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相关概念视频

Molecules with Multiple Chiral Centers02:25

Molecules with Multiple Chiral Centers

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Molecules that possess multiple chiral centers can afford a large number of stereoisomers. For instance, while some molecules like 2-butanol have one chiral center, defined as a tetrahedral carbon atom with four different substituents attached, several molecules like butane-2,3-diol have multiple chiral centers. A simple formula to predict the number of stereoisomers possible for a molecule with n chiral centers is 2n. However, there can be a lower number where some of the stereoisomers are...
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Predicting Molecular Geometry02:27

Predicting Molecular Geometry

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VSEPR Theory for Determination of Electron Pair Geometries
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Molecular Models02:00

Molecular Models

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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.
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Chemical Shift: Internal References and Solvent Effects01:17

Chemical Shift: Internal References and Solvent Effects

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In an NMR sample, precise measurement of the absolute absorption frequencies of nuclei is difficult. A standard internal reference compound is added, and the frequency difference between the reference signal and sample signals is measured.
The internal reference compound generally used in NMR spectroscopy is tetramethylsilane (TMS). TMS is preferred because it is chemically inert, soluble in NMR solvents, and easily removable. Also, the highly shielded methyl protons in TMS yield an intense...
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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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Molecular Geometry and Dipole Moments02:36

Molecular Geometry and Dipole Moments

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The VSEPR theory can be used to determine the electron pair geometries and molecular structures as follows:
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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
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进化多目标分子优化在一个隐含的化学空间.

Xin Xia1,2, Yiping Liu3, Chunhou Zheng1

  • 1The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, School of Artificial Intelligence, Anhui University, Hefei 230601, China.

Journal of chemical information and modeling
|June 13, 2024
PubMed
概括
此摘要是机器生成的。

我们开发了一种新的多目标分子优化框架 (MOMO),以设计具有多个优化性质的药物分子. 莫莫产生多样化,新和高性质的分子,在药物发现中表现优于现有的方法.

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科学领域:

  • 计算化学计算化学
  • 药物发现 药物发现 药物发现
  • 生物信息学是一种生物信息学.

背景情况:

  • 在药物开发中,生成方法对于设计优化分子至关重要.
  • 目前的方法难以同时优化多种药物特性,同时确保多样性和新性.

研究的目的:

  • 引入一个新的多目标分子优化框架 (MOMO).
  • 解决现有方法在产生多样化,新和高性质分子的局限性,具有多个优化属性.

主要方法:

  • 在分子序列层面上,MOMO使用了基于帕雷托的多性质评估策略.
  • 一个进化的搜索是指导在一个隐含的化学空间.

主要成果:

  • 在基准任务上,MOMO在多样性,新性和优化性质方面显著优于五种最先进的方法.
  • 在四个现实世界药物发现挑战中验证了实际应用.

结论:

  • 莫莫为涉及多种性质的分子优化问题提供了强大的解决方案.
  • 该框架可以成为加速药物发现和开发的宝贵工具.