Article

SAAINT-DB: a comprehensive structural antibody database for antibody modeling and design

Xiaoqiang Huang1, Jun Zhou1, Shuang Chen1, Xiaofeng Xia2, Y. Eugene Chen1, Jie Xu1
1 Center for Advanced Models for Translational Sciences and Therapeutics, University of Michigan Medical School, Ann Arbor, MI 48109, USA
2 Research & Development, ATGC Inc., King of Prussia, PA 19406, USA
Correspondence to: Xiaoqiang Huang: xiaoqiah@umich.edu,
DOI: 10.1038/s41401-025-01608-5
Received: 20 March 2025
Accepted: 6 June 2025
Advance online: 30 June 2025

Abstract

Antibody (Ab) structures and antibody-antigen (Ag) interactions (AAIs) are essential for understanding immune recognition and designing Ab therapeutics. While existing structural Ab databases provide valuable insights, they still face limitations in data accuracy, completeness, and/or update frequency. Here, we present SAAINT-parser, a computational workflow for rapid, accurate, and robust extraction of Ab and AAI information from the Protein Data Bank (PDB). SAAINT-parser features precise detection of Ab chains, accurate pairing of Ab chains, and reliable identification of AAIs. The resulting SAAINT-DB, last updated on May 1, 2025, contains 19,128 data entries from 9757 PDB structures, offering a comprehensive and up-to-date resource. Detailed analyses highlight the advantages of SAAINT-DB over the widely used SAbDab in terms of data accuracy and completeness. Furthermore, SAAINT-DB provides nearly twice as many non-redundant, manually curated Ab-Ag binding affinity entries as SAbDab. To support Ab-related research and benefit the broader scientific community, we provide open access to SAAINT-parser, the SAAINT-DB summary file, unprocessed PDB structures, and SAAINT-parser-processed structure models at https://github.com/tommyhuangthu/SAAINT.
Keywords: antibody; immunoglobulin; antibody structure; antibody-antigen interaction; database

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