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

Ribosome Profiling02:24

Ribosome Profiling

3.5K
Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
3.5K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

53
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...
53
Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

10.8K
Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to...
10.8K
Ligand Binding Sites02:40

Ligand Binding Sites

12.8K
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...
12.8K
Conserved Binding Sites01:49

Conserved Binding Sites

4.2K
Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
4.2K

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

Deep Learning Models Capture Umbrella Sampling-Derived Energetic Trends: A Troponin C Case Study.

Journal of chemical information and modeling·2026
Same author

Prediction of pre- and postfusion conformations of class I fusion proteins with AlphaFold2.

PloS one·2026
Same author

Structure-guided compound prioritization strategy for virtual screening identifies putative binders for the nuclear receptor LRH-1.

bioRxiv : the preprint server for biology·2026
Same author

Profiling the CFTR Variant Selectivity and Off-Target Interactions of VX-121.

bioRxiv : the preprint server for biology·2026
Same author

EGFR S442 ectodomain mutation confers cetuximab resistance that can be overcome by ERBB2 blockade with trastuzumab-deruxtecan.

Cancer letters·2026
Same author

Lanthipeptide structure prediction and design with Rosetta.

Methods in enzymology·2026

相关实验视频

Updated: Jun 29, 2025

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

17.0K

将罗塞塔序列设计与蛋白质语言模型预测相结合,使用进化规模建模 (ESM) 作为限制.

Moritz Ertelt1,2, Jens Meiler1,2,3,4, Clara T Schoeder1,2

  • 1Institute for Drug Discovery, University Leipzig Medicine Faculty, Liebigstr. 19, D-04103 Leipzig, Germany.

ACS synthetic biology
|April 3, 2024
PubMed
概括

这项研究将机器学习语言模型与蛋白质设计工具相结合. 新方法通过使用进化见解来改进稳定和功能性蛋白质的设计.

关键词:
罗塞塔 (Rosetta) 是一个计算型蛋白质设计它们是de novo蛋白质.进化健身 进化的健身蛋白质语言模型蛋白质语言模型的模型热力学稳定性 热力学稳定性

更多相关视频

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
06:50

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

1.8K
Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

7.3K

相关实验视频

Last Updated: Jun 29, 2025

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

17.0K
Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
06:50

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

1.8K
Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

7.3K

科学领域:

  • 计算生物学是一种计算生物学.
  • 蛋白质工程是一种蛋白质工程.
  • 在生物信息学中的机器学习.

背景情况:

  • 通过计算来设计稳定和功能性蛋白质是具有挑战性的,因为难以预测蛋白质动力学和质.
  • 进化信息有助于蛋白质设计,重点关注与原生类似的序列,增强稳定性和功能.
  • 最近的蛋白质语言模型擅长预测突变效应,但初步评估显示设计序列的得分较低.

研究的目的:

  • 通过将蛋白质语言模型的预测整合到现有的设计协议中来增强计算蛋白质设计.
  • 通过利用机器学习见解来提高计算设计蛋白质的稳定性和功能.

主要方法:

  • 将进化规模建模 (ESM) 语言模型纳入罗塞塔蛋白质设计能量函数.
  • 使用ESM预测开发了一种新的度量来限制设计期间的能量功能.
  • 通过评估语言模型得分,序列恢复和罗塞塔能量来评估修改后的罗塞塔协议的性能.

主要成果:

  • 与标准的罗塞塔设计相比,采用综合方法设计的序列获得了更高的语言模型分数.
  • 新方法保持了类似的序列恢复率.
  • 对于设计的序列,观察到适度的轻微下降,根据罗塞塔能量进行评估.

结论:

  • 将蛋白质语言模型与罗塞塔设计工具箱相结合,为设计更稳定和功能更强的蛋白质提供了一种强大的方法.
  • 这种整合利用了机器学习的预测能力和蛋白质设计软件的既定框架.
  • 开发的方法代表了计算蛋白质序列设计领域的重大进展.