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相关概念视频

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
Targets for Drug Action: Overview01:26

Targets for Drug Action: Overview

6.0K
Drugs target macromolecules to modify ongoing cellular processes. Primary drug targets include receptors, ion channels, transporters, and enzymes.
Receptors are either membrane-spanning or intracellular proteins, which upon binding a ligand, get activated and transmit the signal downstream to elicit a response. Drugs bind receptors, either mimicking the action of endogenous ligands or blocking the receptor activity to bring about a modified response. Nearly 35% of approved drugs target the G...
6.0K
Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

480
Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence...
480
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

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相关实验视频

Updated: May 24, 2025

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

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通过深度多模式图和结构性学习来预测药物向相互作用.

Haorun Li, Zhihang Hu

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 5, 2025
    PubMed
    概括

    这项研究引入了一种用于药物向相互作用 (DTI) 预测的新框架,通过整合多式联络数据和结构性学习来提高药物发现,以提高准确性和通用性.

    科学领域:

    • 生物医学信息学 生物医学信息学
    • 计算生物学 计算生物学
    • 药物发现 药物发现 药物发现

    背景情况:

    • 现有的药物向相互作用 (DTI) 预测框架往往无法捕捉相互作用的多式联络性质,并且缺乏可概括性.
    • 先进的特征表示和考虑分子级结构对于强大的DTI预测至关重要.

    研究的目的:

    • 开发一种用于药物向相互作用 (DTI) 预测的新,可概括的框架,解决以前方法的局限性.
    • 通过增强DTI预测,提高药物重定向,查和设计的效率.

    主要方法:

    • 一个多模式图形神经网络结合使用模型组合的直接分子级结构学习.
    • 利用了包括药物,蛋白质,疾病和途径在内的多模式生物医学数据集,并从语言模型和知识图中嵌入功能.
    • 集成了一个结构性学习模块,用于独立于图表模块的分子级信息.

    主要成果:

    • 与对现实数据集的基准DTI预测框架相比,拟议的框架表现优越.
    • 该模型在独立数据集上表现出强大的概括性,准确预测未见药物和蛋白质的相互作用.

    结论:

    • 新的框架在药物向相互作用预测方面取得了重大进展,优于现有的方法.

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  • 该模型的通用性和可扩展性到其他生物医学链接预测任务,如药物相互作用,突出其潜在的影响.