<ul><li>The AlphaFold Protein Structure Database (AFDB) is known for its high structural coverage and near-experimental accuracy, making it valuable for protein design.</li><li>However, using AFDB directly in training deep models for tasks like inverse folding reveals a systematic geometric bias in the database's structural features.</li><li>To address this bias, a Debiasing Structure AutoEncoder (DeSAE) has been introduced to improve the reconstruction of native-like conformations from corrupted backbone geometries.</li><li>The application of DeSAE to AFDB structures has shown significant improvements in inverse folding performance, emphasizing the importance of debiasing in structure-based learning tasks.</li></ul>

AlphaFold Database Debiasing for Robust Inverse Folding

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