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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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Atomic force microscopy (AFM) is a type of scanning probe microscopy that can analyze topographic details of various specimens like ceramics, glass, polymers, and biological samples. AFM offers over 1000 times more resolution than the optical imaging system. Images generated from AFM are three-dimensional surface profiles, offering an advantage over the flat, two-dimensional images from other imaging techniques.
The AFM Probe
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相关实验视频

Updated: Sep 8, 2025

Author Spotlight: In Silico Creation and Impact of Carbonylated Amino Acids on Protein Structure and Function
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使用AtomWorks和RF3加速生物分子建模

Nathaniel Corley1,2,3, Simon Mathis1,4, Rohith Krishna1,3

  • 1Institute for Protein Design, University of Washington, Seattle, 98105, Washington, USA.

bioRxiv : the preprint server for biology
|August 20, 2025
PubMed
概括
此摘要是机器生成的。

AtomWorks是一个新的数据框架,加速开源生物分子机器学习. 它启用了RosettaFold-3 (RF3),这是一个与闭源模型竞争的蛋白质结构预测工具.

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科学领域:

  • 计算生物学是一种计算生物学.
  • 机器学习是机器学习.
  • 结构生物学是结构生物学.

背景情况:

  • 深度学习模型具有先进的生物分子结构预测.
  • 开发和培训这些任务的新型模型是具有挑战性的.
  • 现有的开源工具落后于最先进的闭源替代品.

研究的目的:

  • 介绍AtomWorks,这是一个通用的数据框架,用于开发生物分子基础模型.
  • 为了介绍RosettaFold-3 (RF3),一个使用AtomWorks训练的新结构预测模型.
  • 增强在蛋白质结构预测和设计中的开源能力.

主要方法:

  • 开发用于生物分子机器学习的AtomWorks数据框架.
  • 使用AtomWorks对蛋白质结构数据库进行RosettaFold-3 (RF3) 模型的训练.
  • 在RF3中加入了改进的奇拉性处理,以提高精度.

主要成果:

  • 原子工厂促进了各种生物分子基础模型的开发.
  • 在预测任意生物分子复合体方面,RF3表现出了竞争力的表现.
  • RF3缩小了领先的封闭源代码 (AlphaFold3) 和开源结构预测工具之间的性能差距.

结论:

  • 预计AtomWorks将加速下一代开源生物分子模型的开发.
  • RF3为结构预测提供了一个强大且广泛适用的开源工具.
  • AtomWorks框架和RF3模型是在允许许可证下发布的,以促进社区发展.