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Updated: May 19, 2026

The ITS2 Database

The ITS2 Database

Published on: March 12, 2012

PDBe-SIFTS: an open-source tool for Structure Integration with Function, Taxonomy, and Sequences, featuring improved

Adam Bellaiche¹, Preeti Choudhary¹, Sreenath Nair¹

¹Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.

Biorxiv : the Preprint Server for Biology

|May 18, 2026

Summary

PDBe-SIFTS is an open-source tool for mapping protein sequences to structures, offering faster and more accurate residue-level alignments. This framework enhances biological data interpretation for research and drug discovery.

Keywords:

BLASTP Computational biology MMSeqs2 PDB SIFTS UniProtKB benchmarking biological resources data annotation data integration databases open-source software pipelines protein backbone connectivity protein sequences protein structures residue-level mapping scoring functions sequence alignment sequence search structural bioinformatics structure-to-sequence mapping

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An Integrated Approach for Microprotein Identification and Sequence Analysis

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

Area of Science:

Structural biology
Bioinformatics
Computational biology

Background:

Mapping protein sequences to structures is crucial for understanding protein function and mechanisms.
Existing methods for Structure Integration with Function, Taxonomy and Sequences (SIFTS) rely on internal pipelines.
Accurate sequence-structure mapping is essential for drug discovery and disease research.

Purpose of the Study:

To present PDBe-SIFTS, a fully open-source, locally deployable implementation of the SIFTS mapping framework.
To provide researchers with a tool for fast, scalable, and accurate residue-level sequence-structure mapping.
To improve structural coherence in alignments and deliver up-to-date, expert-curated quality mappings.

Main Methods:

Utilizing MMseqs2 for fast and scalable sequence searching.
Implementing an improved bounded scoring scheme for ranking candidate mappings.
Employing residue-level mapping refinement based on backbone connectivity.
Distributing PDBe-SIFTS as a Python package with command-line tools for database building, matching, mapping, and annotation generation.

Main Results:

MMseqs2 accelerated UniProtKB searches by 22-36 times compared to BLASTP.
PDBe-SIFTS recovered curated mappings at the top rank in 93.1% of cases.
The tool demonstrated fast mapping capabilities, improving structural coherence and accuracy.

Conclusions:

PDBe-SIFTS provides an efficient and accurate solution for residue-level sequence-structure mapping.
The open-source framework empowers researchers to run, inspect, and extend mappings locally.
This tool facilitates richer interpretation of biological data and advances in related research fields.