Computational insights into pyridoxal 5-phosphate for cataract therapy: targeting TNF-α, IL-6, and IL-1β through...

This study computationally investigated the effect of pyridoxal 5-phosphate (PLP) interacts with key inflammatory cytokines such as TNF-α, IL-6, and IL-1β implicated in cataract, using network pharmacology, molecular docking, and molecular dynamics simulation. A network pharmacology approach was employed. Cataract-associated targets were retrieved from GeneCards and OMIM databases. Cataract-associated genes were identified using DisGeNET and intersected with targets predicted by Swiss Target Prediction. Protein-protein interaction (PPI) networks were analyzed using STRING and Cytoscape. Molecular docking was conducted using Autodock Vina, and molecular dynamics (MD) simulations were performed with Desmond to evaluate the stability of ligand-protein interactions. A network pharmacology approach, involving 1633 non-redundant genes from 10,069 GeneCards and 634 OMIM entries, was used to predict targets relevant to cataract. Functional enrichment analysis identified metabolic and signal transduction pathways affected by PLP. Molecular docking showed strong binding of PLP to inflammatory targets, with the highest affinity for TNF-α (7JRA; -7.09 kcal/mol), followed by IL-1β (6Y8M; -5.511 kcal/mol) and IL-6 (1ALU; -5.156 kcal/mol), suggesting its potential to modulate cataract-associated inflammation. Molecular dynamics simulations confirmed the stability of these interactions, with IL-1β showing the most constrained dynamics and highest stability - 181.00 ± 12.90 kcal/mol, while 7JRA (-48.58 ± 6.26) showed intermediate stability during simulation. These computational findings suggest that PLP shows potential as a pharmacological intervention for cataracts. Further in vitro and in vivo experimental validation is required to confirm its therapeutic potential.

The online version contains supplementary material available at 10.1007/s40203-026-00594-8.