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

Molecular Models02:00

Molecular Models

Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
Predicting Molecular Geometry02:27

Predicting Molecular Geometry

VSEPR Theory for Determination of Electron Pair Geometries
Mass Spectrometry: Molecular Fragmentation Overview01:20

Mass Spectrometry: Molecular Fragmentation Overview

The ionization of a molecule into a molecular ion inside the mass spectrometer causes instability in the molecule's structure due to the loss of an electron. This eventually leads to the fragmentation or breaking of some bonds in the molecule. The fragmentation occurs predominantly at specific bonds to yield relatively stable fragments.
One type of fragmentation pattern is the cleavage of a single bond in the molecular ion. The cleavage leads to a radical and a cation. The cleavage can occur at...

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

Structural basis of Mlc-mediated transcriptional regulation of carbohydrate metabolism.

Nature communications·2026
Same author

From unsupervised selection of AIMs to likelihood-based BGA inference: Challenges revealed by OpenADMIXTURE and GENOGEOGRAPHER.

Forensic science international. Genetics·2026
Same author

Deep generative modeling captures maturation-dependent pairing patterns in human antibodies.

iScience·2026
Same author

Beyond performance: how design choices shape chemical language models.

Journal of cheminformatics·2025
Same author

Structural basis of drug recognition by human MATE1 transporter.

Nature communications·2025
Same author

Large transient assemblies of Apaf1 constitute the apoptosome in cells.

Nature communications·2025

相关实验视频

Updated: May 10, 2026

Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin
06:29

Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin

Published on: March 3, 2021

5.4K

构建AMol:用于基于片段的分子设计的多功能Python工具包.

Noah Kleinschmidt1, Thomas Lemmin2

  • 1Institute of Biochemistry and Molecular Medicine, University of Bern, Buehlstrasse 28, 3012, Bern, Switzerland.

Journal of cheminformatics
|August 25, 2024
PubMed
概括

BuildAMol是一个灵活的Python工具包用于分子建模,允许专家驱动的各种分子结构的构建. 它支持各种应用,从金属复合物到药物发现管道,推进计算生物学.

关键词:
基于碎片的分子组件组件.分子建模分子建模在这里,Python是Python.超分子建模 超分子建模

更多相关视频

NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode
09:19

NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode

Published on: June 4, 2021

3.2K
Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids
08:21

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

2.6K

相关实验视频

Last Updated: May 10, 2026

Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin
06:29

Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin

Published on: March 3, 2021

5.4K
NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode
09:19

NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode

Published on: June 4, 2021

3.2K
Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids
08:21

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

2.6K

科学领域:

  • 计算生物学是一种计算生物学.
  • 化学信息学 化学信息学
  • 分子建模分子建模

背景情况:

  • 现有的分子建模系统往往专门用于特定的分子类 (例如蛋白质,连接体),并且缺乏专家驱动组装的灵活性.
  • 当前的手动或半自动工具在它们可以生成的结构范围上有局限性.

研究的目的:

  • 介绍BuildAMol,一个通用,基于碎片的分子组装工具包,旨在提供灵活性和可扩展性.
  • 赋予研究人员一个用户友好的API,用于详细的手动或半自动构建各种分子模型.

主要方法:

  • 开发了BuildAMol作为一个基于Python的工具包,具有完善的文档,用户友好的API.
  • 通过各种使用案例展示了多功能性,包括金属复合体生成,树突模拟和整合到药物发现管道中.

主要成果:

  • 构建AMol为专家驱动的分子模型构建提供了一个强大的框架.
  • 该工具包将建模,修改,优化和可视化功能集成到一个统一的API中.
  • 促进与其他化学信息图书馆的协作,并具有浅的学习曲线.

结论:

  • BuildAMol为分子建模提供了一种多功能且易于使用的解决方案,满足广泛的应用.
  • 它是促进分子研究和创新的宝贵工具,包括深度学习技术的整合.