Evidence map›Paper›PMID 21559271›Full record

ArticlePloS one2011

Calpain cleavage prediction using multiple kernel learning.

David A DuVerle, Yasuko Ono, Hiroyuki Sorimachi, Hiroshi Mamitsuka

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed
3.6field-weighted citation impact, top 7% of its field
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

49 citing papers in PubMed, 88 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Review
  6. Inducible Depletion of Calpain-2 Mitigates Abdominal Aortic Aneurysm in Mice.Arteriosclerosis, thrombosis, and vascular biology · 2021
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Calcium-Activated Calpain Specifically Cleaves Glutamate Receptor IIA But Not IIB at theThe Journal of neuroscience : the official journal of the Society for Neuroscience · 2019
    Article
  17. Article
  18. Review
  19. Review
  20. 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 at 2 institutions in 1 country.

David A DuVerleBioinformatics Center, Kyoto University, Uji, Kyoto, Japan. dave@kuicr.kyoto-u.ac.jp
Yasuko Ono
Hiroyuki Sorimachi
Hiroshi Mamitsuka
Kyoto Bunkyo University · JPKyoto University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Calpain, an intracellular Ca²⁺-dependent cysteine protease, is known to play a role in a wide range of metabolic pathways through limited proteolysis of its substrates. However, only a limited number of these substrates are currently known, with the exact mechanism of substrate recognition and cleavage by calpain still largely unknown. While previous research has successfully applied standard machine-learning algorithms to accurately predict substrate cleavage by other similar types of proteases, their approach does not extend well to calpain, possibly due to its particular mode of proteolytic action and limited amount of experimental data. Through the use of Multiple Kernel Learning, a recent extension to the classic Support Vector Machine framework, we were able to train complex models based on rich, heterogeneous feature sets, leading to significantly improved prediction quality (6% over highest AUC score produced by state-of-the-art methods). In addition to producing a stronger machine-learning model for the prediction of calpain cleavage, we were able to highlight the importance and role of each feature of substrate sequences in defining specificity: primary sequence, secondary structure and solvent accessibility. Most notably, we showed there existed significant specificity differences across calpain sub-types, despite previous assumption to the contrary. Prediction accuracy was further successfully validated using, as an unbiased test set, mutated sequences of calpastatin (endogenous inhibitor of calpain) modified to no longer block calpain's proteolytic action. An online implementation of our prediction tool is available at http://calpain.org.

Indexed as

AlgorithmsArea Under CurveArtificial IntelligenceBinding SitesBiochemistryCalciumCalcium-Binding ProteinsCalpainComputational BiologyHumansModels, StatisticalNormal DistributionProtein BindingProtein Structure, SecondaryProtein Structure, TertiaryReproducibility of ResultsCalciumCalcium-Binding ProteinsCalpaincalpastatin

Identifiers

PMID21559271
PMCPMC3086883
OpenAlexW2002798380

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.