In Silico Screening of Peptide Inhibitors of PHLDA1-Encoded Protein Targeting Cardiovascular Diseases
Abstract
The PHLDA1-encoded protein (PEP) is a pivotal regulator of cardiomyocyte apoptosis and a promising therapeutic target for cardiovascular diseases. Leveraging in silico approaches, we characterized PEP's structure using AlphaFold3 (AF3) and refined it via molecular dynamics (MD) simulations with various force fields. Kinetic and thermodynamics analysis further confirmed revealed that the Amber99 force field induced the most significant structural change, with the most significant decrease in radius of gyration and lowest potential energy. High-throughput screening of 20 phenylalanine-based dipeptides (FA-FY) revealed sequence-dependent binding to PEP, with FF, FH, FP, and FY exhibiting the maximum count of binders (11, 7, 6, and 6, respectively). Key residues (e.g., L55, C60, E142, E89) formed a continuous binding groove, while FF dipeptides demonstrated cooperative aggregation-enhanced binding. Notably, low-pLDDT regions (< 50) frequently participated in ligand interactions, challenging the rigid "lock-and-key" paradigm and underscoring the role of intrinsic disorder in binding. this work establishes PEP as a tractable target for dipeptide inhibitors and provides a computational framework for designing peptide-based therapeutics against cardiac injury.
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