Computational Antibody Papers

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2025
TitleKey points
    • A heavy-chain–only version of ABodyBuilder2, removing the light-chain component entirely.
    • The model is substantially faster than ABodyBuilder2 and comparable to IgFold or AlphaFold2 owing to (i) smaller embedding dimensions (128–256 vs 384 in ABB2), (ii) use of fewer submodels (3 vs 4), (iii) omission of the refinement step by default, and (iv) the inherently shorter sequence length of single heavy chains.
    • Accuracy-wise, HeavyBuilder performs on par with ABodyBuilder2, IgFold, and AlphaFold2 for framework and CDRH1–H2, and is slightly better for CDRH3 (∼3.4 Å RMSD vs ∼4 Å for others). While ABodyBuilder2 achieves 2.99 Å on CDRH3, that figure depends on the inclusion of the paired light chain, so the authors note that it is not a fair comparison.
    • Review of currently available large scale software for antibody analysis.
    • Today’s biologics R&D is slowed by fragmented tools and manual data wrangling; the paper proposes a unified, open-architecture platform that spans registration, tracking, analysis, and decisions from discovery through developability.
    • Key components are end-to-end registration of molecules/materials/assays; a harmonized data schema with normalized outputs; automated analytics with consistent QC; complete metadata capture and “data integrity by design.”
    • The platform should natively interface with AI, enable multimodal foundation models and continuous “lab-in-the-loop” learning, and support federated approaches to counter data scarcity while preserving privacy.
    • Dotmatics, Genedata, and Schrödinger each cover pieces (e.g., LiveDesign lacks end-to-end registration), and the authors stress regulatory-ready features.