Dr. Kinase: predicting the drug-resistance hotspots of protein kinases

Protein kinases (PKs) regulate various cellular functions, and are targeted by small-molecule kinase inhibitors (KIs) in cancers and other diseases. However, drug resistance (DR) of KIs occurs through critical mutations in four types of representative hotspots, including gatekeeper, G-loop, αC-helix, and A-loop. KI DR has become a common clinical complication affecting multiple cancers, targeted kinases, and drugs. To tackle this challenge, we report an upgraded web server, namely Dr. Kinase, for predicting the loci of four DR hotspots and assessing effects of mutations on DR hotspots for PKs in our previous studies, by utilizing multimodal features and deep hybrid learning. The performance of Dr. Kinase has been rigorously evaluated using independent testing, demonstrating excellent accuracy with area under the curve values exceeding 0.89 in different types of DR hotspot predictions. We further conducted in silico analyses to evaluate and validate the epidermal growth factor receptor mutations on protein conformation and KIs' binding efficacy. Dr. Kinase is freely available at http://modinfor.com/drkinase, with comprehensive annotations and visualizations. We anticipate that Dr. Kinase will be a highly useful service for the basic, translational, and clinical community to unveil the molecular mechanisms of DR and the development of next-generation KIs for emerging cancer precision medicine.

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Publication Details

Journal
Nucleic Acids Research
Published
2025-05-01
DOI
https://doi.org/10.1093/nar/gkaf366
Citations
2
Primary Topic
Protein Degradation and Inhibitors
Type
article
Field-Weighted Citation Impact
1.61

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article

Dr. Kinase: predicting the drug-resistance hotspots of protein kinases

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2 citations
Nucleic Acids Research
Protein Degradation and Inhibitors
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article

Dr. Kinase: predicting the drug-resistance hotspots of protein kinases

Zhongming Zhao, Shaofeng Lin, Haodong Xu, Ruifeng Hu, Lian-Qin Kuang, Haiji Wang, Chao Tu, Liming Wang, Zhihong Li, Hui Luo, Zhiwei Dong, Tao Wang
article en
2 citations

Abstract

Protein kinases (PKs) regulate various cellular functions, and are targeted by small-molecule kinase inhibitors (KIs) in cancers and other diseases. However, drug resistance (DR) of KIs occurs through critical mutations in four types of representative hotspots, including gatekeeper, G-loop, αC-helix, and A-loop. KI DR has become a common clinical complication affecting multiple cancers, targeted kinases, and drugs. To tackle this challenge, we report an upgraded web server, namely Dr. Kinase, for predicting the loci of four DR hotspots and assessing effects of mutations on DR hotspots for PKs in our previous studies, by utilizing multimodal features and deep hybrid learning. The performance of Dr. Kinase has been rigorously evaluated using independent testing, demonstrating excellent accuracy with area under the curve values exceeding 0.89 in different types of DR hotspot predictions. We further conducted in silico analyses to evaluate and validate the epidermal growth factor receptor mutations on protein conformation and KIs' binding efficacy. Dr. Kinase is freely available at http://modinfor.com/drkinase, with comprehensive annotations and visualizations. We anticipate that Dr. Kinase will be a highly useful service for the basic, translational, and clinical community to unveil the molecular mechanisms of DR and the development of next-generation KIs for emerging cancer precision medicine.

Nucleic Acids ResearchVol. 53(W1)
Fujian Medical University (CN), Central South University (CN), Hunan University (CN), Second Xiangya Hospital of Central South University (CN), The University of Texas Health Science Center at Houston (US)
National Natural Science Foundation of China, Scientific Research Foundation of Hunan Provincial Education Department
Good health and well-being
Openalex Percentile: Top 18%
Protein Degradation and Inhibitors
1.61
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