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Designing novel FAK inhibitors targeting gastric cancer: a combined approach using machine learning, docking analysis, molecular dynamics simulations, and experimental validation

Crossref DOI link: https://doi.org/10.1007/s10822-025-00747-5

Published Online: 2026-01-07

Published Print: 2026-12

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

He, Xiaoyu

Wan, Qianwen

Zhou, Yaofeng

Yan, Jiawang

Zhao, Yihuan

Tang, Fushan
Funding

Funding for this research was provided by:

This project is supported by Guizhou Provincial Science and Technology Projects (No. Qiankehe Jichu (Basic Research) MS [2025] 372)

This project is supported by Guizhou Provincial Science and Technology Projects (No. Qiankehe Jichu (Basic Research) MS [2025] 372)

This project is supported by Guizhou Provincial Science and Technology Projects (No. Qiankehe Jichu (Basic Research) MS [2025] 372)

Guizhou Provincial Science and Technology Projects (No. Qian Ke He Jichu-[2024] youth 322)

Guizhou Provincial Science and Technology Projects (No. Qian Ke He Jichu-[2024] youth 322)

Guizhou Provincial Science and Technology Projects (No. Qian Ke He Jichu-[2024] youth 322)

National Natural Science Foundation of China (Grant No. 22463013)

National Natural Science Foundation of China (Grant No. 22463013)

National Natural Science Foundation of China (Grant No. 22463013)

Science and Technology Plan Project of Guizhou (No. Qian Science Platform Talent [2021]1350-017)

Science and Technology Plan Project of Guizhou (No. Qian Science Platform Talent [2021]1350-017)

Science and Technology Plan Project of Guizhou (No. Qian Science Platform Talent [2021]1350-017)
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Text and Data Mining valid from 2026-01-07

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Article History

Received: 2 September 2025

Accepted: 15 December 2025

First Online: 7 January 2026

Declarations

:

: The authors declare no competing interests.

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