Prediction of Proteolysis-Targeting Chimeras Retention Time Using XGBoost Model Incorporated with Chromatographic Conditions

Proteolysis-targeting chimeras (PROTACs) are heterobifunctional molecules that target undruggable proteins, enhance selectivity and prevent target accumulation through catalytic activity. The unique structure of PROTACs presents challenges in structural identification and drug design. Liquid chromat...

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Bibliographic Details
Main Author:	Xinhao Qu (20535329) (author)
Other Authors:	Chen Jiang (200126) (author), Mengyi Shan (20535332) (author), Wenhao Ke (20288017) (author), Jing Chen (4762) (author), Qiming Zhao (3423731) (author), Youhong Hu (530973) (author), Jia Liu (41593) (author), Lu-Ping Qin (331906) (author), Gang Cheng (108773) (author)
Published:	2025
Subjects:	Biochemistry Pharmacology Sociology Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified target undruggable proteins support vector machines shapley additive explanations prevent target accumulation rf ), k lc ), combined deep learning model 963 ± 0 958 ± 0 934 ± 0 896 ± 0 protacs remains challenging protacs presents challenges chromatographic conditions proteolysis chromatographic condition descriptors atomic charge states 2 </ sup optimized xgboost model rt data set model ’ r </ >< sup protacs compounds ccs ), unique structure thus facilitating targeting chimeras svm ) structural identification screening combinations precise method nearest neighbor ms alone molecular fingerprints molecular features mass spectrometry liquid chromatography hyperparameter tuning heterobifunctional molecules enhance selectivity drug design charge descriptors catalytic activity bond variability also emphasizes
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Prediction of Proteolysis-Targeting Chimeras Retention Time Using XGBoost Model Incorporated with Chromatographic Conditions

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