Covalent cyclic peptides represent a transformative approach for targeting challenging protein-protein interactions (PPIs) characterized by flat, extensive binding surfaces. Recent advances in electrophilic phage display now enable the evolution of these peptides through integrating sulfur(VI) fluoride exchange (SuFEx) chemistry with functional selection strategies. This innovative platform combines genetic encoding with site-specific cyclization and warhead incorporation to generate high-affinity, irreversible binders. When targeting the SARS-CoV-2 Spike-ACE2 interface, the approach produced sub-100 nM inhibitors with >10-fold improved potency over non-covalent analogues. The methodology's success against this clinically relevant target underscores its potential to address longstanding challenges in PPI modulation, particularly for high-value targets in oncology and neurodegeneration. By combining covalent engagement with phage display's evolutionary power, this technology establishes a new paradigm for developing mechanistically validated peptide therapeutics against previously intractable interactions. Keywords: covalent peptide inhibitors, cyclic peptide therapeutics, phage display evolution, protein-protein interaction inhibition, SuFEx chemistry, irreversible binders, SARS-CoV-2 inhibitors, Spike-ACE2 disruption, electrophilic warheads, undruggable targets, functional selection, peptide macrocycles, PPI drug discovery, covalent phage display
Read full abstract- All Solutions
Editage
One platform for all researcher needs
Paperpal
AI-powered academic writing assistant
R Discovery
Your #1 AI companion for literature search
Mind the Graph
AI tool for graphics, illustrations, and artwork
Journal finder
AI-powered journal recommender
Unlock unlimited use of all AI tools with the Editage Plus membership.
Explore Editage Plus - Support
Overview
10255 Articles
Published in last 50 years
Articles published on Cyclic Peptide
Authors
Select Authors
Journals
Select Journals
Duration
Select Duration
9872 Search results
Sort by Recency