Evidence map›Paper›PMID 40411416›Full record

ArticleProtein science : a publication of the Protein Society2025

Defining short linear motif binding determinants by phage display-based deep mutational scanning.

Caroline Benz, Lars Maassen, Leandro Simonetti, Filip Mihalic, Richard Lindqvist, Ifigenia Tsitsa, Aimiliani Konstantinou, Per Jemth, Anna K Överby, Norman E Davey and 1 more

Abstract read
In one paragraph

Article in Protein science : a publication of the Protein Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

11 authors.

Caroline BenzDepartment of Chemistry - BMC, Uppsala University, Uppsala, Sweden.
Lars MaassenDepartment of Chemistry - BMC, Uppsala University, Uppsala, Sweden.
Leandro SimonettiDepartment of Chemistry - BMC, Uppsala University, Uppsala, Sweden.
Filip MihalicDepartment of Medical Biochemistry and Microbiology, Uppsala University, BMC, Uppsala, Sweden.ORCID 0000-0002-6840-2319
Richard LindqvistDepartment of Clinical Microbiology, Umeå University, Umeå, Sweden.
Ifigenia TsitsaDivision of Cancer Biology, The Institute of Cancer Research, London, UK.ORCID 0000-0001-8154-5528
Aimiliani KonstantinouDepartment of Chemistry - BMC, Uppsala University, Uppsala, Sweden.
Per JemthDepartment of Medical Biochemistry and Microbiology, Uppsala University, BMC, Uppsala, Sweden.ORCID 0000-0003-1516-7228
Anna K ÖverbyDepartment of Clinical Microbiology, Umeå University, Umeå, Sweden.
Norman E DaveyDivision of Cancer Biology, The Institute of Cancer Research, London, UK.
Ylva IvarssonDepartment of Chemistry - BMC, Uppsala University, Uppsala, Sweden.ORCID 0000-0002-7081-3846

Funding

Cancer Research UK A28159Cancer Research UK C68484Vetenskapsrådet 2020-03380Vetenskapsrådet 2020-04395Vetenskapsrådet 2022-05278
6 · The paper itself

Abstract

Deep mutational scanning (DMS) has emerged as a powerful approach for evaluating the effects of mutations on binding or function. Here, we developed a DMS by phage display protocol to define the specificity determinants of short linear motifs (SLiMs) binding to peptide-binding domains. We first designed a benchmarking DMS library to evaluate the performance of the approach on well-known ligands for 11 different peptide-binding domains, including the talin-1 PTB domain, the G3BP1 NTF2 domain, and the MDM2 SWIB domain. Comparison with a set of reference motifs from the eukaryotic linear motif (ELM) database confirmed that the DMS by phage display analysis correctly identifies known motif binding determinants and provides novel insights into specificity determinants, including defining a non-canonical talin-1 PTB binding motif with a putative extended conformation. A second DMS library was designed, aiming to provide information on the binding determinants for 19 SLiM-based interactions between human and SARS-CoV-2 proteins. The analysis confirmed the affinity determining residues of viral peptides binding to host proteins and refined the consensus motifs in human peptides binding to five domains from SARS-CoV-2 proteins, including the non-structural protein (NSP) 9. The DMS analysis further pinpointed mutations that increased the affinity of ligands for NSP3 and NSP9. An affinity-improved cell-permeable NSP9-binding peptide was found to exert stronger antiviral effects than the wild-type peptide. Our study demonstrates that DMS by phage display can efficiently be multiplexed and applied to refine binding determinants and shows how the results can guide peptide-engineering efforts.

Indexed as

SARS-CoV-2Amino Acid MotifsBinding SitesCell Surface Display TechniquesHumansMutationPeptide LibraryPeptidesProtein BindingProtein DomainsPeptide LibraryPeptidesdeep mutational scanningNSP9peptide‐phage displaySARS‐CoV‐2short linear motif

Identifiers

PMID40411416
PMCPMC12102759

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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.