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相关概念视频

Protein Denaturation01:28

Protein Denaturation

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The function of proteins depends on their native three-dimensional structure, which is dictated by the amino acid sequence of the specific protein. Folding of the polypeptide chain takes place under specific conditions that energetically favor the folded conformation. In contrast, protein denaturation occurs spontaneously under unfavorable conditions that disrupt the integrity of the folded conformation. Thus, the chemical and physical environment of a protein, such as significant changes in pH...
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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.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to...
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Protein Folding01:22

Protein Folding

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Overview
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Protein and Protein Structure02:15

Protein and Protein Structure

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Proteins are one of the most abundant organic molecules in living systems and have the most diverse range of functions of all macromolecules. Proteins may be structural, regulatory, contractile, or protective. They may serve in transport, storage, or membranes; or they may be toxins or enzymes. Their structures, like their functions, vary greatly. They are all, however, amino acid polymers arranged in a linear sequence.
A protein's shape is critical to its function. For example, an enzyme...
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Conservation of Protein Domains02:26

Conservation of Protein Domains

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Protein Folding Quality Check in the RER01:29

Protein Folding Quality Check in the RER

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ER is the primary site for the maturation and folding of soluble and transmembrane secretory proteins. The calnexin cycle is a specific chaperone system that folds and assesses the confirmation of N-glycosylated proteins before they can exit the ER lumen. The primary players of this quality check pipeline are the lectins, ER-resident chaperones, and a glucosyl transferase enzyme. In case the calnexin system in the lumen fails to salvage a misfolded protein, it is transported to the cytoplasm...
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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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DeepPPThermo:用于预测蛋白质热稳定性的深度学习框架,结合蛋白质水平和氨基酸水平特征.

Xiaoyang Xiang1, Jiaxuan Gao1, Yanrui Ding1

  • 1School of Science, Jiangnan University, Wuxi, P. R. China.

Journal of computational biology : a journal of computational molecular cell biology
|December 15, 2023
PubMed
概括

DeepPPThermo是一个新的深度学习模型,通过整合序列特征,准确地预测蛋白质的热稳定性. 这种方法增强了热友蛋白的识别,并指导了蛋白质工程的努力.

关键词:
这是一个双LSTM.注意力机制注意力机制深度学习是一种深度学习.在 doc2vec 中,我们可以使用热友蛋白质是一种热友蛋白质.

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科学领域:

  • 生物化学 生化学
  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学

背景情况:

  • 通过传统的实验方法发现热友蛋白质和提高蛋白质的热稳定性是低效和昂贵的.
  • 机器学习 (ML) 已经成为预测蛋白质热稳定性的强大工具,但有效利用多视图序列信息仍然是一个挑战.

研究的目的:

  • 开发一个基于深度学习的分类器,DeepPPThermo,用于准确预测热友和中友蛋白质.
  • 将经典序列特征与深度学习表示特征融合在一起,以改善热稳定性预测.

主要方法:

  • 提出了DeepPPThermo,这是一个集成经典序列特征和深度学习表示的深度学习分类器.
  • 使用深度神经网络 (DNN) 和双长期短期记忆 (Bi-LSTM) 来提取隐藏的特征.
  • 利用本地和全球注意力机制来赋予多视图特征的差异重要性,将融合特征输入到一个完全连接的网络分类器中.

主要成果:

  • 与先进的ML和深度学习算法相比,DeepPPThermo在分类热友和中友蛋白质方面表现优越.
  • 废弃性研究证实了DeepPPThermo模型的个体特征的重要性和整体稳定性.

结论:

  • DeepPPThermo提供了强大的和有效的深度学习方法来预测蛋白质的热稳定性.
  • 该模型可以帮助探索蛋白质多样性,识别新型热友蛋白质,并指导蛋白质工程的定向突变.