Computational Insights into Flavonoids for ADAMTS-5 Exosite Inhibition in Knee Osteoarthritis: Docking, MD Simulations, and Machine Learning-Guided Structure Prediction

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Abstract
The limited selectivity of most catalytic-site ADAMTS-5 inhibitors and the necessity to preserve aggrecan integrity in early-grade knee osteoarthritis require the development of selective aggrecanase inhibitors. The present study conducted rational in silico screening of flavonoids as potential ADAMTS-5 inhibitors by integrating high-throughput virtual screening, molecular docking, and molecular dynamic simulations targeting the exosite domains of ADAMTS-5 (the Disintegrin-like and spacer domain). The objective was to identify plant-derived flavonoids with favorable drug-like properties and specific interactions towards the ADAMTS-5 exosite as a more targeted alternative to catalytic-site inhibition. In this study, 847 flavonoids were screened using drug-likeness and ADME criteria to identify promising leads. The top 16 selected flavonoids were further subjected to molecular docking and SAR analysis. Of these compounds, Homoeriodictyol satisfied key drug-likeness criteria and exhibited the highest binding affinity to the Disintegrin-like domain, with a binding energy of −23.1 kcal/mol and favorable interactions. Molecular dynamics simulations of the Homoeriodictyol–ADAMTS-5 complex over 100 ns demonstrated stable binding throughout the trajectory. DCCM analysis and PCA further supported the proposed exosite-mediated modulation. To extend exosite mapping beyond the Disintegrin-like domain, this study also examined the spacer domain using a machine-learning-predicted structural model and identified key residues that contribute to ligand binding.

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