Design and Screening Research of Novel TYK2 Inhibitors Based on QSAR, Molecular Docking, and Molecular Dynamics Simulation

ABSTRACT Tyrosine kinase 2 (TYK2) is an important target for the treatment of inflammatory bowel disease and plays a key role in cytokine signal transduction. This study took 52 novel selective TYK2 inhibitors with anti‐inflammatory activity as the dataset and systematically constructed four QSAR models: CoMFA, CoMSIA, Topomer CoMFA, and HQSAR. These models demonstrated excellent fitting and predictive capabilities through both internal cross‐validation and external test set validation. Based on the QSAR results combined with screening from the ZINC20 database, 16 new compounds with high predicted activity were designed. Furthermore, molecular docking and molecular dynamics simulations were performed to verify the stable binding characteristics of these compounds to the target protein. This study not only provided an effective screening tool for the design of novel TYK2 inhibitors but also proposed a series of potential candidate molecules, which may offer valuable references for optimizing the pharmacokinetic properties and overcoming drug resistance issues of TYK2 inhibitors, thereby facilitating their clinical application.

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Publication Details

Journal
ChemistrySelect
Published
2026-04-01
DOI
https://doi.org/10.1002/slct.202504195
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00

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Design and Screening Research of Novel TYK2 Inhibitors Based on QSAR, Molecular Docking, and Molecular Dynamics Simulation

Jian‐Bo Tong, Yifan Sun, Yakun Zhang, Jia‐Le Li et al.
ChemistrySelect
Computational Drug Discovery Methods
article

Design and Screening Research of Novel TYK2 Inhibitors Based on QSAR, Molecular Docking, and Molecular Dynamics Simulation

Jian‐Bo Tong, Yifan Sun, Yakun Zhang, Jia‐Le Li, Qi Hou
article en

Abstract

ABSTRACT Tyrosine kinase 2 (TYK2) is an important target for the treatment of inflammatory bowel disease and plays a key role in cytokine signal transduction. This study took 52 novel selective TYK2 inhibitors with anti‐inflammatory activity as the dataset and systematically constructed four QSAR models: CoMFA, CoMSIA, Topomer CoMFA, and HQSAR. These models demonstrated excellent fitting and predictive capabilities through both internal cross‐validation and external test set validation. Based on the QSAR results combined with screening from the ZINC20 database, 16 new compounds with high predicted activity were designed. Furthermore, molecular docking and molecular dynamics simulations were performed to verify the stable binding characteristics of these compounds to the target protein. This study not only provided an effective screening tool for the design of novel TYK2 inhibitors but also proposed a series of potential candidate molecules, which may offer valuable references for optimizing the pharmacokinetic properties and overcoming drug resistance issues of TYK2 inhibitors, thereby facilitating their clinical application.

ChemistrySelectVol. 11(14)
Northwest Research Institute of Chemical Industry (CN), Shaanxi University of Science and Technology (CN)
National Natural Science Foundation of China, Shaanxi University of Science and Technology
Good health and well-being
Openalex Percentile: Top 17%
Computational Drug Discovery Methods
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