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

“Phage Display Driven Identification and Computational Mapping of Macrocyclic Peptides Targeting RhoA G17V. Abraham S(1), Zhu C(1), Le LHS(1), Alugubelli YR(1), Nonomura T(2), Huang Y(2), Hampton JT(1), Zhou Y(2), Liu WR(1)(2)(3)(4)(5). Author information: (1)Texas A&M Drug Discovery Center and Department of Chemistry, Texas A&M University, College Station, Texas 77843, United States. (2)Institute of Biosciences and Technology and Department of Translational Medical Sciences, College of Medicine, Texas A&M University, Houston, Texas 77030, United States. (3)Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas 77843, United States. (4)Department of Cell Biology and Genetics, College of Medicine, Texas A&M University, College Station, Texas 77843, United States. (5)Department of Pharmaceutical Sciences, Texas A&M University, College Station, Texas 77843, United States. 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.”