Robust inference of kinase activity using functional networks.
Robust inference of kinase activity using functional networks.
复制标题
DOI：
10.1038/s41467-021-21211-6
复制
发表时间：
2021-02-19
影响因子：
16.6
通讯作者：
Koyutürk M
中科院分区：
文献类型：
--
作者：
Yılmaz S;Ayati M;Schlatzer D;Çiçek AE;Chance MR;Koyutürk M
质谱分析能够在广泛的生物环境中对磷蛋白进行高通量筛选。当辅以计算算法时，磷酸化蛋白质组数据可以推断激酶活性，从而有助于识别癌症、阿尔茨海默病和帕金森病等各种疾病中失调的激酶。为了提高激酶活性推断的可靠性，我们提出了一个基于网络的框架 RoKAI，它集成了各种功能信息源以捕获信号传导的协调变化。通过计算实验，我们表明激酶功能附近位点的磷酸化可以显着预测其活性。将这些知识纳入 RoKAI 持续提高了激酶活性推断方法的准确性，同时使它们对于缺失注释和定量更加稳健。这使得能够识别未被充分研究的激酶，并可能导致开发用于许多疾病靶向治疗的新型激酶抑制剂。 RoKAI 可作为基于网络的工具在 http://rokai.io 上使用。激酶驱动细胞状态的根本变化，但根据底物水平的变化预测激酶活性可能具有挑战性。在这里，作者介绍了一个计算框架，该框架利用底物之间的相似性来稳健地推断激酶活性。
Mass spectrometry enables high-throughput screening of phosphoproteins across a broad range of biological contexts. When complemented by computational algorithms, phospho-proteomic data allows the inference of kinase activity, facilitating the identification of dysregulated kinases in various diseases including cancer, Alzheimer’s disease and Parkinson’s disease. To enhance the reliability of kinase activity inference, we present a network-based framework, RoKAI, that integrates various sources of functional information to capture coordinated changes in signaling. Through computational experiments, we show that phosphorylation of sites in the functional neighborhood of a kinase are significantly predictive of its activity. The incorporation of this knowledge in RoKAI consistently enhances the accuracy of kinase activity inference methods while making them more robust to missing annotations and quantifications. This enables the identification of understudied kinases and will likely lead to the development of novel kinase inhibitors for targeted therapy of many diseases. RoKAI is available as web-based tool at http://rokai.io. Kinases drive fundamental changes in cell state, but predicting kinase activity based on substrate-level changes can be challenging. Here the authors introduce a computational framework that utilizes similarities between substrates to robustly infer kinase activity.
登录
查看更多内容
影响因子：
14.9
作者：
Minguez P;Letunic I;Parca L;Bork P
通讯作者：
Bork P
DOI：
10.1056/nejmoa1007056
发表时间：
2010-10-28
期刊：
The New England journal of medicine
影响因子：
--
作者：
Butrynski JE;D'Adamo DR;Hornick JL;Dal Cin P;Antonescu CR;Jhanwar SC;Ladanyi M;Capelletti M;Rodig SJ;Ramaiya N;Kwak EL;Clark JW;Wilner KD;Christensen JG;Jänne PA;Maki RG;Demetri GD;Shapiro GI
通讯作者：
Shapiro GI
影响因子：
64.8
作者：
通讯作者：
--
影响因子：
3.7
作者：
MASSEY, FJ
通讯作者：
MASSEY, FJ
影响因子：
7
作者：
Arshad, Osama A.;Danna, Vincent;McDermott, Jason E.
通讯作者：
McDermott, Jason E.