Evidence mapPaperPMID 42450332Full record

ReviewInternational journal of molecular sciences2026

Cyclic Peptides as Modulators of Protein-Protein Interactions: A Survival Guide from Discovery Platforms to AI-Driven Design.

Sara Salvi, Pasquale Linciano, Simona Collina, Giacomo Rossino

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In one paragraph

Review in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Sara SalviDepartment of Drug Sciences, University of Pavia, Via Taramelli 12, 27100 Pavia, Italy.ORCID 0009-0001-1900-1965
Pasquale LincianoDepartment of Drug Sciences, University of Pavia, Via Taramelli 12, 27100 Pavia, Italy.ORCID 0000-0003-0382-7479
Simona CollinaDepartment of Drug Sciences, University of Pavia, Via Taramelli 12, 27100 Pavia, Italy.ORCID 0000-0002-2954-7558
Giacomo RossinoDepartment of Drug Sciences, University of Pavia, Via Taramelli 12, 27100 Pavia, Italy.ORCID 0000-0002-1008-5736

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein-protein interactions (PPIs) represent a vast and largely underexplored landscape of therapeutic targets, yet their structural features-including large, flat, and dynamic interfaces-have historically limited their druggability. In this context, cyclic peptides have emerged as a powerful class of PPI modulators, sitting at the interface between biologics and small molecules, and thus garnering key advantages of both classes. Their conformational constraint enhances binding affinity, proteolytic stability and, in some instances, cell permeability, thus enabling access to intracellular targets. This review provides an updated overview of cyclic peptides as modulators of PPIs, focusing on both conceptual foundations and practical strategies for their discovery and optimization. The main discovery approaches include natural sources, de novo design based on secondary structure mimetics, high-throughput screening, and computational approaches. Integration of these complementary strategies is crucial to enhance success rates in the discovery of effective and developable cyclic peptides. Accordingly, the present review aims to provide a practical guide for researchers entering this rapidly growing field, outlining current opportunities, methodological advances, and remaining challenges in the development of cyclic peptide-based PPI modulators.

Indexed as

Artificial IntelligenceDrug DiscoveryPeptides, CyclicProtein Interaction MapsAnimalsDrug DesignHumansProtein BindingPeptides, Cycliccomputational methodscyclic peptidescyclotidesmRNA displaynucleotide-encoded mass library screeningphage displayprotein–protein interactionsSICLOPPSstabilized α-helical peptidesstapled peptides

Identifiers

PMID42450332
PMCPMC13361436

What Socratic holds

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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 Socratic graph.