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本文引用的文献

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Deciphering the dark cancer phosphoproteome using machine-learned co-regulation of phosphosites.利用机器学习的磷酸化位点共调控来解析癌症暗磷酸化蛋白质组。
Nat Commun. 2025 Mar 20;16(1):2766. doi: 10.1038/s41467-025-57993-2.
2
Illuminating the dark kinome: utilizing multiplex peptide activity arrays to functionally annotate understudied kinases.阐明黑暗的激酶组:利用多重肽活性阵列对研究不足的激酶进行功能注释。
Cell Commun Signal. 2024 Oct 17;22(1):501. doi: 10.1186/s12964-024-01868-4.
3
Assessing Darkness of the Human Kinome from a Medicinal Chemistry Perspective.从药物化学角度评估人类蛋白质组的暗物质。
J Med Chem. 2024 Oct 10;67(19):17919-17928. doi: 10.1021/acs.jmedchem.4c01992. Epub 2024 Sep 25.
4
Overview of the Knowledge Management Center for Illuminating the Druggable Genome.照亮药物基因组学知识管理中心概述
Drug Discov Today. 2024 Mar;29(3):103882. doi: 10.1016/j.drudis.2024.103882. Epub 2024 Jan 11.
5
Illuminating function of the understudied druggable kinome.研究较少的可成药激酶组的照明功能。
Drug Discov Today. 2024 Mar;29(3):103881. doi: 10.1016/j.drudis.2024.103881. Epub 2024 Jan 11.
6
Properties of FDA-approved small molecule protein kinase inhibitors: A 2024 update.美国食品药品监督管理局批准的小分子蛋白激酶抑制剂的特性:2024年更新
Pharmacol Res. 2024 Feb;200:107059. doi: 10.1016/j.phrs.2024.107059. Epub 2024 Jan 11.
7
Dark kinase annotation, mining, and visualization using the Protein Kinase Ontology.利用蛋白激酶本体进行暗激酶注释、挖掘和可视化。
PeerJ. 2023 Dec 5;11:e16087. doi: 10.7717/peerj.16087. eCollection 2023.
8
Predicting protein and pathway associations for understudied dark kinases using pattern-constrained knowledge graph embedding.利用模式约束知识图嵌入技术预测研究不足的暗激酶的蛋白质和途径关联。
PeerJ. 2023 Oct 18;11:e15815. doi: 10.7717/peerj.15815. eCollection 2023.
9
How many kinases are druggable? A review of our current understanding.有多少激酶可成药?对我们目前认识的综述。
Biochem J. 2023 Aug 30;480(16):1331-1363. doi: 10.1042/BCJ20220217.
10
An atlas of substrate specificities for the human serine/threonine kinome.人类丝氨酸/苏氨酸激酶组的底物特异性图谱
Nature. 2023 Jan;613(7945):759-766. doi: 10.1038/s41586-022-05575-3. Epub 2023 Jan 11.

使用生物学和化学标准鉴定和评估研究不足的蛋白激酶。

Identifying and evaluating understudied protein kinases using biological and chemical criteria.

作者信息

Koch Selina, Bajorath Jürgen

机构信息

Department of Life Science Informatics and Data Science, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität Friedrich-Hirzebruch-Allee 5/6 D-53115 Bonn Germany

Lamarr Institute for Machine Learning and Artificial Intelligence, Rheinische Friedrich-Wilhelms-Universität Bonn Friedrich-Hirzebruch-Allee 5/6 D-53115 Bonn Germany.

出版信息

RSC Med Chem. 2025 Jun 5. doi: 10.1039/d5md00306g.

DOI:10.1039/d5md00306g
PMID:40510904
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12152735/
Abstract

Protein kinases (PKs) play a central role in cellular signaling. Uncontrolled signaling by deregulated PKs is implicated in a variety of diseases. As a consequence, PKs are among the most popular pharmaceutical targets. The preferred strategy for therapeutic intervention of medical conditions caused by deregulated PKs is the inhibition of their catalytic phosphorylation activity. Accordingly, small-molecular PK inhibitors (PKIs) have become a major drug class in oncology and prime candidates in other therapeutic areas. While cellular functions of many PKs and potential involvement in disease biology have been intensely investigated, others have received comparably little attention, leading to the identification of understudied 162 kinases representing the dark "dark kinome". Dark PKs have for the most part been categorized based on the absence of functional information and lack of reagents. Large-magnitude projects have been initiated to further explore and functionally characterize the dark kinome. In addition, different categories of PKs have also been defined based on their degree of chemical exploration in medicinal chemistry, representing complementary assessments of understudied PKs.

摘要

蛋白激酶(PKs)在细胞信号传导中起着核心作用。失调的蛋白激酶导致的信号失控与多种疾病有关。因此,蛋白激酶是最热门的药物靶点之一。针对由失调的蛋白激酶引起的病症进行治疗干预的首选策略是抑制其催化磷酸化活性。相应地,小分子蛋白激酶抑制剂(PKIs)已成为肿瘤学中的主要药物类别以及其他治疗领域的主要候选药物。虽然许多蛋白激酶的细胞功能及其在疾病生物学中的潜在作用已得到深入研究,但其他蛋白激酶受到的关注相对较少,这导致了162种研究不足的激酶被确定为黑暗“暗激酶组”。黑暗蛋白激酶大多是根据缺乏功能信息和试剂来分类的。已经启动了大规模项目来进一步探索暗激酶组并对其进行功能表征。此外,还根据它们在药物化学中的化学探索程度定义了不同类别的蛋白激酶,这是对研究不足的蛋白激酶的补充评估。