血小板激活级联的信号转导和转化:系统生物学的见解。

IF 2.7 4区 医学 Q2 HEMATOLOGY
Hamostaseologie Pub Date : 2025-02-01 Epub Date: 2025-02-19 DOI:10.1055/a-2486-6758
Anastasia N Sveshnikova, Mikhail Aleksandrovich Panteleev
{"title":"血小板激活级联的信号转导和转化:系统生物学的见解。","authors":"Anastasia N Sveshnikova, Mikhail Aleksandrovich Panteleev","doi":"10.1055/a-2486-6758","DOIUrl":null,"url":null,"abstract":"<p><p>Binding of platelet activators to their receptors initiates a signal transduction network, where intracellular signal is filtered, amplified, and transformed. Computational systems biology methods could be a powerful tool to address and analyze dynamics and regulation of the crucial steps in this cascade. Here we review these approaches and show the logic of their use for a relatively simple case of SFLLRN-induced procoagulant activity. Use of a typical model is employed to track signaling events along the main axis, from the binding of the peptide to PAR1 receptor down to the mPTP opening. Temporal dynamics, concentration dependence, formation of calcium oscillations and their deciphering, and role of stochasticity are quantified for all essential signaling molecules and their complexes. The initial step-wise activation stimulus is transformed to a peak at the early stages, then to oscillation calcium spikes, and then back to a peak shape. The model can show how both amplitude and width of the peak encode the information about the activation level, and show the principle of decoding calcium oscillations via integration of the calcium signal by the mitochondria. Use of stochastic algorithms can reveal that the complexes of Gq, in particular the complex of phospholipase C with Gq, which are the limiting steps in the cascade with their numbers not exceeding several molecules per platelet at any given time; it is them that cause stochastic appearance of the signals downstream. Application of reduction techniques to simplify the system is demonstrated.</p>","PeriodicalId":55074,"journal":{"name":"Hamostaseologie","volume":"45 1","pages":"49-62"},"PeriodicalIF":2.7000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Signal Transduction and Transformation by the Platelet Activation Cascade: Systems Biology Insights.\",\"authors\":\"Anastasia N Sveshnikova, Mikhail Aleksandrovich Panteleev\",\"doi\":\"10.1055/a-2486-6758\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Binding of platelet activators to their receptors initiates a signal transduction network, where intracellular signal is filtered, amplified, and transformed. Computational systems biology methods could be a powerful tool to address and analyze dynamics and regulation of the crucial steps in this cascade. Here we review these approaches and show the logic of their use for a relatively simple case of SFLLRN-induced procoagulant activity. Use of a typical model is employed to track signaling events along the main axis, from the binding of the peptide to PAR1 receptor down to the mPTP opening. Temporal dynamics, concentration dependence, formation of calcium oscillations and their deciphering, and role of stochasticity are quantified for all essential signaling molecules and their complexes. The initial step-wise activation stimulus is transformed to a peak at the early stages, then to oscillation calcium spikes, and then back to a peak shape. The model can show how both amplitude and width of the peak encode the information about the activation level, and show the principle of decoding calcium oscillations via integration of the calcium signal by the mitochondria. Use of stochastic algorithms can reveal that the complexes of Gq, in particular the complex of phospholipase C with Gq, which are the limiting steps in the cascade with their numbers not exceeding several molecules per platelet at any given time; it is them that cause stochastic appearance of the signals downstream. Application of reduction techniques to simplify the system is demonstrated.</p>\",\"PeriodicalId\":55074,\"journal\":{\"name\":\"Hamostaseologie\",\"volume\":\"45 1\",\"pages\":\"49-62\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2025-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Hamostaseologie\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1055/a-2486-6758\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/2/19 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"HEMATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hamostaseologie","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1055/a-2486-6758","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/2/19 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"HEMATOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

血小板激活剂与其受体的结合启动信号转导网络,其中细胞内信号被过滤、放大和转化。计算系统生物学方法可以成为解决和分析这个级联中关键步骤的动态和调节的强大工具。在这里,我们回顾了这些方法,并展示了它们在一个相对简单的sfllrn诱导的促凝活性病例中的应用逻辑。使用典型模型沿着主轴跟踪信号事件,从肽与PAR1受体的结合到mPTP打开。时间动力学、浓度依赖性、钙振荡的形成及其解析、随机性的作用被量化为所有必需的信号分子及其复合物。最初的阶梯式激活刺激在早期阶段转化为峰值,然后是振荡钙峰,然后再回到峰值形状。该模型可以显示峰的振幅和宽度如何编码有关激活水平的信息,并显示通过线粒体对钙信号的整合解码钙振荡的原理。使用随机算法可以揭示Gq的复合物,特别是磷脂酶C与Gq的复合物,它们是级联中的限制步骤,它们的数量在任何给定时间内都不超过每个血小板的几个分子;正是它们导致了下游信号的随机出现。演示了应用约简技术来简化系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Signal Transduction and Transformation by the Platelet Activation Cascade: Systems Biology Insights.

Binding of platelet activators to their receptors initiates a signal transduction network, where intracellular signal is filtered, amplified, and transformed. Computational systems biology methods could be a powerful tool to address and analyze dynamics and regulation of the crucial steps in this cascade. Here we review these approaches and show the logic of their use for a relatively simple case of SFLLRN-induced procoagulant activity. Use of a typical model is employed to track signaling events along the main axis, from the binding of the peptide to PAR1 receptor down to the mPTP opening. Temporal dynamics, concentration dependence, formation of calcium oscillations and their deciphering, and role of stochasticity are quantified for all essential signaling molecules and their complexes. The initial step-wise activation stimulus is transformed to a peak at the early stages, then to oscillation calcium spikes, and then back to a peak shape. The model can show how both amplitude and width of the peak encode the information about the activation level, and show the principle of decoding calcium oscillations via integration of the calcium signal by the mitochondria. Use of stochastic algorithms can reveal that the complexes of Gq, in particular the complex of phospholipase C with Gq, which are the limiting steps in the cascade with their numbers not exceeding several molecules per platelet at any given time; it is them that cause stochastic appearance of the signals downstream. Application of reduction techniques to simplify the system is demonstrated.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Hamostaseologie
Hamostaseologie HEMATOLOGY-
CiteScore
5.50
自引率
6.20%
发文量
62
审稿时长
6-12 weeks
期刊介绍: Hämostaseologie is an interdisciplinary specialist journal on the complex topics of haemorrhages and thromboembolism and is aimed not only at haematologists, but also at a wide range of specialists from clinic and practice. The readership consequently includes both specialists for internal medicine as well as for surgical diseases.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信