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

Newman Projections02:06

Newman Projections

16.2K
Different notations are used to represent the three-dimensional structure of molecules on two-dimensional surfaces. One of the most commonly used representations is the dash-wedge formula. The dashed wedges, solid wedges, and the plane lines indicate the groups situated behind the plane, coming out of the plane, and in the plane, respectively.
The organic molecules rotate across the single bonds leading to numerous temporary three-dimensional structures of varying energy known as...
16.2K
Molecular Shapes01:18

Molecular Shapes

56.6K
Molecules have characteristic shapes that are crucial for their function. The arrangement of various electron groups around the central atom dictates their molecular geometry. Electron pairs in the valence shell of a central atom will adopt an arrangement that minimizes repulsions between the electron pairs by maximizing the distance between them. The valence electrons form either bonding pairs, located primarily between bonded atoms, or lone pairs.
Two regions of electron density in a diatomic...
56.6K
Molecular Models02:00

Molecular Models

37.7K
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.
37.7K
Fischer Projections02:18

Fischer Projections

12.9K
Learning to draw Fischer projections of molecules and understanding their relevance plays a crucial role in the visual depiction of organic molecules. A Fischer projection is a two-dimensional projection on a planar surface to simplify the three-dimensional wedge–dash representation of molecules. This is especially helpful in the case of molecules with multiple chiral centers that can be difficult to draw. Here, all the bonds of interest are represented as horizontal or vertical lines.
12.9K
Molecular Geometry and Dipole Moments02:36

Molecular Geometry and Dipole Moments

12.4K
The VSEPR theory can be used to determine the electron pair geometries and molecular structures as follows:
12.4K
Lewis Structures of Molecular Compounds and Polyatomic Ions02:54

Lewis Structures of Molecular Compounds and Polyatomic Ions

34.3K
To draw Lewis structures for complicated molecules and molecular ions, it is helpful to follow a step-by-step procedure as outlined:
34.3K

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

Coarse-Grained Simulations Reveal Salt- and Length-Dependent Condensation of G4C2 RNA Repeats.

The journal of physical chemistry letters·2026
Same author

Lipid Composition Determines Hybrid Nanoparticle Selectivity: Beyond Membrane Mimicry in Cancer Targeting.

Nano letters·2026
Same author

Ultrasound-responsive liposomes: A mechanistic framework to decode the effects of acoustic parameters.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

The Role of Water Volume Fraction on Water Adsorption in Anion Exchange Membranes.

Macromolecules·2026
Same author

Coarse-Grained Martini 3 Model of Chondroitin Sulfate A.

Journal of chemical theory and computation·2026
Same author

Martini 3 Building Blocks for Lipid Nanoparticle Design.

Journal of chemical theory and computation·2025

相关实验视频

Updated: May 20, 2025

Line Shape Analysis of Dynamic NMR Spectra for Characterizing Coordination Sphere Rearrangements at a Chiral Rhenium Polyhydride Complex
10:52

Line Shape Analysis of Dynamic NMR Spectra for Characterizing Coordination Sphere Rearrangements at a Chiral Rhenium Polyhydride Complex

Published on: July 27, 2022

2.6K

CGsmiles:用于多个分辨率的分子表示的多功能线条符号.

Fabian Grünewald1,2, Leif Seute1, Riccardo Alessandri3

  • 1Heidelberg Institute for Theoretical Studies (HITS), Schloss-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany.

Journal of chemical information and modeling
|March 24, 2025
PubMed
概括

我们介绍了CGsmiles,这是粗粒度 (CG) 模型的新符号,可以有效地进行化学空间探索和多分辨率分子表示. 这种格式解决了当前方法的局限性,促进了高通量选和机器学习应用.

更多相关视频

Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps
09:30

Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps

Published on: July 19, 2024

1.1K
Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs
05:00

Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs

Published on: August 9, 2024

837

相关实验视频

Last Updated: May 20, 2025

Line Shape Analysis of Dynamic NMR Spectra for Characterizing Coordination Sphere Rearrangements at a Chiral Rhenium Polyhydride Complex
10:52

Line Shape Analysis of Dynamic NMR Spectra for Characterizing Coordination Sphere Rearrangements at a Chiral Rhenium Polyhydride Complex

Published on: July 27, 2022

2.6K
Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps
09:30

Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps

Published on: July 19, 2024

1.1K
Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs
05:00

Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs

Published on: August 9, 2024

837

科学领域:

  • 计算化学的计算化学
  • 化学信息学 化学信息学
  • 材料科学 材料科学 材料科学

背景情况:

  • 粗粒度 (CG) 模型简化了分子表示,以实现更快的模拟,这对于高通量 (HT) 选和探索广的化学空间至关重要.
  • 现有的CG模型缺乏用于描述原子分组 (映射) 的标准化数据格式,这阻碍了可扩展性和数据共享.
  • 马蒂尼力场是CG模型的例子,但需要强大的符号来实现其不断增长的分子图书馆.

研究的目的:

  • 介绍CGsmiles,一种用于表示粗粒度分子及其等级关系的新型线符号.
  • 解决当前粗粒度建模中缺乏标准化映射和索引功能的问题.
  • 证明CGsmiles在促进多解析度分析和机器学习应用中的实用性.

主要方法:

  • 开发了CGsmiles,这是一种以SMILES和BigSMILES为灵感的线条符号,编码分子图和粒子属性.
  • 整合了一个框架,在单个字符串内,在粗粒度和细粒度分辨率之间进行无转换.
  • 使用CGsmiles语法分析了马蒂尼力场的407个分子的基准集.

主要成果:

  • CGsmiles成功地编码了分子图和粒子属性,独立于分辨率.
  • 该符号可以在单个字符串中表示多个分辨率和层次关系.
  • 通过构建机器学习模型来使用多分辨率数据预测分区系数,证明了CGsmiles的实用性.

结论:

  • CGsmiles为描述粗粒度模型及其映射提供了一种通用而严格的解决方案.
  • 该符号克服了粗粒度建模中的重大障碍,使真正的高通量能力成为可能.
  • CGsmiles适用于聚合物和其他复杂系统,增强分子模拟和数据分析.