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Ligand Binding Sites02:40

Ligand Binding Sites

12.7K
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...
12.7K
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
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
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
Protein-Drug Binding: Determination Methods01:22

Protein-Drug Binding: Determination Methods

108
Determining protein-drug binding can be achieved through indirect and direct methods, each providing valuable insights into the interaction between proteins and drugs.
Indirect methods involve isolating the bound drug from its free form in biological samples such as blood, serum, or plasma. These techniques aim to measure the percentage of drugs bound to proteins. Equilibrium dialysis is a commonly used method where the free drug concentration at equilibrium is measured by separating the bound...
108
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

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相关实验视频

Updated: May 27, 2025

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

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机器学习方法用于从序列数据中预测蛋白质-配体结合位点.

Orhun Vural1, Leon Jololian1

  • 1Department of Electrical and Computer Engineering, The University of Alabama at Birmingham, Birmingham, AL, United States.

Frontiers in bioinformatics
|February 18, 2025
PubMed
概括
此摘要是机器生成的。

本综述探讨了机器学习方法,用于仅使用蛋白质序列数据预测蛋白质-连接体结合位. 它强调了药物发现这一关键领域的最新进展,挑战和未来研究方向.

关键词:
有约束力的预测预测.计算机化药物发现.深度学习是一种深度学习.蛋白质 - 配体结合点的结合点.基于序列的方法 基于序列的方法

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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
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A Protocol for Computer-Based Protein Structure and Function Prediction
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A Protocol for Computer-Based Protein Structure and Function Prediction

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相关实验视频

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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA

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A Protocol for Computer-Based Protein Structure and Function Prediction
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A Protocol for Computer-Based Protein Structure and Function Prediction

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科学领域:

  • 生物化学和计算生物学
  • 专注于生物系统中的分子相互作用和计算方法.

背景情况:

  • 蛋白质通过相互作用部位,特别是蛋白质-连接体结合部位来执行重要的生物功能.
  • 准确预测这些地点对于计算药物发现和治疗开发至关重要.

研究的目的:

  • 审查机器学习研究,从序列数据中预测蛋白质-配体结合位点.
  • 检查该领域的最新进展,嵌入方法和机器学习架构.

主要方法:

  • 对基于序列的机器学习来预测蛋白质-配体结合位点的现有文献的审查.
  • 分析最近研究中使用的各种嵌入技术和神经网络架构.

主要成果:

  • 机器学习显著提高了从序列数据中预测蛋白质-连接体结合位点的准确性.
  • 确定了各种成功的嵌入方法和深度学习架构.

结论:

  • 基于序列的机器学习提供了一种强大的方法来预测蛋白质-连接体结合点.
  • 需要进一步的研究来应对当前的挑战,并探索未来的方向,以提高药物发现的准确性和应用.