{
  "abstract": "Motivation: Predicted protein structure resources now contain hundreds of millions of models, turning structural comparison from a pairwise alignment task into a database-scale retrieval problem. Exhaustive structural aligners are computationally impractical at this scale, whereas fast structural-alphabet searches may discard remote or low-complexity homologs during prefiltering. Database-scale search therefore requires methods that combine rapid retrieval with sensitivity to global structural similarity.\n\nResults: We present SSAlign, a protein structure search method that integrates SaProt sequence-structure embeddings, entropy-reduced dense retrieval, an SS-score predictor, and two-stage alignment refinement. In benchmarks on the Swiss-Prot, SCOPe40, and AFDB50 datasets, SSAlign showed competitive alignment quality and returned more TM-align-supported hits than Foldseek in recall-oriented evaluations. On AFDB50, 1000 queries against 53.7 million structures completed in 3150 s on CPUs and 2290 s with GPU prefiltering, corresponding to 103-fold and 142-fold speedups over Foldseek, respectively. On SCOPe40, SSAlign increased the area under the curve (AUC) by 20.2% at family level and 33.3% at superfamily level. In simple-fold antimicrobial peptide case studies, SSAlign retrieved candidates that were not returned by Foldseek under the tested settings, indicating its utility as a fast candidate-generation tool for proteome-scale structural search.\n\nAvailability and implementation: The source code for SSAlign is publicly available at https://github.com/ISYSLAB-HUST/SSAlign. The software version and test data used in this study are archived on Zenodo at https://doi.org/10.5281/zenodo.23432919. Datasets and prebuilt indices can be downloaded from http://bioinfo.isyslab.info/ssalign/download/section/ssalign/.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "name": "Lei Wang",
      "orcid": "0000-0002-0168-9730"
    },
    {
      "name": "Xuchao Zhang"
    },
    {
      "name": "Yan Wang",
      "orcid": "0000-0002-8570-0481"
    },
    {
      "name": "Zhidong Xue",
      "orcid": "0000-0003-3559-0867"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/b568s0j0tjp1c.bib",
  "cited_by": 1,
  "doi": "10.1093/bioinformatics/btag789",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13722286/",
  "id": "b568s0j0tjp1c",
  "issns": [
    "1367-4803",
    "1367-4811"
  ],
  "landing_url": "https://doi.org/10.1093/bioinformatics/btag789",
  "language": "en",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "AcademicSubjects/SCI01060"
    ],
    [
      "heading",
      "Original Paper"
    ],
    [
      "heading",
      "Structural Bioinformatics"
    ],
    [
      "openalex",
      "1312|Protein Structure and Dynamics"
    ]
  ],
  "openalex": "W4412056249",
  "pdf_url": null,
  "pmcid": "PMC13722286",
  "pmid": "42929763",
  "published": "2026-10-26",
  "publisher": "Oxford University Press",
  "ris": "https://research.draconitic.com/paper/b568s0j0tjp1c.ris",
  "sources": [
    {
      "first_seen": "2026-11-03T12:22:49Z",
      "native_id": "PMC13722286",
      "source": "pmc",
      "url": "https://doi.org/10.1093/bioinformatics/btag789"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "openalex:1312|Protein Structure and Dynamics",
      "subfield": "molecular-biology"
    }
  ],
  "title": "SSAlign: fast and sensitive protein structure search at scale",
  "title_text": "SSAlign: fast and sensitive protein structure search at scale",
  "type": "peer-reviewed",
  "updated_at": "2026-11-03T12:22:49Z",
  "url": "https://research.draconitic.com/paper/b568s0j0tjp1c",
  "venue": "Bioinformatics",
  "versions": []
}