxirene for the modular synthesis of α-Oxy carbonyls.

Nature communications·2026
Same author

Towards large-scale chemical reaction image parsing <i>via</i> a multimodal large language model.

Chemical science·2025
Same author

Stereoselective diversification of α-amino acids enabled by N-heterocyclic carbene catalysis.

Nature communications·2025
Same author

Enantioselective intramolecular cyclopropanation via a cationic sulfoxonium-Rh-carbene.

Nature communications·2025

相关实验视频

Updated: Jan 18, 2026

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
09:17

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

Published on: March 1, 2022

3.6K

用层次一致性扩散模型生成用于蛋白结合的分子.

Guanlue Li1, Chenran Jiang2, Ziqi Gao3

  • 1Data Science and Analytics, The Hong Kong University of Science and Technology (Guang Zhou) Guangzhou 511400 China guanlueli@gmail.com.

Chemical science
|September 11, 2025
PubMed
概括

我们开发了一种新的AI模型,即原子动图一致性扩散模型 (AMDiff),用于生成有效和新型药物分子. 这种方法增强了针对特定蛋白质点的基于结构的药物设计.

更多相关视频

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells
06:48

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells

Published on: January 5, 2024

5.2K
Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps
09:30

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

Published on: July 19, 2024

2.0K

相关实验视频

Last Updated: Jan 18, 2026

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
09:17

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

Published on: March 1, 2022

3.6K
Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells
06:48

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells

Published on: January 5, 2024

5.2K
Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps
09:30

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

Published on: July 19, 2024

2.0K

科学领域:

  • 计算化学是一种计算化学.
  • 人工智能在药物发现中的作用
  • 分子建模分子建模

背景情况:

  • 产生有效和可靠的3D分子结构对于药物发现至关重要.
  • 当前的原子和动机智能模型面临着分子有效性和可靠性的挑战.
  • 弥合原子视图和动机视图的方法是必要的,以实现全面的分子生成.

研究的目的:

  • 开发一种先进的AI模型,用于有效的3D分子结构生成.
  • 为了提高药物发现产生的分子的有效性和可靠性.
  • 加快针对特定目标的候选药物的设计.

主要方法:

  • 开发了原子-动图一致性扩散模型 (AMDiff),使用多视图学习的联合培训范式.
  • 实现了分层扩散架构,集成了原子和动图视图.
  • 使用无分类器指导和拓特征作为条件输入.

主要成果:

  • 与现有方法相比,AMDiff在生成不同蛋白质口袋的分子方面表现出优越的有效性和新性.
  • 该模型成功生成了适合特定蛋白质标的分子.
  • 对无细胞性淋巴瘤激酶 (ALK) 和循环素依赖激酶4 (CDK4) 的案例研究表明,在基于结构的新药设计中具有有效性.

结论:

  • AMDiff有效地整合了原子和动图级别的信息,以实现强大的分子生成.
  • 该模型通过提高分子有效性和新性来增强基于结构的新药设计.
  • 在药物发现中,AMDiff加速了针对特定目标分子的开发.