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April 18, 2026Biochemistry0 citationsOpen Access

Phage Display Driven Identification and Computational Mapping of Macrocyclic Peptides Targeting RhoA G17V

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SASebin AbrahamCZChaoyang ZhuLLLai Hoang Son Le

Key Points

  • This research aims to identify and characterize macrocyclic peptides that effectively bind to the mutant RhoA G17V protein.
  • Utilized phage display with cyclic peptide libraries to screen for binders to RhoA G17V.
  • Conducted biopanning using two peptide libraries, a 10-mer and a 12-mer.
  • Employed computational docking and molecular dynamics simulations to analyze peptide-protein interactions.
  • Applied alanine scanning mutagenesis to validate binding interfaces within the identified peptides.
  • Identified Z1, a macrocyclic peptide with a binding affinity of 136 nM to RhoA G17V, the highest recorded affinity.
  • The 12-mer cyclic library outperformed the 10-mer library in terms of binding strength.
  • Molecular dynamics simulations confirmed stable interactions driven by hydrophobic and electrostatic forces.

Abstract

Mutant RhoA G17V is a clinically significant yet historically undruggable oncogenic GTPase that drives angioimmunoblastic T-cell lymphoma through a neomorphic interaction with the guanine nucleotide exchange factor Vav1. Its rigid GTPase fold, absence of deep binding pockets, and transient protein-protein interfaces have hindered conventional small-molecule approaches, creating a critical need for alternative therapeutic modalities. Here, we report a systematic strategy to target RhoA G17V using macrocyclic peptides. Two complementary phage-displayed cyclic peptide libraries, an AcrK-mediated 10-mer cyclic library and a CAmCBT-cyclized 12-mer library, were subjected to high-stringency biopanning against recombinant RhoA G17V. While the 10-mer library yielded moderate-affinity binders, the 12-mer library enabled the discovery of Z1, a macrocyclic peptide with submicromolar affinity (KD = 136 nM), representing the highest-affinity peptide reported for RhoA G17V to date. Computational docking combined with long-timescale molecular dynamics simulations revealed a stable peptide-protein interaction governed by cooperative hydrophobic and electrostatic interactions. Systematic alanine scanning mutagenesis experimentally validated the predicted binding determinants, confirming the key residues within the macrocycle. Collectively, this work establishes macrocyclic phage display as a powerful and generalizable platform for discovering high-affinity ligands against challenging mutant GTPases and lays a foundation for the development of precision peptide-based therapeutics.

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Cite This Study

Abraham et al. (2026) studied this question.

synapsesocial.com/papers/69e31f1a40886becb653e8achttps://doi.org/10.1021/acs.biochem.6c00058
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