AFPFusionLM: A Hybrid Sequence–Structure Protein Language Model for Antifreeze Protein Function Prediction

Yijun Li, Xiaonan Wang, Chi Wang

Submission Type: I want my submission to be considered for both oral and poster presentation.

Keywords: AI for biology, Antifreeze proteins, Protein function prediction, Protein language model, Representation learning

TL;DR: We propose AFPFusionLM, a hybrid sequence–structure protein language model, trained with classification and supervised contrastive objectives, achieving state-of-the-art antifreeze protein prediction and enabling closed-loop design.

Confirmation Of Submission Requirements: I submit an abstract. It uses the template provided on the submission page and is no longer than 2 pages.

Submission Number: 315