Targeting TMPRSS2-ERG Fusion-Driven Prostate Cancer using Novel HBS-α-Helicomimics
Sushmita KunduiD, Promit GangulyiD, Lalnunfela Varte, Shifali MahajaniD, Erode N. PrabhakaraniD, Bushra AteeqiD
Abstract
Gene fusions between the androgen receptor (AR)-responsive gene TMPRSS2 and ERG occur in approximately 50% of prostate cancers (PCa), thereby promoting tumorigenesis through aberrant ERG expression. Therapeutic targeting of transcription factor-DNA interfaces remains a formidable challenge, largely owing to the entropic penalty associated with peptide folding during target engagement. Here, we describe the structure-guided design and preclinical evaluation of hydrogen-bond surrogate (HBS)-constrained alpha-helicomimics targeting the ERG-DNA recognition interface. Structural analysis of ERG-DNA complex revealed that DNA binding induces elongation of recognition helix H4 from approximately 2.5 to 4.0 helical turns. To stabilize the bioactive conformation, we incorporated an N-terminal HBS macrocycle, introduced D363E and S366E mutations to enhance DNA binding and structural stability, and added dual NLS-TAT tags to facilitate cellular delivery. Biochemical and cellular assays demonstrated that the lead compound, ERG helicomimics, competitively inhibited ERG binding to ETS motifs, disrupted ERG association with AR and other cofactors, leading to suppressed ERG transcriptional activity. Chromatin immunoprecipitation-qPCR confirmed reduced ERG occupancy at regulatory regions of canonical target genes, accompanied by downregulation of ERG-driven transcriptional programs. ERG helicomimics also reduced proliferation, migration, and invasion in ERG-positive PCa cells. In a murine xenograft model of TMPRSS2-ERG-positive PCa, systemic ERG helicomimics treatment suppressed tumor growth without overt toxicity and reduced Ki-67 expression compared with the designated control peptide. Collectively, our findings support HBS-constrained ERG helicomimics as a rational strategy for targeting ERG-driven PCa and warrant further therapeutic optimization.
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