CHIMERA-Bench: A Benchmark Dataset for Epitope-Specific Antibody Design

2026-03-13

AI Summary

This work addresses the lack of a standardized benchmark in computational antibody design, which has hindered fair comparisons among existing methods. To this end, we introduce the first epitope-specific antibody design benchmark, centered on the task of epitope-guided co-design of CDR sequences and structures. Built upon 2,922 non-redundant antibody–antigen complex structures, the benchmark provides fine-grained epitope and paratope annotations, three biologically motivated data-splitting strategies, and a comprehensive evaluation protocol that includes novel specificity-aware metrics. By systematically evaluating diverse generative models across multiple generalization scenarios, this study establishes a standardized platform for the development and assessment of antibody design methodologies.

Technology Category

• Machine Learning: Calibration & Uncertainty Quantification
• Cognitive Modeling & Cognitive Systems: (Computational) Cognitive Architectures
• Computer Vision: Biometrics, Face, Gesture & Pose

Application Category

• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Graph Algorithms and Modeling for the Web: Graph embeddings and representation learning for Web-related graphs

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 unseen epitopes, unseen antigen folds, and prospective temporal targets; and (3) a comprehensive evaluation protocol with five metric groups including novel epitope-specificity measures. We benchmark representative methods spanning different generative paradigms and report results across all splits. \textsc{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. The source code and data are available at: https://github.com/mansoor181/chimera-bench.git

Problem

• antibody design
• epitope-specific
• benchmark dataset
• CDR modeling
• computational immunology

Innovation

• antibody design
• epitope-specificity
• benchmark dataset
• CDR co-design
• generalization evaluation