Drug Repositioning in Kinase Inhibitor Discovery for Cancer Therapy

Repurposing of existing drugs has emerged as a time- and cost-effective strategy in oncology drug discovery. Given the critical role of dysregulated kinase signaling in cancer, kinase-focused repurposing strategies have attracted considerable interest. This approach encompasses both “target hopping” between different kinases and the discovery of unexpected kinase inhibitory activity in non-kinase drugs. In this review, we summarize recent advances in the repositioning of kinase inhibitors from medicinal chemistry and structural biology perspectives. We highlight the structural basis and binding modes that enable kinase polypharmacology and therapeutic exploitation of off-target activity. Furthermore, we discuss key structural optimization strategies used to convert initial repurposing hits into potent and selective anticancer agents. Overall, kinase-focused repurposing offers a rational, cost-efficient route to expand anticancer options by exploiting conserved kinase-recognition features and refining selectivity through structure-guided optimization. Translation remains constrained by tumor heterogeneity, incomplete target validation, computational-model bias, PK/PD and toxicity limitations, and regulatory and IP barriers. Integrating interpretable AI and multi-omics with kinome-wide profiling, direct target-engagement assays, patient-relevant models, and data sharing should improve patient stratification and accelerate clinical validation.

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Publication Details

Journal
Pharmaceutics
Published
2026-09-29
DOI
https://doi.org/10.3390/pharmaceutics18101240
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

Drug Repositioning in Kinase Inhibitor Discovery for Cancer Therapy

Xiaocong Pang, Yonghong Liu, Qianran Sun
Pharmaceutics
Computational Drug Discovery Methods
article

Drug Repositioning in Kinase Inhibitor Discovery for Cancer Therapy

Xiaocong Pang, Yonghong Liu, Qianran Sun
article en

Abstract

Repurposing of existing drugs has emerged as a time- and cost-effective strategy in oncology drug discovery. Given the critical role of dysregulated kinase signaling in cancer, kinase-focused repurposing strategies have attracted considerable interest. This approach encompasses both “target hopping” between different kinases and the discovery of unexpected kinase inhibitory activity in non-kinase drugs. In this review, we summarize recent advances in the repositioning of kinase inhibitors from medicinal chemistry and structural biology perspectives. We highlight the structural basis and binding modes that enable kinase polypharmacology and therapeutic exploitation of off-target activity. Furthermore, we discuss key structural optimization strategies used to convert initial repurposing hits into potent and selective anticancer agents. Overall, kinase-focused repurposing offers a rational, cost-efficient route to expand anticancer options by exploiting conserved kinase-recognition features and refining selectivity through structure-guided optimization. Translation remains constrained by tumor heterogeneity, incomplete target validation, computational-model bias, PK/PD and toxicity limitations, and regulatory and IP barriers. Integrating interpretable AI and multi-omics with kinome-wide profiling, direct target-engagement assays, patient-relevant models, and data sharing should improve patient stratification and accelerate clinical validation.

PharmaceuticsVol. 18(10)
Peking University (CN), Peking University First Hospital (CN), State Key Laboratory of Natural and Biomimetic Drugs (CN)
Openalex Percentile: Top 9%
Computational Drug Discovery Methods
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