Graph-based and molecular modeling approaches to identify TpiA as a noval therapeutic target in Neisseria meningitidis.

Neisseria meningitidis continues to be a major etiology of invasive meningococcal disease, and the increasing frequency of antimicrobial resistance necessitates the discovery of new therapeutic strategies. This study aimed to identify and prioritize novel, pathogen-specific drug targets and potential natural inhibitors using an integrative computational approach integrating graph-based pangenome analysis, subtractive genomics, and network topology. Pangenome construction and subsequent subtractive genomics of the core genes, followed by network analysis, shortlisted five essential hub proteins (guaA, pykA, tktA, eno, and tpiA), with tpiA, a central glycolytic enzyme with little prior therapeutic exploration, was selected as a promising drug target for subsequent phytochemical screening. Subsequently, phytochemicals from Cinnamomum verum were screened against tpiA in order to identify potential inhibitors. The top three candidate compounds underwent 100 ns molecular dynamics and MM-GBSA analyses, exhibiting lower RMSD and reduced residue fluctuations compared to the apo form, while maintaining stable radius of gyration and SASA. Further insilico validation through MM-GBSA confirmed favorable binding energies with beta-sitosterol (- 21.28 kcal·mol⁻1), stigmasterol (- 17.01 kcal·mol⁻1), and riboflavin (- 16.09 kcal·mol⁻1) with van der Waals interactions predominating for the sterols. Collectively, these in-silico findings validate TpiA as a promising antibacterial target and highlight Cinnamomum verum phytosterols, particularly beta-sitosterol and stigmasterol, as lead scaffolds warranting further experimental exploration\.