StoPred:使用蛋白质语言模型和注意力图的蛋白质复合体的精确静脉测量预测.
Quancheng Liu1, Chunxiang Peng2, Wei Zheng3,1
1Gilbert S Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Avenue, Ann Arbor, 48109-2218, MI, U.S..
Research square
|November 24, 2025
概括
使用蛋白质语言模型和图表注意力网络,StoPred准确地预测了蛋白质复合体静态度. 这种新的方法增强了对同质和异质复合体的预测,克服了现有的计算方法的局限性.
科学领域:
- 生物化学 生物化学
- 计算生物学 计算生物学
- 结构生物学 结构生物学
背景情况:
- 蛋白质复合体对于生物功能至关重要,但确定它们的亚单元固体测量在实验上具有挑战性.
- 现有的石化测量预测计算方法是有限的,通常需要同源结构或预定义的组装状态.
- 当前的蛋白质语言模型 (pLM) 方法预测了同质固体测量,但在异质复合体方面失败了.
研究的目的:
- 开发一种新的计算方法,用于准确预测蛋白质复合体静脉测量.
- 解决现有方法的局限性,特别是异构体复合物的局限性.
- 将序列和结构信息与先进的深度学习技术集成在一起.
主要方法:
- 开发了StoPred,一种将plm嵌入式与图形注意网络集成的方法.
- 从序列或结构特征直接预测静态度的模拟的子单位间关系.
- 将该方法应用于同质和异质蛋白质复合体.
主要成果:
- 与基准数据集的基于模板和深度学习方法相比,StoPred实现了更高的准确性和效率.
- 在top-1准确度方面显著改善:同质复合体高达16%,异质复合体高达41%.
- 斯托普雷德是第一个能够准确预测异构体复杂石化学的深度学习方法.
结论:
- 斯托普雷德 (StoPred) 提供了一个强大而准确的解决方案,用于预测蛋白质复合体石基度,包括具有挑战性的异构组合.
- 该方法通过利用pLM嵌入和图表注意力网络来推进计算方法.
- 通过准确的复杂成分预测,StoPred对了解蛋白质功能和生物通路具有广泛的影响.
相关概念视频
Protein Networks
4.5K
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,...
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,...
4.5K
Protein Networks
2.8K
2.8K
Protein-protein Interfaces
14.4K
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...
14.4K
Protein-Protein Interfaces
4.4K
4.4K
Physiological Pharmacokinetic Models: Assumption with Protein Binding
202
Physiological models with protein binding in pharmacokinetics offer a sophisticated approach to understanding drug disposition. These models consider drug-protein interactions, enabling them to effectively predict drug concentrations in different organs and tissues. This precision aids in accurate drug dosing, providing a significant advantage over conventional models. A key process within these models is equilibration, which ensures that drug concentrations achieve a steady state within the...
202
Ligand Binding Sites
14.8K
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...
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...
14.8K


