Evidence map›Paper›PMID 33438817›Full record

ArticleMolecular systems biology2020

Large-scale survey and database of high affinity ligands for peptide recognition modules.

Joan Teyra, Abdellali Kelil, Shobhit Jain, Mohamed Helmy, Raghav Jajodia, Yogesh Hooda, Jun Gu, Akshay A D'Cruz, Sandra E Nicholson, Jinrong Min and 4 more

Abstract read
In one paragraph

Article in Molecular systems biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

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  13. Peptide-binding specificity prediction using fine-tuned protein structure prediction networks.Proceedings of the National Academy of Sciences of the United States of America · 2023
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  14. Review
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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

14 authors.

Joan TeyraThe Donnelly Centre, University of Toronto, Toronto, ON, Canada.ORCID 0000-0003-2816-339X
Abdellali KelilThe Donnelly Centre, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-0406-2052
Shobhit JainThe Donnelly Centre, University of Toronto, Toronto, ON, Canada.
Mohamed HelmyThe Donnelly Centre, University of Toronto, Toronto, ON, Canada.
Raghav JajodiaIndian Institute of Engineering Science and Technology, Shibpur, India.
Yogesh HoodaThe Donnelly Centre, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-7181-9254
Jun GuThe Donnelly Centre, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-1898-9393
Akshay A D'CruzThe Walter and Eliza Hall Institute of Medical Research, Parkville, Vic., Australia.ORCID 0000-0003-2718-0673
Sandra E NicholsonThe Walter and Eliza Hall Institute of Medical Research, Parkville, Vic., Australia.
Jinrong MinStructural Genomics Consortium, University of Toronto, Toronto, ON, Canada.
Marius SudolDepartment of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Philip M KimThe Donnelly Centre, University of Toronto, Toronto, ON, Canada.ORCID 0000-0003-3683-152X
Gary D BaderThe Donnelly Centre, University of Toronto, Toronto, ON, Canada.ORCID 0000-0003-0185-8861
Sachdev S SidhuThe Donnelly Centre, University of Toronto, Toronto, ON, Canada.ORCID 0000-0001-7755-5918

Funding

CIHR MOP-93684
6 · The paper itself

Abstract

Many proteins involved in signal transduction contain peptide recognition modules (PRMs) that recognize short linear motifs (SLiMs) within their interaction partners. Here, we used large-scale peptide-phage display methods to derive optimal ligands for 163 unique PRMs representing 79 distinct structural families. We combined the new data with previous data that we collected for the large SH3, PDZ, and WW domain families to assemble a database containing 7,984 unique peptide ligands for 500 PRMs representing 82 structural families. For 74 PRMs, we acquired enough new data to map the specificity profiles in detail and derived position weight matrices and binding specificity logos based on multiple peptide ligands. These analyses showed that optimal peptide ligands resembled peptides observed in existing structures of PRM-ligand complexes, indicating that a large majority of the phage-derived peptides are likely to target natural peptide-binding sites and could thus act as inhibitors of natural protein-protein interactions. The complete dataset has been assembled in an online database (http://www.prm-db.org) that will enable many structural, functional, and biological studies of PRMs and SLiMs.

Indexed as

Databases, ProteinSurveys and QuestionnairesAmino Acid SequenceBacteriophagesHumansLigandsPeptidesLigandsPeptidesdomain specificitypeptide inhibitorspeptide librarypeptide recognition modulesphage display

Identifiers

PMID33438817
PMCPMC7724964

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.