AI-driven PROTAC design overcomes oncogenic resilience by eliminating the CLIP1–LTK fusion protein
- Shicheng Chen
- Haiting Duan
- Sheng Zhong
- Jingxuan Ge
- Huifeng Zhao
- Yuanyi Ye
- Huiyong Sun
- Dan Li
- Yu Kang
- Xiaowu Dong
- Jinxin Che
- Tingjun Hou
- Peichen Pan
2026-08-06
The discovery of CAP-Gly domain-containing linker protein 1(CLIP1)–Leukocyte tyrosine kinase (LTK) as an oncogenic fusion reveals a unique dependency not only on LTK kinase activity but also on CLIP1-mediated multimerization, a noncatalytic function that drives oncogenic signaling. While this fusion is currently targeted with anaplastic lymphoma kinase inhibitors, their exclusive focus on kinase inhibition leaves the scaffolding function intact, necessitating a complete protein clearance strategy. Here, we report the AI-guided development of a first-in-class proteolysis-targeting chimera (PROTAC) designed to selectively degrade the CLIP1–LTK fusion protein. By integrating deep learning models for ternary complex prediction with structure-based molecular optimization, we designed DCL05, an orally bioavailable degrader of CLIP1–LTK fusion protein, achieving picomolar degradation potency (DC 50 = 40 pM) and robust antitumor activity. DCL05 consistently outperformed existing kinase inhibitors across a broad spectrum of LTK resistance-associated mutations, both in vitro and in vivo. Collectively, our study explores resistance-associated contexts of LTK and establishes a structure-guided PROTAC development pipeline, providing a promising therapeutic strategy for overcoming acquired resistance in kinase-driven cancers.