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相关概念视频

Noncovalent Attractions in Biomolecules02:35

Noncovalent Attractions in Biomolecules

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Noncovalent attractions are associations within and between molecules that influence the shape and structural stability of complexes. These interactions differ from covalent bonding in that they do not involve sharing of electrons.
Four types of noncovalent interactions are hydrogen bonds, van der Waals forces, ionic bonds, and hydrophobic interactions.
Hydrogen bonding results from the electrostatic attraction of a hydrogen atom covalently bonded to a strong-electronegative atom like oxygen,...
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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-protein Interfaces02:04

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 and Linkage00:49

Ligand Binding and Linkage

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Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence...
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Cooperative Allosteric Transitions01:58

Cooperative Allosteric Transitions

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Cooperative allosteric transitions can occur in multimeric proteins, where each subunit of the protein has its own ligand-binding site. When a ligand binds to any of these subunits, it triggers a conformational change that affects the binding sites in the other subunits; this can change the affinity of the other sites for their respective ligands. The ability of the protein to change the shape of its binding site is attributed to the presence of a mix of flexible and stable segments in the...
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Allosteric Proteins-ATCase01:19

Allosteric Proteins-ATCase

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Binding sites linkages can regulate a protein's function.  For example, enzyme activity is often regulated through a feedback mechanism where the end product of the biochemical process serves as an inhibitor.
Aspartate transcarbamoylase (ATCase) is a cytosolic enzyme that catalyzes the condensation of L-aspartate and carbamoyl phosphate to  N-carbamoyl-L-aspartate. This reaction is the first step in pyrimidine biosynthesis. UTP and CTP, the end products of the pyrimidine synthesis...
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Sedimentation Equilibrium of a Small Oligomer-forming Membrane Protein: Effect of Histidine Protonation on Pentameric Stability
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用HADDOCK建模蛋白质-甘氨酸相互作用

Anna Ranaudo1,2, Marco Giulini2, Angela Pelissou Ayuso2

  • 1Department of Earth and Environmental Sciences, University of Milano-Bicocca, Piazza Della Scienza 1, Milan 20126, Italy.

Journal of chemical information and modeling
|October 3, 2024
PubMed
概括

高含糊性驱动的DOCK (HADDOCK) 有效地预测了蛋白质 - 甘氨酸复合体. 这种计算方法取得了很高的成功率,有助于药物设计和理解甘氨酸的功能.

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科学领域:

  • 结构生物学是结构生物学.
  • 计算化学是一种计算化学.
  • 葡萄糖科学 (Glycoscience) 是一种科学.

背景情况:

  • 甘氨酸是参与生物信息传输和信号传递的多种分子.
  • 了解蛋白质-甘氨酸复杂结构对于阐明生物机制和药物设计至关重要.

研究的目的:

  • 评估高模糊性驱动的DOCKing (HADDOCK) 对于预测蛋白质-甘氨酸复合结构的有效性.
  • 为了评估HADDOCK在绑定和未绑定蛋白质-甘氨酸数据集上的性能.

主要方法:

  • 使用了89个蛋白质 - 甘氨酸复合物的基准.
  • 应用HADDOCK,并先前了解蛋白质结合部位.
  • 在结合和不结合的蛋白质和甘氨酸结构上测试了该协议.

主要成果:

  • 在绑定数据集中达到70%的前5名成功率.
  • 在未绑定数据集中,成功率在前五名中达到40%.
  • 确定了甘氨酸的复杂性和形状灵活性作为关键限制.

结论:

  • HADDOCK是一种有效的计算工具,用于预测蛋白质 - 甘氨酸复合体.
  • 哈德考克预测的准确性受糖甘结构复杂性的影响.
  • 需要进一步开发以解决对接协议中的甘氨酸灵活性.