Evidence map›Paper›PMID 28078782›Full record

ArticleProtein science : a publication of the Protein Society2017

PACMANS: A bioinformatically informed algorithm to predict, design, and disrupt protease-on-protease hydrolysis.

Meghan C Ferrall-Fairbanks, Zachary T Barry, Maurizio Affer, Marc A Shuler, Ellen W Moomaw, Manu O Platt

Open access · bronzeAbstract read
In one paragraph

Article in Protein science : a publication of the Protein Society, 2017. 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
0.4field-weighted citation impact, top 41% 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

7 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Reassessing enzyme kinetics: Considering protease-as-substrate interactions in proteolytic networks.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  6. Article
  7. Computational predictions of cysteine cathepsin-mediated fibrinogen proteolysis.Protein science : a publication of the Protein Society · 2018
    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

6 authors at 3 institutions in 1 country.

Meghan C Ferrall-FairbanksWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia.
Zachary T BarryWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia.
Maurizio AfferWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia.
Marc A ShulerWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia.
Ellen W MoomawDepartment of Chemistry and Biochemistry, Kennesaw State University, Kennesaw, Georgia.
Manu O PlattWallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia.
The Wallace H. Coulter Department of Biomedical Engineering · USGeorgia Institute of Technology · USKennesaw State University · US

Funding

Multiscale, mechanistic, and predictive models of stroke in sickle cell diseaseDP2OD007433 · OD · GEORGIA INSTITUTE OF TECHNOLOGY · PI PLATT, MANU O · 2010 to 2010
$2.3M
NIH HHS DP2 OD007433
6 · The paper itself

Abstract

Multiple proteases in a system hydrolyze target substrates, but recent evidence indicates that some proteases will degrade other proteases as well. Cathepsin S hydrolysis of cathepsin K is one such example. These interactions may be uni- or bi-directional and change the expected kinetics. To explore potential protease-on-protease interactions in silico, a program was developed for users to input two proteases: (1) the protease-ase that hydrolyzes (2) the substrate, protease. This program identifies putative sites on the substrate protease highly susceptible to cleavage by the protease-ase, using a sliding-window approach that scores amino acid sequences by their preference in the protease-ase active site, culled from MEROPS database. We call this PACMANS, Protease-Ase Cleavage from MEROPS ANalyzed Specificities, and test and validate this algorithm with cathepsins S and K. PACMANS cumulative likelihood scoring identified L253 and V171 as sites on cathepsin K subject to cathepsin S hydrolysis. Mutations made at these locations were tested to block hydrolysis and validate PACMANS predictions. L253A and L253V cathepsin K mutants significantly reduced cathepsin S hydrolysis, validating PACMANS unbiased identification of these sites. Interfamilial protease interactions between cathepsin S and MMP-2 or MMP-9 were tested after predictions by PACMANS, confirming its utility for these systems as well. PACMANS is unique compared to other putative site cleavage programs by allowing users to define the proteases of interest and target, and can also be employed for non-protease substrate proteins, as well as short peptide sequences.

Indexed as

AlgorithmsProteolysisSoftwarePeptide HydrolasesPeptide HydrolasesbioinformaticscathepsinshydrolysisMMPsmutagenesispredictionproteasesproteolysis

Identifiers

PMID28078782
PMCPMC5368069
OpenAlexW2578063682

What OpenQuestion holds

Textmetadata
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.