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相关概念视频

Drug Discovery: Overview01:26

Drug Discovery: Overview

7.2K
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...
7.2K
Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

467
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...
467
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
Targets for Drug Action: Overview01:26

Targets for Drug Action: Overview

5.9K
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...
5.9K
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
Drug-Receptor Interactions01:29

Drug-Receptor Interactions

4.7K
Drug-receptor interaction describes the binding of receptors by drugs, but not all drug-receptor interactions result in activation and tissue response. For instance, the binding of agonists activates the receptor to generate a cellular reaction, while antagonists bind to receptors without causing their activation.
Several parameters, such as the drug's affinity for its receptor and its efficacy, which is its ability to activate the receptor, determine the drug's effect on the tissue....
4.7K

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相关实验视频

Updated: May 17, 2025

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
08:31

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

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MHNfs:促进低数据药物发现的背景生物活性预测.

Johannes Schimunek1, Sohvi Luukkonen1, Günter Klambauer1

  • 1ELLIS Unit Linz and LIT AI Lab, Institute for Machine Learning, Johannes Kepler University Linz, A-4040 Linz, Austria.

Journal of chemical information and modeling
|April 30, 2025
PubMed
概括

药物发现面临着数据稀缺的挑战. 一个新的应用程序MHNfs使用少量射击学习来预测有限数据的分子活动,加速候选者识别.

科学领域:

  • 计算化学是一种计算化学.
  • 机器学习在药物发现中的作用
  • 生物信息学是一种生物信息学.

背景情况:

  • 药物发现越来越多地利用计算和机器学习 (ML) 方法.
  • 这些方法的一个重大障碍是缺乏高质量的数据.
  • 解决数据局限性对于推进计算药物发现至关重要.

研究的目的:

  • 介绍MHNfs,这是一个用于在低数据设置中进行分子活动预测的应用程序.
  • 为研究人员提供一个可访问的工具,以便在药物发现中利用少数人学习.
  • 为了使用最小已知的分子数据来实现精确的活动预测.

主要方法:

  • 开发了MHNfs应用程序,结合了最先进的几次射击学习模型.
  • 使用MHNfs模型,该模型在FS-Mol基准数据集上表现强.
  • 模拟现实世界药物发现场景,通过将PubChem生物测试调整为少量预测任务.

主要成果:

  • MHNfs模型在一些射击活动预测任务中取得了强的表现.
  • 该应用程序为用户提供了一个直观的界面,以获得分子活动预测.
  • 使用调整的PubChem生物测试进行的评估证实了该应用在数据不足的情况下的有效性.

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

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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

Published on: February 23, 2024

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相关实验视频

Last Updated: May 17, 2025

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
08:31

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

4.9K
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

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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

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结论:

  • MHNfs为部署先进的几次射击学习模型提供了一种简化和可访问的解决方案.
  • 该应用程序有效地解决了在计算药物发现中数据稀缺的挑战.
  • MHNfs是加速识别新药候选药物的宝贵工具.