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相关概念视频

Ligand Binding and Linkage00:49

Ligand Binding and Linkage

4.8K
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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Assembly of Signaling Complexes01:30

Assembly of Signaling Complexes

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Multiprotein signaling complexes are formed in a dynamic process involving protein-protein interactions at the cytoplasmic domain of transmembrane receptors or enzymatic and non-enzymatic proteins associated with the receptor. These complexes ensure the activation and propagation of intracellular signals that regulate cell functions.
Interaction domains in cell signaling
Interaction domains recognize exposed features of their binding partners containing post-translationally modified sequences,...
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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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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...
12.8K
Protein Kinases and Phosphatases02:54

Protein Kinases and Phosphatases

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Proteins undergo chemical modifications that trigger changes in the charge, structure, and conformation of the proteins. Phosphorylation, acetylation, glycosylation, nitrosylation, ubiquitination, lipidation, methylation, and proteolysis are various protein modifications that regulate protein activity. Such modifications are usually enzyme-driven.
Protein kinases
Many proteins in the cell are regulated by phosphorylation, the addition of a phosphate group. A family of enzymes called kinases...
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导向对接作为数据生成方法促进了基于结构的机器学习在Kinases上.

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概括
此摘要是机器生成的。

机器学习模型通过使用3D结构来改善药物发现. 生成合成蛋白质-配体复合体可以提高药物开发的结合亲和力预测准确度.

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科学领域:

  • 计算化学是一种计算化学.
  • 机器学习在药物发现中的作用
  • 结构生物信息学 结构生物信息学

背景情况:

  • 机器学习模型对于探索药物发现中的化学空间至关重要.
  • 将3D结构信息集成到模型中是有益的,但由于实验性蛋白质-连接体复杂结构的稀缺性而受到限制.
  • 激酶药物发现是一个关键领域,结构数据往往缺乏.

研究的目的:

  • 为了应对药物发现中有限的蛋白质连接体复杂结构的挑战.
  • 为训练机器学习模型生成合成激酶-联结体复杂数据.
  • 评估使用生成的复杂数据对结合亲和力预测准确度的影响.

主要方法:

  • 使用模板对接对ChEMBL测试数据的一个子集生成合成酶-连接物复合物的数据.
  • 在训练中使用了一个E(3) -不变图神经网络.
  • 将基于结构的模型与合成姿势的性能与仅带或药物向相互作用模型进行了比较.

主要成果:

  • 用合成结合姿势训练的模型在预测结合亲和度方面表现出明显更高的精度.
  • 与缺乏此类数据的模型相比,包含生成的3D结构信息提高了预测性能.
  • 该研究验证了计算生成的复杂数据对增强预测模型的实用性.

结论:

  • 生成合成蛋白质 - 连接体复合物的数据是一个可行的策略,以克服基于结构的药物发现的数据限制.
  • 结合合成姿势的基于结构的机器学习模型提供了卓越的结合亲和力预测.
  • 这种方法可以提高药物发现管道的效率和准确性,特别是对于像酶这样的目标.