Evidence map›Paper›PMID 37175549›Full record

ReviewInternational journal of molecular sciences2023

Targeting Protein-Protein Interfaces with Peptides: The Contribution of Chemical Combinatorial Peptide Library Approaches.

Alessandra Monti, Luigi Vitagliano, Andrea Caporale, Menotti Ruvo, Nunzianna Doti

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 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

5 authors.

Alessandra MontiInstitute of Biostructures and Bioimaging (IBB), National Research Council (CNR), 80131 Napoli, Italy.
Luigi VitaglianoInstitute of Biostructures and Bioimaging (IBB), National Research Council (CNR), 80131 Napoli, Italy.ORCID 0000-0002-3032-3375
Andrea CaporaleInstitute of Crystallography (IC), National Research Council (CNR), Strada Statale 14 km 163.5, Basovizza, 34149 Triese, Italy.
Menotti RuvoInstitute of Biostructures and Bioimaging (IBB), National Research Council (CNR), 80131 Napoli, Italy.ORCID 0000-0001-5997-756X
Nunzianna DotiInstitute of Biostructures and Bioimaging (IBB), National Research Council (CNR), 80131 Napoli, Italy.ORCID 0000-0003-2952-6658

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein-protein interfaces play fundamental roles in the molecular mechanisms underlying pathophysiological pathways and are important targets for the design of compounds of therapeutic interest. However, the identification of binding sites on protein surfaces and the development of modulators of protein-protein interactions still represent a major challenge due to their highly dynamic and extensive interfacial areas. Over the years, multiple strategies including structural, computational, and combinatorial approaches have been developed to characterize PPI and to date, several successful examples of small molecules, antibodies, peptides, and aptamers able to modulate these interfaces have been determined. Notably, peptides are a particularly useful tool for inhibiting PPIs due to their exquisite potency, specificity, and selectivity. Here, after an overview of PPIs and of the commonly used approaches to identify and characterize them, we describe and evaluate the impact of chemical peptide libraries in medicinal chemistry with a special focus on the results achieved through recent applications of this methodology. Finally, we also discuss the role that this methodology can have in the framework of the opportunities, and challenges that the application of new predictive approaches based on artificial intelligence is generating in structural biology.

Indexed as

Artificial IntelligencePeptide LibraryBinding SitesMembrane ProteinsPeptidesProtein BindingMembrane ProteinsPeptide LibraryPeptidespeptidespeptidomimeticsprotein–protein interactionsynthetic combinatorial approaches

Identifiers

PMID37175549
PMCPMC10178479

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.