Evidence map›Paper›PMID 40663335›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

Quantitative Affinity Screening of Macrocyclic Peptide Libraries Using Yeast Surface Display Technology.

Ylenia Mazzocato, Zhanna Romanyuk, Monica Chinellato, Camilla Mazzucco, Linda Trevisan, Sara Linciano, Alessandro Angelini

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Ylenia Mazzocato *Department of Molecular Sciences and Nanosystems, Ca' Foscari University of Venice, Mestre, Venice, Italy.
Zhanna Romanyuk *Department of Molecular Sciences and Nanosystems, Ca' Foscari University of Venice, Mestre, Venice, Italy.
Monica ChinellatoDepartment of Molecular Sciences and Nanosystems, Ca' Foscari University of Venice, Mestre, Venice, Italy.
Camilla MazzuccoDepartment of Molecular Sciences and Nanosystems, Ca' Foscari University of Venice, Mestre, Venice, Italy.
Linda TrevisanDepartment of Molecular Sciences and Nanosystems, Ca' Foscari University of Venice, Mestre, Venice, Italy.
Sara LincianoDepartment of Molecular Sciences and Nanosystems, Ca' Foscari University of Venice, Mestre, Venice, Italy. sara.linciano@unive.it.
Alessandro AngeliniDepartment of Molecular Sciences and Nanosystems, Ca' Foscari University of Venice, Mestre, Venice, Italy. alessandro.angelini@unive.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This protocol details the use of yeast surface display technology for the in vitro-directed evolution of disulfide-tethered macrocyclic peptide ligands. In the first section, we describe the generation of large naïve combinatorial libraries encoding cysteine-rich peptide sequences expressed on the yeast cell surface using homologous recombination-based methods. In the second section, we detail the use of fluorescence-activated cell sorting to rapidly and effectively isolate yeast-encoding disulfide-tethered macrocyclic peptide ligands with favorable binding properties. In the last section, we describe the quantitative characterization of isolated disulfide-tethered macrocyclic peptide ligand variants directly as yeast cell surface fusions, thus eliminating the need for costly and time-consuming synthesis and purification.

Indexed as

Cell Surface Display TechniquesPeptide LibraryPeptidesPeptides, CyclicSaccharomyces cerevisiaeDisulfidesFlow CytometryLigandsDisulfidesLigandsPeptide LibraryPeptidesPeptides, CyclicCyclic peptideDirected evolutionDisulfide-tethered macrocyclic peptideDrug discoveryHigh-throughput screeningYeast surface display

Identifiers

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.