Evidence map›Paper›PMID 33617527›Full record

ArticlePLoS computational biology2021

Quantitative profiling of protease specificity.

Boris I Ratnikov, Piotr Cieplak, Albert G Remacle, Elise Nguyen, Jeffrey W Smith

Abstract read
In one paragraph

Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Synthetic protein protease sensor platform.Frontiers in bioengineering and biotechnology · 2024
    Article
  7. Review
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

5 authors.

Boris I RatnikovSanford Burnham Prebys Medical Discovery Institute, La Jolla, California, United States of America.ORCID 0000-0002-7667-6096
Piotr CieplakSanford Burnham Prebys Medical Discovery Institute, La Jolla, California, United States of America.ORCID 0000-0003-0700-5691
Albert G RemacleSanford Burnham Prebys Medical Discovery Institute, La Jolla, California, United States of America.ORCID 0000-0003-1475-6346
Elise NguyenSanford Burnham Prebys Medical Discovery Institute, La Jolla, California, United States of America.ORCID 0000-0001-5632-0714
Jeffrey W SmithSanford Burnham Prebys Medical Discovery Institute, La Jolla, California, United States of America.

Funding

Tumor Microenvironment and Cancer ImmunologyP30CA030199 · NCI · SANFORD BURNHAM PREBYS MEDICAL DISCOVERY INSTITUTE · PI ELENA B PASQUALE · 1985 to 2026
$107.2M
De-orphanizing MMPs in intercelluar interactionsR01GM107523 · NIGMS · SANFORD BURNHAM PREBYS MEDICAL DISCOVERY INSTITUTE · PI SMITH, JEFFREY W · 2016 to 2019
$2.1M
NCI NIH HHS P30 CA030199NIGMS NIH HHS R01 GM107523
6 · The paper itself

Abstract

Proteases are an important class of enzymes, whose activity is central to many physiologic and pathologic processes. Detailed knowledge of protease specificity is key to understanding their function. Although many methods have been developed to profile specificities of proteases, few have the diversity and quantitative grasp necessary to fully define specificity of a protease, both in terms of substrate numbers and their catalytic efficiencies. We have developed a concept of "selectome"; the set of substrate amino acid sequences that uniquely represent the specificity of a protease. We applied it to two closely related members of the Matrixin family-MMP-2 and MMP-9 by using substrate phage display coupled with Next Generation Sequencing and information theory-based data analysis. We have also derived a quantitative measure of substrate specificity, which accounts for both the number of substrates and their relative catalytic efficiencies. Using these advances greatly facilitates elucidation of substrate selectivity between closely related members of a protease family. The study also provides insight into the degree to which the catalytic cleft defines substrate recognition, thus providing basis for overcoming two of the major challenges in the field of proteolysis: 1) development of highly selective activity probes for studying proteases with overlapping specificities, and 2) distinguishing targeted proteolysis from bystander proteolytic events.

Indexed as

Models, BiologicalAmino Acid SequenceCatalytic DomainComputational BiologyHigh-Throughput Nucleotide SequencingInformation TheoryMatrix Metalloproteinase 2Matrix Metalloproteinase 9Models, MolecularPeptide HydrolasesPeptide LibraryProtein FoldingProteolysisProteomicsSubstrate SpecificityMatrix Metalloproteinase 2Matrix Metalloproteinase 9MMP2 protein, humanMMP9 protein, humanPeptide HydrolasesPeptide Library

Identifiers

PMID33617527
PMCPMC7932537

What OpenQuestion holds

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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.