In-silico prediction of multi‑target mechanisms of Pinellia ternata phytochemicals in lung cancer: Evidence from a graph‑attention‑guided virtual screening and multi‑scale simulations

Pinellia ternate has long been used to treat respiratory diseases, possessing potential anti-tumor activity and exhibiting multi-component, multi-target characteristics. This study prioritized lung cancer-related targets using the HERBGAT framework based on graph attention networks (GAT). High-quality PDB structures were retrieved, and diffusion-generative docking was performed to construct complex conformations and assess their confidence levels. Molecular dynamics simulations of representative complexes were conducted over 200 ns, and binding free energies were estimated using the MM/PBSA method. The pharmacokinetic characteristics of the bioactive compounds were evaluated using Swiss ADME and PreADMET computational tools, and density functional theory (DFT) analysis using ORCA software was combined to explore their electronic structure and properties. In this study, the potential targets of Pinellia ternata highly overlap with lung cancer pathological genes, with FGFR4, CDK2, JAK2, KDR, PAK4, PTK2 and PDGFRA being the core. Baicalein exhibits a conserved binding mode of "hinge hydrogen bond-aromatic interlayer-hydrophobic groove" at targets such as PTK2/KDR/JAK2. Energy decomposition indicates that van der Waals forces and nonpolar solvation are the main thermodynamic driving forces for complex formation. Density functional theory (DFT) analysis further reveals that the high electronic "softness" of baicalein and its sensitive response to the environment in terms of frontier orbitals and electrostatic potential may be related to its high affinity, which is ubiquitous in different pockets. This study provides a computational chain of evidence for the intervention of Pinellia ternata's active ingredient on lung cancer-related targets. The well-defined cross-target migratory pharmacophore of baicalein, consistent energy and kinetics, and the oral pharmacodynamics of ADMET indicate that it can serve as a multi-target lead compound targeting the PTK2/KDR migration-angiogenesis pathway, while also affecting JAK2 and CDK2. Given that the current evidence is based on in-silico predictions, further validation through target enzymology, binding thermodynamics, and cellular pathway experiments is needed.