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相关概念视频

Conserved Binding Sites01:49

Conserved Binding Sites

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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...
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Protein Networks02:26

Protein Networks

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
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Protein-protein Interfaces

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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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Ligand Binding Sites02:40

Ligand Binding Sites

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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...
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Protein-Drug Binding: Determination Methods01:22

Protein-Drug Binding: Determination Methods

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Determining protein-drug binding can be achieved through indirect and direct methods, each providing valuable insights into the interaction between proteins and drugs.
Indirect methods involve isolating the bound drug from its free form in biological samples such as blood, serum, or plasma. These techniques aim to measure the percentage of drugs bound to proteins. Equilibrium dialysis is a commonly used method where the free drug concentration at equilibrium is measured by separating the bound...
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DeePNAP:一种深度学习方法,可以从它们的序列中预测蛋白质-核酸结合的亲和力.

Uddeshya Pandey1, Sasi M Behara1, Siddhant Sharma1

  • 1Department of Biology, Indian Institute of Science Education and Research Tirupati, Tirupati 517507, India.

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概括

DeePNAP仅使用序列数据来预测蛋白质-核酸相互作用的结合亲和力和突变诱导的自由能量变化. 这种机器学习模型为各种生物系统提供了高精度和通用性.

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科学领域:

  • 计算生物学 计算生物学
  • 生物信息学是一种生物信息学.
  • 分子相互作用 分子相互作用

背景情况:

  • 预测蛋白质核酸 (PNA) 结合亲和力对于理解PNA相互作用 (PNAI) 至关重要.
  • 现有的模型往往需要结构信息,并且仅限于特定的PNAI,由于结构数据稀缺,阻碍了概括性.
  • 目前的工具通常预测单个参数,限制了它们的多功能性.

研究的目的:

  • 开发一个多功能机器学习模型,DeePNAP,仅从序列预测PNA结合亲和力和突变效应.
  • 克服依赖于结构数据和有限的PNAI范围的现有方法的局限性.
  • 为快速准确预测PNAI参数提供一个工具.

主要方法:

  • 利用来自ProNAB数据库的14,401条条目的大型异质数据集,包括野生类型和突变PNA复合体.
  • 开发了DeepNAP,这是一个机器学习模型,使用基于序列的功能进行预测.
  • 通过使用相关系数和K_D和ΔΔG预测的根平均平方误差来验证模型的性能.

主要成果:

  • DeePNAP 完全从 PNA 序列中准确预测结合亲和力 (K_D) 和自由能量变化 (ΔΔG).
  • 该模型显示了高相关系数和低根平均平方误差,表明强大的预测能力和通用性.
  • 在真核生物和原核生物中实现了广泛的PNAI的精确预测.

结论:

  • DeePNAP提供了一个强大的,基于序列的方法来预测PNA结合亲和力和突变效应,克服结构数据的限制.
  • 该模型的通用性和多功能性使其成为PNAI研究的宝贵工具.
  • 为DeePNAP提供了一个Web界面,以促进快速预测和更深入地了解生物系统中的PNAI.