SimBinder-IF: Structure-Aware Antibody Affinity Optimization via Efficient Preference Learning

Xinyan Zhao

doi:10.1093/bioinformatics/btag548

SimBinder-IF: Structure-Aware Antibody Affinity Optimization via Efficient Preference Learning

2026-07-24

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DOI：10.1093/bioinformatics/btag548

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Antibody therapeutic efficacy depends on high-affinity target engagement, yet laboratory affinity maturation is slow and costly. Most protein language models (PLMs) lack explicit training for high affinity, and current preference optimization methods introduce computational overhead without clear affinity improvements. Therefore, structure-aware and parameter-efficient approaches for antibody affinity optimization are urgently needed.

SimBinder-IF: Structure-Aware Antibody Affinity Optimization via Efficient Preference Learning

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