Evidence map›Paper›PMID 40848287›Full record

ArticleBioinformatics (Oxford, England)2025

An interpretable alphabet for local protein structure search based on amino acid neighborhoods.

Saba Zerefa, Jesse Cool, Pramesh Singh, Samantha Petti

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. PUFFIN: protein unit discovery with functional supervision.Bioinformatics (Oxford, England) · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Saba ZerefaSchool of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, United States.
Jesse CoolDepartment of Mathematics, Tufts University, Medford, MA 02155, United States.
Pramesh SinghTufts Institute for Artificial Intelligence, Tufts University, Medford, MA 02155, United States.
Samantha PettiDepartment of Mathematics, Tufts University, Medford, MA 02155, United States.ORCID 0000-0001-8281-8161

Funding

Burroughs-Wellcome Careers at the Scientific Interface (CASI)NSF-Simons Center for Mathematical and Statistical Analysis of Biology at Harvard #1764269Wellcome Trust
6 · The paper itself

Abstract

motivationRecent advancements in protein structure prediction methods have vastly increased the size of databases of protein structures, necessitating fast methods for protein structure comparison. Search methods that find structurally similar proteins can be applied to find remote homologs, study the functional relationships among proteins, and aid in protein engineering tasks.

resultsWe design a "3Dn" structural alphabet that encodes the local neighborhoods around each amino acid in an interpretable way. In a search benchmark task, a combination of our alphabet and Foldseek's 3Di alphabet, outperforms each alphabet individually and ranks best among local search methods that do not require amino acid identity information. We provide software tools that enable the exploration of novel alphabets and combinations of alphabets for protein structure search. AVAILABILITY AND IMPLEMENTATION: The code is freely available at https://github.com/spetti/structure_comparison and at Zenodo https://doi.org/10.5281/zenodo.15734371.

Indexed as

Amino AcidsComputational BiologyProteinsSoftwareAlgorithmsDatabases, ProteinProtein ConformationSequence Analysis, ProteinAmino AcidsProteins

Identifiers

PMID40848287
PMCPMC12516309

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.