Department of Biochemistry and Molecular Biology Sealy Center for Structural Biology Computational Biology About Us
Structural Database · Version 2.0

SDAP 2.0 — Structural Database of Allergenic Proteins

University of Texas Medical Branch · Galveston, TX

Alphabetical listing of allergens ABCDEFGHIJKLMNOPQRSTUVWXYZ
Access to SDAP is available free of charge for Academic and non-profit use. Licenses for commercial use can be obtained by contacting W. Braun ([email protected]). Secure access: https://fermi.sdaponline.org/SDAP

SDAP is a Web server that integrates a database of allergenic proteins with various computational tools that can assist structural biology studies related to allergens. SDAP is an important tool in the investigation of the cross-reactivity between known allergens, in testing the FAO/WHO allergenicity rules for new proteins, and in predicting the IgE-binding potential of genetically modified food proteins.

Read an SDAP Overview or select a SDAP function from the left column.

SDAP Tools
🧠

AllergenAI New!

AI-powered allergenicity prediction from protein sequence using deep learning.

Launch AllergenAI →
🧪

FAO/WHO Allergenicity Test

Evaluate potential allergenicity using the FAO/WHO decision tree (2001).

Run Test →
🧬

FASTA Search

Sequence similarity search using FASTA-36 against all SDAP allergens.

FASTA Search →
🧾

Peptide Match

Find exact peptide sequence matches across all SDAP allergen sequences.

Peptide Match →
🔗

Peptide Similarity

PD physico-chemical descriptor similarity search against all allergens.

Peptide Similarity →
🗂️

Peptide–Protein PD Index

Compare two protein or peptide sequences using the PD index method.

PD Index →
Featured Structures
If SDAP is Used in Publications, Please Cite
  • Liu J, Negi SS, Yang C, Zhou X, Schein CH, Braun W, Kim P. AllergenAI: a deep learning model predicting allergenicity based on protein sequence. BMC Bioinformatics. 2025;26(1):279. [Abstract] [Full Paper]
  • Negi SS, Schein CH, Braun W. The updated Structural Database of Allergenic Proteins (SDAP 2.0) provides 3D models for allergens and incorporated Bioinformatics Tools. J Allergy Clin Immunol Glob. 2023;2(4):100162. [Abstract] [Full Paper]
  • Schein CH, Negi SS, Braun W. Still SDAPing Along: 20 Years of the Structural Database of Allergenic Proteins. Front. Allergy 3:863172. [Full Paper]
  • Ivanciuc O, Schein CH, Braun W. SDAP: Database and Computational Tools for Allergenic Proteins. Nucleic Acids Res. 2003;31(1):359–362. [PubMed]
  • Ivanciuc O, Schein CH, Braun W. Data Mining of Sequences and 3D Structures of Allergenic Proteins. Bioinformatics 2002;18(10):1358–1364. [PubMed]
More Recent Publications
  • Negi SS, Goldblum R, Braun W, Horiuti TM. Design of peptides with high affinity binding to a monoclonal antibody. Peptides. 145:170628, 2021. [PubMed]
  • Dreskin SC, Koppelman SJ et al. The importance of the 2S albumins for allergenicity and cross-reactivity. J Allergy Clin Immunol 147(4):1154–1163, 2021. [PubMed]
  • Lu W, Negi SS, Schein CH et al. Distinguishing allergens from non-allergenic homologues using PCP motifs. Mol Immunol, 9:1–8, 2018. [PubMed]
  • Negi SS, Braun W. Cross-React: a new structural bioinformatics method for predicting allergen cross-reactivity. Bioinformatics, 33(7):1014–1020, 2017. [PubMed]
  • Ivanciuc O et al. AllerML: Markup language for allergens. Regul. Toxicol. Pharmacol., 60(1):151–160, 2011. [PubMed]

We use the IUIS nomenclature and allergens in SDAP as the official set of allergens. We also include other proteins clearly marked as non-IUIS allergens as a service for allergen researchers exploring proteins that might have a potential allergenic response.

Funding & Support
The SDAP project is supported by grants from the National Institute of Health (2R56AI064913), the U.S. EPA STAR Research Assistance Agreement (No. RD 834823), the NIH (1RO1AI165866-01), and the Margaret Maccallum Gage and Tracy Davis Gage foundation.
Recent SDAP Developments
Previous version of SDAP was developed by Dr. Ovidiu Ivanciuc at UTMB, Galveston, TX. Current version developed by Dr. Surendra Negi at UTMB, Galveston, TX.