Targeting key proteins of pleural mesothelioma using plumbagin-indole-3-propionic acid ester: Insights from network pharmacology, molecular dynamics simulation and machine learning-based analysis.

This study explores the network pharmacology (NP) and molecular dynamics (MD) simulation analysis of pleural mesothelioma (PM) related enzymes. Through the investigation of 1253 associated genes, culminating in a protein-protein interaction (PPI) network constructed using the STRING database. Pathway analysis identified critical signaling pathways, including MAPK, PI3K/AKT, and RAS, associated with PM pathogenesis. Furthermore, we have synthesized plumbagin-indole-3-proponic acid (PLU-IPA) from plumbagin (PLU) and assessed the toxicity profiles of PLU and PLU-IPA, revealing a reduction in toxicity following IPA incorporation. MD simulations highlighted the stability of PLU-IPA complexes with various proteins (IL6, KRASG12D, SRC and TNFα), supported by analyses of root mean square deviation (RMSD), root mean square fluctuations (RMSF), clustering, and dynamic cross-correlation matrices (DCCM). Principal component analysis (PCA) assessment elucidated the conformational dynamics of the complexes. Additionally, MMGBSA and decomposition binding free energy calculations provided insights into the energetics of ligand binding. Notably, low-frequency mode analyses via Elastic Network Models (ENM) offered a comprehensive view of protein flexibility and ligand interactions. The prominent conformation modifications of each complex during MD simulation has been determined via Markov state model confirms the stability of PLU-IPA in the binding site. These findings underscore the intricate molecular mechanisms underlying PM and highlight PLU-IPA as a potential therapeutic target for future investigations.