CHIMERA-Bench: A Benchmark Dataset for Epitope-Specific Antibody Design
Mansoor Ahmed, Nadeem Taj, Imdad Ullah Khan, Hemanth Venkateswara, Murray Patterson

TL;DR
Chimera-Bench introduces a comprehensive, standardized benchmark dataset for epitope-specific antibody design, enabling fair comparison and development of generative models in this field.
Contribution
It provides the largest curated dataset, standardized evaluation protocols, and diverse test splits for epitope-conditioned antibody design.
Findings
Benchmarking of representative methods across all splits.
Largest dataset of its kind for antibody design.
Evaluation includes novel epitope-specificity metrics.
Abstract
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 \textsc{Chimera-Bench} (\textbf{C}DR \textbf{M}odeling with \textbf{E}pitope-guided \textbf{R}edesign), a unified benchmark built around a single canonical task: \emph{epitope-conditioned CDR sequence-structure co-design}. \textsc{Chimera-Bench} provides (1) a curated, deduplicated dataset of \textbf{2,922} antibody-antigen complexes with epitope and paratope annotations; (2) three biologically motivated splits testing generalization to…
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