395-ImmunoStruct：预测免疫原性的多模态深度学习模型

这项研究介绍了一种名为 ImmunoStruct 的多模态深度学习模型，旨在精确预测 HLA I 类分子与多肽复合物的免疫原性。与仅依赖氨基酸序列的传统方法不同，该模型通过整合三维结构信息、序列特征以及生化属性，显著提升了预测精度与可解释性。研究人员利用 AlphaFold2 构建了包含两万六千多个样本的大型数据集，并引入了针对癌症新抗原的对比学习策略，以捕捉突变体与野生型之间的细微差异。实验结果表明，ImmunoStruct 在识别新冠病毒表位和评估癌症患者存活率方面展现出卓越的临床潜力。该成果不仅为表位疫苗的优化设计提供了强有力的工具，也为蛋白质复合物的属性预测开辟了新路径。References:* Givechian K B, Rocha J F, Liu C, et al. ImmunoStruct enables multimodal deep learnin...去小宇宙查看完整单集简介前往小宇宙评论区与主播互动

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