Investigating the anticancer potential of phytochemicals from the mangrove Rhizophora mucronata as inhibitors of lung cancer-associated proteins: Insights from multiscale computational and in silico analyses.

Lung cancer remains the leading cause of cancer-related mortality worldwide, with a five-year survival rate of approximately 20-25% despite advances in targeted therapy and immunotherapy. There is a continuous need for novel, low-toxicity compounds capable of modulating key oncogenic pathways in non-small cell lung cancer (NSCLC). Mangrove ecosystems are rich reservoirs of bioactive phytochemicals, yet the inhibitory potential of compounds from Rhizophora mucronata against validated lung cancer-associated proteins has not been systematically explored using multi-scale computational approaches. This study employed an integrated computational pipeline to evaluate 14 phytochemicals from R. mucronata. Density Functional Theory (DFT) calculations at the B3LYP/6-31G* level were performed to characterize electronic properties of the ligands. Molecular docking studies were conducted using both AutoDock Vina (PyRx) and Schrödinger Glide against the Keap1 Kelch domain (PDB 1X2J) and the YEATS2 YEATS domain (PDB 5XNV). Top-ranked complexes were subjected to 100-ns molecular dynamics (MD) simulations in Desmond, and pharmacokinetic and toxicity profiles were predicted using SwissADME and pkCSM. Among the screened compounds, ligand L10 (cyclohexane-1,2,3,4,5,6-hexaol) exhibited the smallest HOMO-LUMO energy gap (0.36 eV), favorable binding affinities (Glide score of -7.789 kcal/mol against 1X2J), multiple hydrogen-bonding interactions, and stable complex behavior during MD simulations (Cα RMSD < 3 Å). Several other ligands (L02, L05, and L07) also displayed promising profiles. Most compounds complied with Lipinski's rule of five and showed acceptable predicted ADMET properties. These preliminary findings suggest that Rhizophora mucronate -derived phytochemicals, particularly L10, are promising candidates for further experimental evaluation as modulators of Keap1 and YEATS2 in lung cancer. This study provides a computational framework for prioritizing natural product leads from mangrove species for subsequent in vitro and in vivo validation.