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相关概念视频

Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

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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.
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Multi-species Conserved Sequences02:51

Multi-species Conserved Sequences

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Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale  studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved...
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Conservation of Protein Domains02:26

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In multi-pass transmembrane proteins, the polypeptide chain crosses the membrane more than once. The transmembrane polypeptide chain either forms an α-helix or β-strand structure. α-Helix containing multi-pass transmembrane proteins are ubiquitous, whereas β-strand containing ones are mainly found in gram-negative bacteria, mitochondria, and chloroplasts.
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Multi-input and Multi-variable systems01:22

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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
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Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

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Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
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Updated: Jul 6, 2025

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

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使用多目标进化算法的蛋白质多重构造预测.

Minghua Hou1, Sirong Jin1, Xinyue Cui1

  • 1College of Information Engineering, Zhejiang University of Technology, Hangzhou, 310023, China.

Interdisciplinary sciences, computational life sciences
|January 8, 2024
PubMed
概括
此摘要是机器生成的。

预测多个蛋白质构造现在可以使用MultiSFold,这是一种超越AlphaFold2.2.的新方法. 蛋白质结构预测的这一进步为动态和静态蛋白质模型提供了更好的准确性.

关键词:
多目标进化算法多目标进化算法多重构造状态是多重构造状态.蛋白质结构预测 蛋白质结构预测

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相关实验视频

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科学领域:

  • 计算生物学是一种计算生物学.
  • 结构生物信息学 结构生物信息学
  • 蛋白质结构预测 蛋白质结构预测

背景情况:

  • AlphaFold2和AlphaFold DB显著提升了静态蛋白质结构的预测.
  • 预测多个蛋白质构造仍然是结构生物学中的一个关键挑战.

研究的目的:

  • 开发一种新的方法,MultiSFold,用于预测多个蛋白质构造.
  • 为了评估MultiSFold的性能与最先进的方法对比,在 conformational 采样中.

主要方法:

  • 利用基于距离的多目标进化算法进行多重构造预测.
  • 采用深度学习来产生对能源景观建设的竞争约束.
  • 集成的代模式探索,多目标优化和对形态采样的几何优化.

主要成果:

  • MultiSFold在预测多重形状方面取得了56.25%的成功率,明显超过AlphaFold2的10.00%.
  • 在静态结构预测方面,MultiSFold比AlphaFold2提高了2.97%的TM得分,比RoseTTAFold提高了7.72%.
  • 该方法证明了在不同形态状态中产生形状的潜力.

结论:

  • MultiSFold有效地预测了多种蛋白质构造,解决了现有方法的关键局限性.
  • 合规采样与深度学习相结合,显示了全面蛋白质结构建模的前景.
  • MultiSFold为动态和静态蛋白质结构预测提供了更高的准确性.