From Pharmacophore to Free Energy: A Multi Scale Approach to DJ 1 (PARK7) Inhibitor Identification

Abstract

DJ-1 (PARK7), a multifunctional protein implicated in both neurodegeneration and oncogenesis, remains an underexploited therapeutic target due to limitations in the structural and dynamic interrogation of its ligand-binding landscape. In this study, we employed an integrated computational pipeline to identify novel DJ-1 modulators, leveraging pharmacophore-guided virtual screening, molecular docking, molecular dynamics (MD) simulations, and MM/PBSA binding free energy calculations. Using the 7PA3 crystal structure and its co-crystallized ligand (6SI) as a reference, we constructed a pharmacophore model encapsulating key noncovalent features around the redox-active Cys106 and neighboring residues. A filtered library of 180 PubChem analogs underwent structure-based docking, identifying three top candidates (CID140877623, CID108749815, CID118980429) with superior binding affinities relative to 6SI. MD simulations over 200 ns revealed CID140877623 as the most dynamically stable complex, marked by a low RMSD, minimal fluctuation, and compact conformation. Notably, MM/PBSA analysis confirmed its high binding free energy, surpassing the reference ligand and underscoring its strong van der Waals and electrostatic contributions. These findings position CID140877623 as a high-confidence lead for downstream biochemical validation. This work not only expands the repertoire of DJ-1-targeting scaffolds but also establishes a robust in silico paradigm that integrates pharmacophore modeling with dynamic ensemble screening for rational inhibitor prioritization in redox-regulated protein targets.