Mujie Lin

Mujie Lin

M.Phil. in Computer Science @ PKU. Building AI systems for molecular discovery, protein dynamics, and scientific foundation models.

ADCNet: a unified framework for predicting the activity of antibody-drug conjugates

Published in Briefings in Bioinformatics (SCI Q1, IF = 7.7), 2025

Abstract

Antibody-drug conjugates (ADCs) have revolutionized the field of cancer treatment in the era of precision medicine due to their ability to precisely target cancer cells and release highly effective drugs. Nevertheless, the rational design and discovery of ADCs remain challenging because the relationship between their quintuple structures and activities is difficult to explore and understand. To address this issue, ADCNet introduces a unified deep learning framework to predict ADC activity by integrating antigen, antibody, linker, payload, and drug-antibody ratio representations. ADCNet combines protein representations from ESM-2 and molecular representations from FG-BERT, and achieves strong performance on internal testing, cross-validation, ablation, and external independent evaluation.

Contribution

Fourth author. Contributed to deep learning modeling and molecular representation learning components for ADC activity prediction.

Recommended citation: Liye Chen#, Biaoshun Li#, Yihao Chen#, Mujie Lin, Shipeng Zhang, Chenxin Li, Yu Pang, Ling Wang. "ADCNet: a unified framework for predicting the activity of antibody-drug conjugates." Brief. Bioinform., 2025.
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