Evidence map›Paper›PMID 36827259›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2023

Improved global protein homolog detection with major gains in function identification.

Mesih Kilinc, Kejue Jia, Robert L Jernigan

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

35 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Large Numbers of New Human Paralogs Discovered.bioRxiv : the preprint server for biology · 2025
    Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Improving the Annotations of JCVI-Syn3a Proteins.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  20. Expanding the β-Lactamase Family in the Human Microbiome.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    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

3 authors.

Mesih KilincBioinformatics and Computational Biology Program, Iowa State University, Ames, IA 50011.ORCID 0000-0003-1581-2717
Kejue JiaRoy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011.
Robert L JerniganBioinformatics and Computational Biology Program, Iowa State University, Ames, IA 50011.ORCID 0000-0003-0996-8360

Funding

Novel Use of Genome Information to Understand MutationsR01HG012117 · NHGRI · IOWA STATE UNIVERSITY · PI JERNIGAN, ROBERT L, KLOCZKOWSKI, ANDRZEJ · 2021 to 2025
$2.3M
Protein Sequence MatchingR01GM127701 · NIGMS · IOWA STATE UNIVERSITY · PI JERNIGAN, ROBERT L, KLOCZKOWSKI, ANDRZEJ · 2018 to 2021
$1.4M
Statistical methods for higher order dependences to understand protein functionsR01GM144961 · NIGMS · COLORADO STATE UNIVERSITY · PI ZHOU, WEN · 2021 to 2023
$600k
NHGRI NIH HHS R01 HG012117NIGMS NIH HHS R01 GM127701NIGMS NIH HHS R01 GM144961
6 · The paper itself

Abstract

There are several hundred million protein sequences, but the relationships among them are not fully available from existing homolog detection methods. There is an essential need for an improved method to push homolog detection to lower levels of sequence identity. The method used here relies on a language model to represent proteins numerically in a matrix (an embedding) and uses discrete cosine transforms to compress the data to extract the most essential part, significantly reducing the data size. This PRotein Ortholog Search Tool (PROST) is significantly faster with linear runtimes, and most importantly, computes the distances between pairs of protein sequences to yield homologs at significantly lower levels of sequence identity than previously. The extent of allosteric effects in proteins points out the importance of global aspects of structure and sequence. PROST excels at global homology detection but not at detecting local homologs. Results are validated by strong similarities between the corresponding pairs of structures. The number of remote homologs detected increased significantly and pushes the effective sequence matches more deeply into the twilight zone. Human protein sequences presently having no assigned function now find significant numbers of putative homologs for 93% of cases and structurally verified assigned functions for 76.4% of these cases. The data compression enables massive searches for homologs with short search times while yielding significant gains in the numbers of remote homologs detected. The method is sufficiently efficient to permit whole-genome/proteome comparisons. The PROST web server is accessible at https://mesihk.github.io/prost.

Indexed as

Data CompressionProteomeAmino Acid SequenceDatabases, ProteinGenomeHumansSearch EngineProteomefunction identificationhomologprotein language modelsproteinssequence search

Identifiers

PMID36827259
PMCPMC9992864

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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.