Enhanced Binding Site Identification in Protein–Ligand Complexes with a Combined Blind Docking and Dipolar Electron Paramagnetic Resonance Approach

Understanding protein-drug complex structures is crucial for elucidating therapeutic mechanisms and side effects. Blind docking facilitates site identification but is hindered by computational complexity and imprecise scoring, causing ambiguity. Dipolar electron paramagnetic resonance (EPR) provides spin-spin distances but struggles to determine relative positions within complexes. We present a novel approach combining GPU-accelerated blind docking with EPR distance constraints to enhance binding site detection. Our algorithm uses a single EPR distance distribution to filter and validate docking results. Ligand poses from blind docking are clustered, filtered by expected distances, and refined through focused docking. To illustrate our approach, we investigated human serum albumin binding with porphyrin-based photosensitizers used in photodynamic therapy. Combining docking and EPR, we identified possible binding sites, demonstrating that EPR data significantly reduce possible configurations and provide experimentally validated information. This strategy produces a detailed map of photoligand binding sites, revealing that binding may occur away from standard albumin sites and often involves multiple locations. Furthermore, it overcomes key limitations of fluorescence-based methods, which are prone to misinterpretation in albumin studies due to non one-to-one donor-acceptor relationships. By resolving ambiguities in both blind docking and EPR, our framework provides a versatile platform for investigating EPR-active ligands.