构建首个统一抗体设计基准，实现表位导向的抗体序列结构协同设计
CHIMERA-Bench: A Benchmark Dataset for Epitope-Specific Antibody Design
- 提出表位引导的CDR序列与结构联合生成任务
- 涵盖2922个复合物数据集，支持三种生物学意义测试划分
- 提供五类新指标，适合抗体生成模型评估与比较
计算抗体设计近年发展迅速，过去三年已提出数十种深度生成方法，但缺乏标准化基准用于公平比较和模型开发。现有方法基于不同SAbDab快照、非重叠测试集及不兼容指标进行评估，研究将设计问题碎片化为多个子任务且无统一定义。本文提出CHIMERA-Bench：一个围绕单一标准任务——表位条件下的CDR序列-结构联合设计构建的统一基准。该基准包含三部分：第一，经过筛选去重的2922个抗体-抗原复合物数据集，附带表位与结合区标注；第二，三个具有生物学意义的划分，用于测试模型在未见表位、未见抗原折叠及前瞻性时间目标上的泛化能力；第三，涵盖五类度量组的综合评估协议，包括新型表位特异性度量。我们对十一种覆盖六种生成范式的模型进行了基准测试，并报告所有划分下的结果。CHIMERA-Bench是当前抗体设计领域规模最大的数据集，支持社区开发新方法并评估其泛化性能。
原文摘要 · Abstract (English)
Computational antibody design has seen rapid methodological progress, with dozens of deep generative methods proposed in the past three years, yet the field lacks a standardized benchmark for fair comparison and model development. These methods are evaluated on different SAbDab snapshots, non-overlapping test sets, and incompatible metrics, and the literature fragments the design problem into numerous sub-tasks with no common definition. We introduce CHIMERA-Bench: (CDR Modeling with Epitope-guided Redesign), a unified benchmark built around a single canonical task: epitope-conditioned CDR sequence-structure co-design. CHIMERA-Bench provides three components. The first is a curated, deduplicated dataset of 2,922 antibody-antigen complexes with epitope and paratope annotations. The second is a set of three biologically motivated splits that test generalization to unseen epitopes, unseen antigen folds, and prospective temporal targets. The third is a comprehensive evaluation protocol with five metric groups, including novel epitope-specificity measures. We benchmark eleven methods spanning six generative paradigms and report results across all splits. CHIMERA-Bench is the largest dataset of its kind for the antibody design problem, allowing the community to develop and test novel methods and evaluate their generalizability.
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