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

Opioid Receptors: Overview01:22

Opioid Receptors: Overview

383
Opioid receptors, including the mu (μ, MOR), delta (δ, DOR), and kappa (κ, KOR) types, belong to the rhodopsin family of G protein-coupled receptors. These receptors are located throughout the central and peripheral nervous systems and in non-neuronal tissues such as macrophages and astrocytes. Opioid receptor ligands can be categorized into agonists or antagonists. Highly selective agonists include [d-Ala2, MePhe4, Gly(ol)5]-enkephalin or DAMGO for MOR, [D-Pen2,...
383
Analgesia and Pain Management01:25

Analgesia and Pain Management

403
Pain is critical to various clinical pathologies, provoking an urgent need for effective management. Pain, whether acute or chronic, is a complex neurochemical process. Its alleviation depends on the type, with nonopioid analgesics effective for mild to moderate pain, such as musculoskeletal or inflammatory pain, while neuropathic pain responds best to anticonvulsants, tricyclic antidepressants, or serotonin/norepinephrine reuptake inhibitors. For severe acute or chronic pain, opioids may be...
403
Opioid Analgesics: Synthetic and Semisynthetic Opioids01:15

Opioid Analgesics: Synthetic and Semisynthetic Opioids

189
Synthetic and semisynthetic opioids are pivotal in pain management and tackling opioid addiction. Semisynthetic opioids, including morphinans (morphine derivatives), oxycodone, oxymorphone, hydrocodone, and hydromorphone, have improved pharmacokinetic profiles compared to morphine. Additionally, heroin and 6-MAM (6-Monoacetylmorphine) show better CNS penetration than morphine due to heightened lipid solubility. Hydromorphone, a potent opioid, undergoes hepatic metabolism to form the active...
189
Opioid Analgesics: Morphine and Other Natural Cogeners01:20

Opioid Analgesics: Morphine and Other Natural Cogeners

146
Opioids are a class of drugs that mimic endogenous opioid peptides and act on opioid receptors, and help in pain relief. These compounds are classified as natural, synthetic, or semi-synthetic. Natural opioids, like morphine, codeine, and thebaine, are derived from the opium poppy plant (Papaver somniferum or Papaver album) and are termed opiates. Synthetic opioids are artificial, while semi-synthetic opioids combine natural and synthetic compounds. Morphine, a prototypical opioid, possesses a...
146
The Two-State Receptor Model01:29

The Two-State Receptor Model

1.8K
The two-state receptor model explains a drug's interaction with receptors, such as G protein-coupled receptors and ligand-gated ion channels, to induce or inhibit a biological response. When no natural ligands are present, a receptor exists in an equilibrium of inactive (Ri) and active (Ra) conformations. The inactive form does not produce a response, while the active form generates a basal effect known as constitutive activity.
The binding affinity of a drug determines its interaction with...
1.8K
Drug Abuse and Addiction: Pharmacological Phenomena01:15

Drug Abuse and Addiction: Pharmacological Phenomena

414
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...
414

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

Hydrogen Radical-Mediated Nitric Oxide Reduction to Ammonia Over Synergistic Pd<sup>0</sup>/Pd<sup>2+</sup> Dual Sites.

Angewandte Chemie (International ed. in English)·2026
Same author

Simultaneous CO<sub>2</sub> and NO Conversion by Spatially Locating Dual Photocatalytic Sites on a Microporous Polymer.

Environmental science & technology·2026
Same author

A Missing Source of Atmospheric NO<sub>2</sub><sup>-</sup>: Heterogeneous Dark Transformation of PAN on Industrial Mineral Dust.

Environmental science & technology·2026
Same author

Surface Energy Modulation of NiO<sub><i>x</i></sub> through In Situ Click-Cross-Linked Networks for Air-Processed Flexible Blue Perovskite Light-Emitting Diodes.

The journal of physical chemistry. A·2026
Same author

RUNX2 drives adenoma-to-carcinoma transition in colon cancer.

Cell death & disease·2026
Same author

Abnormal Activation and Connection in Middle Frontal Gyrus: A Potential Imaging Feature for Facial Synkinesis Comorbid Depression.

Depression and anxiety·2026

相关实验视频

Updated: May 17, 2025

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
16:02

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation

Published on: February 10, 2023

2.6K

使用机器学习和深度学习技术开发μ阿片类受体结合的预测模型.

Jie Liu1, Jerry Li2, Zoe Li1

  • 1U.S. Food and Drug Administration, National Center for Toxicological Research, Jefferson, AR, United States.

Experimental biology and medicine (Maywood, N.J.)
|April 3, 2025
PubMed
概括
此摘要是机器生成的。

开发了机器学习模型来预测μ阿片类受体 (MOR) 结合活性. 这些模型可以帮助识别与MOR结合的化学物质,可能导致非成性止痛药.

关键词:
具有约束力的活动活动.深度学习是一种深度学习.机器学习是机器学习.预测模型是一个预测模型.片类受体受体

更多相关视频

Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis
07:48

Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis

Published on: July 3, 2015

8.7K
Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
10:21

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

Published on: February 23, 2024

2.3K

相关实验视频

Last Updated: May 17, 2025

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
16:02

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation

Published on: February 10, 2023

2.6K
Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis
07:48

Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis

Published on: July 3, 2015

8.7K
Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
10:21

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

Published on: February 23, 2024

2.3K

科学领域:

  • 计算化学是一种计算化学.
  • 药理学 药理学是指药理学的学科.
  • 机器学习 机器学习

背景情况:

  • 阿片类药物通过激活μ阿片类受体 (MOR) 来缓解疼痛,但它们的成性质有助于持续的阿片类危机.
  • 了解化学结构和MOR结合之间的关系对于开发更安全的止痛药至关重要.
  • 预测模型可以加速发现非成或不那么成的阿片类药物疼痛疗法.

研究的目的:

  • 开发和评估机器学习 (ML) 和深度学习 (DL) 模型,用于预测化学化合物的MOR结合活性.
  • 评估各种ML算法的性能,以识别潜在的MOR配体.
  • 调查预测信心和适用性领域分析对模型解释的实用性.

主要方法:

  • 从公共数据库和文献中整理了一组具有已知的MOR结合活性的化学物质数据集.
  • 使用Mold2软件计算每个化学品的分子描述符.
  • 训练并验证了多个ML模型,包括随机森林,k-最近邻居,支持矢量机,多层感知器和长短期内存,使用5倍交叉验证和外部验证集.

主要成果:

  • 开发的模型实现了马修斯相关系数 (MCC),在交叉验证中从0.528到0.654,在外部验证中达到0.408.
  • 预测信心和适用性领域分析被确定为模型可靠性的重要因素.
  • 这些模型显示了识别具有MOR结合能力的化学物质的潜力.

结论:

  • 开发的ML和DL模型显示了预测MOR结合活性的前景.
  • 这些预测工具可以帮助查和识别新型MOR结合剂.
  • 这些发现支持潜在开发更安全,非成性止痛药,以MOR途径为目标.