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

Drug Discovery: Overview01:26

Drug Discovery: Overview

8.8K
Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
8.8K
Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

1.1K
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...
1.1K
Targets for Drug Action: Overview01:26

Targets for Drug Action: Overview

7.5K
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...
7.5K
Principles of Drug Action01:24

Principles of Drug Action

6.7K
Drugs are chemical substances that modify biological responses by interacting with macromolecular targets such as receptors, ion channels, transporters, and enzymes. Pharmacodynamics describes the course of action of drugs leading to the physiological effect at a specific site in the body.
Drugs can be agonists or antagonists. Like the endogenous ligands, agonists always bind and activate the target to produce a cellular response. Agonist binding induces a conformational change which in turn...
6.7K
Drug Clearance: Overview01:06

Drug Clearance: Overview

168
Drug elimination refers to drug removal from the body, either through urine or bile, by the kidneys or liver, respectively. A pharmacokinetic parameter, drug clearance, measures the efficiency of drug removal from the bloodstream within a specific time frame. It is calculated as the rate at which a drug is eliminated from plasma divided by the drug's concentration in plasma.
Drug clearance is not limited to renal excretion but encompasses all organs involved in drug elimination, including...
168
Drug Abuse and Addiction: Pharmacological Phenomena01:15

Drug Abuse and Addiction: Pharmacological Phenomena

663
Drug dependence, abuse, and addiction are complex phenomena that can precipitate various abnormal states. Physical dependence refers to a state of pharmacological adaptation to a drug. This adaptation often results in tolerance—a reduced response to the drug after repeated administrations. When the drug use is abruptly stopped, withdrawal symptoms occur due to the body's need to readjust from the pharmacologically induced imbalance. However, tolerance and withdrawal symptoms do not...
663

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

GHF-ACL: A novel contrastive learning framework with multi-order graph structures for herb-disease association prediction.

PLoS computational biology·2026
Same author

Identification and characterization of lncRNA-stemness-immune regulatory patterns.

Briefings in bioinformatics·2026
Same author

Hypoxia-Associated Alternative Polyadenylation of CARM1 and Tumor Microenvironment Alterations in Non-Small Cell Lung Cancer.

Genes·2026
Same author

DECODE: deep learning-based common deconvolution framework for various omics data.

Nature methods·2026
Same author

DL-GapFilling: a novel deep learning framework for improved plant genome gap filling.

Briefings in bioinformatics·2026
Same author

Reference-Guided Chromosome-by-Chromosome de novo Assembly at Scale Using Low-Coverage High-Fidelity Long-Reads with HiFiCCL.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2025

相关实验视频

Updated: Sep 18, 2025

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
05:10

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

9.7K

MGPT:用于药物发现的多任务图表快速学习框架.

Yang Li1, Youhan Sun1, Xinyu Qin1

  • 1College of Computer and Control Engineering, Northeast Forestry University, Hexing Road, Harbin, Heilongjiang, 150040, China.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|June 25, 2025
PubMed
概括

一个新的多任务图表提示 (MGPT) 模型改善了药物关联预测,特别是在有限的数据的情况下. 这种方法提供了强大的图形表示,用于药物开发中的少量学习.

关键词:
毒品协会 毒品协会不同质的图形网络网络.多任务提示符调整调整自主监督的对比学习学习.

更多相关视频

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery
06:26

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Published on: May 16, 2021

5.0K
Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
10:29

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

1.5K

相关实验视频

Last Updated: Sep 18, 2025

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
05:10

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

9.7K
Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery
06:26

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Published on: May 16, 2021

5.0K
Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
10:29

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

1.5K

科学领域:

  • 生物医学研究的研究.
  • 计算机化药物发现.
  • 图形表示学习学习学习图形表示.

背景情况:

  • 准确预测药物关联 (药物标,副作用,疾病关系) 对精准医学至关重要.
  • 图形表示学习方法越来越多地用于药物关联研究.
  • 在将图形预训练应用于药物开发方面存在挑战,特别是在多任务和少数射击学习方面.

研究的目的:

  • 提出一个统一的多任务图表提示符 (MGPT) 学习模型.
  • 提供可泛化和强大的图形表示,用于少数射击药物协会预测.
  • 解决药物开发中的多任务学习和有限数据场景的挑战.

主要方法:

  • 构建了一个异质图形网络,以实体对作为节点.
  • 在预培训期间,雇员自主监督对比式学习子图.
  • 利用可学习的功能提示,嵌入下游任务的任务特定知识.

主要成果:

  • 在各种药物协会任务中表现出强的表现.
  • 展示了无的任务切换功能.
  • 优于竞争方法的表现,特别是在短暂的学习场景中.

结论:

  • MGPT为药物开发中的多任务学习提供了强大的解决方案.
  • 该模型有效地解决了药物相关性预测中有限数据的挑战.
  • MGPT提供了可概括的图形表示,这对于推进精准医学至关重要.