ABTrans: A Transformer-based Model for Predicting Interaction between Anti-Aβ Antibodies and Peptides.

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Tác giả: Yanlin Bian, Buyong Ma, Yuhong Su, Yangjing Wang, Xincheng Zeng, Lingfeng Zhang

Ngôn ngữ: eng

Ký hiệu phân loại:

Thông tin xuất bản: Germany : Interdisciplinary sciences, computational life sciences , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 174893

Antibodies against Aβ peptide have been recently approved to treat Alzheimer's disease, underscoring the importance of understanding their interactions for developing more potent treatments. Here we investigated the interaction between anti-Aβ antibodies and various peptides using a deep learning model. Our model, ABTrans, was trained on dodecapeptide sequences from phage display experiments and known anti-Aβ antibody sequences sourced from public sources. It classified the binding ability between anti-Aβ antibodies and dodecapeptides into four levels: not binding, weak binding, medium binding, and strong binding, achieving an accuracy of 0.83. Using ABTrans, we examined the cross-reaction of anti-Aβ antibodies with other human amyloidogenic proteins, revealing that Aducanumab and Donanemab exhibited the least cross-reactivity. Additionally, we systematically screened interactions between eleven selected anti-Aβ antibodies and all human proteins to identify potential off-target candidates.
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