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相关概念视频

Protein-protein Interfaces02:04

Protein-protein Interfaces

13.2K
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...
13.2K
Ligand Binding Sites02:40

Ligand Binding Sites

13.2K
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...
13.2K
Protein Networks02:26

Protein Networks

4.1K
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,...
4.1K
Conserved Binding Sites01:49

Conserved Binding Sites

4.4K
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...
4.4K
Protein-Protein Interfaces02:04

Protein-Protein Interfaces

3.8K
3.8K
Proteomics01:33

Proteomics

7.9K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
7.9K

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相关实验视频

Updated: Sep 11, 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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使用蛋白质语言模型进行蛋白质与金属结合预测的深度学习框架.

Fairuz Shadmani Shishir, Bishnu Sarker, Farzana Rahman

    IEEE transactions on computational biology and bioinformatics
    |August 14, 2025
    PubMed
    概括

    这项研究引入了一个深度学习框架,用于预测蛋白质-金属离子结合点,提高准确性和效率. 该模型捕捉了残留物依赖性和位置信息,优于关键金属离子的传统方法.

    科学领域:

    • 计算生物学是一种计算生物学.
    • 生物信息学是一种生物信息学.
    • 结构生物学是结构生物学.

    背景情况:

    • 手动固金属结合点是劳动密集型和耗时的.
    • 准确预测蛋白质 - 金属离子相互作用对于理解蛋白质功能和机制至关重要.
    • 现有的计算方法往往无法捕获远程残留依赖和位置信息.

    研究的目的:

    • 开发一个端到端的深度学习框架,用于预测蛋白质-金属离子结合点.
    • 评估最先进的蛋白质语言模型 (pLMs) 对此任务的性能.
    • 评估位置编码的影响,并与经典机器学习技术进行比较.

    主要方法:

    • 使用大型语言模型 (LLM) 进行金属离子结合预测.
    • 对比了五种不同的蛋白质语言模型 (pLMs).
    • 嵌入了绑定站点的位置编码,并与经典机器学习方法进行了评估.

    主要成果:

    • 使用十倍交叉验证,获得了0.89的马修斯相关系数 (MCC).
    • 六种常见金属离子的精度,回忆和F1得分超过95%.
    • 拟议的深度学习框架有效地捕捉了残留物依赖性和位置信息.

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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

    Published on: November 3, 2011

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    相关实验视频

    Last Updated: Sep 11, 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

    Published on: January 26, 2024

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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

    Published on: November 3, 2011

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    结论:

    • 开发的深度学习框架提供了一个高度准确和高效的方法来预测蛋白质-金属离子结合点.
    • 该研究强调了位置编码和先进的语言模型在提高预测准确性的重要性.
    • 这种计算管道为注释未表征的蛋白质和推进金属蛋白功能研究提供了有价值的工具.