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相关概念视频

Crystal Field Theory - Octahedral Complexes02:58

Crystal Field Theory - Octahedral Complexes

25.8K
Crystal Field Theory
To explain the observed behavior of transition metal complexes (such as colors), a model involving electrostatic interactions between the electrons from the ligands and the electrons in the unhybridized d orbitals of the central metal atom has been developed. This electrostatic model is crystal field theory (CFT). It helps to understand, interpret, and predict the colors, magnetic behavior, and some structures of coordination compounds of transition metals.
CFT focuses on...
25.8K
Predicting Molecular Geometry02:27

Predicting Molecular Geometry

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VSEPR Theory for Determination of Electron Pair Geometries
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Crystal Field Theory - Tetrahedral and Square Planar Complexes02:46

Crystal Field Theory - Tetrahedral and Square Planar Complexes

40.8K
Tetrahedral Complexes
Crystal field theory (CFT) is applicable to molecules in geometries other than octahedral. In octahedral complexes, the lobes of the dx2−y2 and dz2 orbitals point directly at the ligands. For tetrahedral complexes, the d orbitals remain in place, but with only four ligands located between the axes. None of the orbitals points directly at the tetrahedral ligands. However, the dx2−y2 and dz2 orbitals (along the Cartesian axes) overlap with the ligands less than...
40.8K
Noncovalent Attractions in Biomolecules02:35

Noncovalent Attractions in Biomolecules

17.4K
17.4K
Crystal Growth: Principles of Crystallization01:25

Crystal Growth: Principles of Crystallization

1.4K
Crystallization is a phase transformation process in which crystals are precipitated from a supersaturated solution or formed from other sources. During crystallization, atoms or molecules arrange themselves into a well-defined, rigid crystal lattice to minimize energy.
Initiating crystallization involves manipulating the concentration of the solute and the temperature of the solution. Since crystal growth occurs when the ratio of concentration and solubility of the solute in the solvent...
1.4K

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相关实验视频

Updated: May 14, 2025

Crystallization and Structural Determination of an Enzyme:Substrate Complex by Serial Crystallography in a Versatile Microfluidic Chip
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Crystallization and Structural Determination of an Enzyme:Substrate Complex by Serial Crystallography in a Versatile Microfluidic Chip

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深层超分子语言处理用于共同晶体预测.

Rebecca Birolo1, Rıza Özçelik1, Andrea Aramini2

  • 1Eindhoven University of Technology: Technische Universiteit Eindhoven, Biomedical Engineering, NETHERLANDS, KINGDOM OF THE.

Angewandte Chemie (International ed. in English)
|May 13, 2025
PubMed
概括
此摘要是机器生成的。

DeepCocrystal是一个新的深度学习模型,可以预测药物联合晶体的形成,准确度为78%. 这种人工智能工具通过识别有前途的共同晶体对来加速药物开发,有助于发现新的药物配方.

关键词:
化学语言处理 化学语言处理共同结晶的结晶化深度学习是一种深度学习.可以解释的人工智能AI超分子化学 超分子化学

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Combining Wet and Dry Lab Techniques to Guide the Crystallization of Large Coiled-coil Containing Proteins
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Fully Autonomous Characterization and Data Collection from Crystals of Biological Macromolecules
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Crystallization and Structural Determination of an Enzyme:Substrate Complex by Serial Crystallography in a Versatile Microfluidic Chip
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Combining Wet and Dry Lab Techniques to Guide the Crystallization of Large Coiled-coil Containing Proteins
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Fully Autonomous Characterization and Data Collection from Crystals of Biological Macromolecules
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Fully Autonomous Characterization and Data Collection from Crystals of Biological Macromolecules

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科学领域:

  • 制药科学 制药科学
  • 计算化学计算化学
  • 药物发现 药物发现 药物发现

背景情况:

  • 低于最佳的药物动力学特征影响了大约40%的商业化药物.
  • 同结晶增强药物的物理化学特性,而不会影响药理活性.
  • 鉴定合适的共同晶体对是具有挑战性的,因为大量的分子组合.

研究的目的:

  • 开发一种新的深度学习方法,DeepCocrystal,用于预测共晶形成.
  • 从超分子的角度处理化学信息,使用化学语言处理.
  • 加速发现新的共同晶体,以改善药物开发.

主要方法:

  • 开发了DeepCocrystal,这是一个使用分子字符串表示的深度学习模型.
  • 训练并验证了预测共同晶体形成的模型.
  • 采用可解释的AI来理解模型的决策过程.
  • 将不确定性估计集成到预测框架中.

主要成果:

  • 在现实的预测场景中,DeepCocrystal实现了78%的平衡精度,超过了现有的模型.
  • 可解释的人工智能证实,该模型学习了化学相关的超分子特征.
  • 该模型在一项前性研究中成功识别了两种新的diflunisal联合晶体.
  • 不确定性估计指导了潜在发现过程.

结论:

  • DeepCocrystal有效地预测了共同晶体的形成,加速了有前途的候选药物的识别.
  • 深度学习和化学语言处理为制药研究提供了强大的工具.
  • 开发的模型及其网络应用程序可以使学术和工业药物开发工作受益.