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相关概念视频

Ligand Binding Sites02:40

Ligand Binding Sites

12.6K
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...
12.6K
Protein-protein Interfaces02:04

Protein-protein Interfaces

12.4K
Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
12.4K
Protein Networks02:26

Protein Networks

3.9K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
3.9K
Conserved Binding Sites01:49

Conserved Binding Sites

4.1K
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...
4.1K
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

4.7K
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...
4.7K
The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

12.7K
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:
12.7K

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基于Spectra描述器的机器学习用于预测蛋白质-连接体相互作用.

Cheng Chen1, Ledu Wang1, Yi Feng1

  • 1State Key Laboratory of Precision and Intelligent Chemistry, University of Science and Technology of China Hefei Anhui 230026 China sfeng18@ustc.edu.cn.

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概括
此摘要是机器生成的。

我们开发了一种新的分子描述器,即碎片集成光谱描述器 (FISD),以改进用于药物发现的机器学习. 通过捕获分子和蛋白质信息,FISD增强了虚拟选,加速了化合物识别.

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A Protocol for Computer-Based Protein Structure and Function Prediction
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科学领域:

  • 计算化学是一种计算化学.
  • 药物发现 药物发现
  • 机器学习是机器学习.

背景情况:

  • 机器学习模型对于识别药物化合物至关重要.
  • 目前的模型缺乏可靠的,基于物理化学的分子描述器.
  • 现有的方法难以捕获复杂的空间和电子分子信息.

研究的目的:

  • 介绍碎片集成光谱描述器 (FISD) 作为一种新的物理化学描述器.
  • 增强用于药物发现的虚拟查模型.
  • 在机器学习中改进分子和蛋白质的表示.

主要方法:

  • 使用空间和电子结构信息开发了碎片集成光谱描述器 (FISD).
  • 集成的FISD与经典的神经网络模型.
  • 验证了模型的性能与传统描述符和复杂模型相比.
  • 应用FISD来预测和选蛋白标的潜在配体.

主要成果:

  • 与经典神经网络相结合的FISD实现了与复杂模型可比的性能.
  • 新型描述器有效地利用空间和电子分子数据.
  • 证明了对两个蛋白质标的潜在结合配体的成功预测和选.
  • 在虚拟选中,FISD显示了广泛的适用性和实用性.

结论:

  • FISD代表了机器学习分子和蛋白质表示的重大进步.
  • 这个描述符通过提高虚拟查效率来加速药物发现过程.
  • FISD为分子描述器提供了一种更可靠和基于物理化学的方法.