Intrinsic Network Pharmacology Guided Simulation of NAFLD Collapse and Recovery: A Systems Level Investigation of Picrorhiza Kurroa via Multi Layered Network Integration

Abstract

Non-alcoholic fatty liver disease (NAFLD) is a significant world health burden, occurring in more than 25% of the adult population and advancing to steatohepatitis, fibrosis, and eventually cirrhosis or hepatocellular carcinoma. Although it is increasingly prevalent, there are limited pharmacological treatments for NAFLD available, which are mostly symptomatic but not aimed at the systemic multi-factorial dysfunctions at its core. Herbal Ayurvedic medicine, such as the hepatoprotective plant Picrorhiza kurroa (Kutki), represents a fertile ground for multi-targeted therapeutic intervention. Yet, a clear need exists for system-level mechanistic models that can assess such intricate botanicals. Our research initiates an enhanced simulation-based approach unifying classical network pharmacology and our in-house developed 7+1-layer Intrinsic Network Pharmacology (INP) model to investigate the systemic repair capacity of P. kurroa in NAFLD. Beginning with compound-target-pathway (CTP) mapping and network analysis of P. kurroa's bioactive constituents, high-priority targets were evaluated across molecular, enzymatic, signaling, redox, inflammatory, autophagic, and epigenetic levels. The last "+1" dynamic layer includes an ODE-based simulation platform to model disease collapse versus Rasayana-mediated recovery over time. INP and classical pharmacology integration allows high-resolution modeling of the mechanisms by which Kutki phytoconstituents, including Kutkin, Picroside I & II, apocynin, androsin, and cucurbitacins, modulate intricate cellular networks. An INP Fit Score was created to measure compound efficacy across system layers, and differential system trajectories were calculated to model therapeutic responses. This multi-scale computational system not only validates the efficacy of P. kurroa as a systems-level modulator for NAFLD recovery but also provides a replicable paradigm for investigating polyherbal formulations for chronic diseases. The model sets the stage for personalized, network-based Rasayana pharmacology and provides a template for converging traditional medicine with systems biology.