Exploring flavonoids as potential inhibitors for Enterococcus faecium nicotinate nucleotide adenylyltransferase: An integration of in silico with empirical studies

Abstract

• Nicotinate nucleotide adenylyltransferase (NNAT) is identified as a promising drug development target due to its crucial role in the nicotinate nucleotide biosynthesis pathway essential for bacterial survival. • The study screened a library of 1427 compounds from MedChemExpress using computational modeling and fluorescence methods to find potential inhibitors against Enterococcus faecium NNAT (EfNNAT). • Quercetin 3-O-beta-d-glucose-7-O-beta-d-gentiobioside (QGG) emerged as the top inhibitor from both energy-minimised and 100-ns MD-simulated models after rigorous docking protocols (HTVS, SP, and XP). • Molecular spectroscopy confirmed QGG's binding to EfNNAT by displacing fluorescent probes, although thermal shift assays showed minimal impact on protein stability. Nicotinate nucleotide adenylyltransferase (NNAT) emerges as a promising target for drug development, given its pivotal role in the nicotinate nucleotide biosynthesis pathway crucial for bacterial survival. Using computational modelling and fluorescence methods, this study screened a library of 1427 compounds from MedChemExpress as potential inhibitors against Enterococcus faecium NNAT (EfNNAT). We employed Maestro's Glide HTVS, SP, and XP docking protocols to identify compounds with high binding affinity. The screening utilised two models of the EfNNAT crystal structure: energy-minimised and 100-ns MD-simulated model, hypothesising conformational change that may influence ligand selectivity in the HTVS study. Our findings revealed variations between the minimised versus MD-simulated models, impacting ligand selectivity by each model post-HTVS. However, quercetin 3-O-beta-d-glucose-7-O-beta-d-gentiobioside (QGG) appeared to be the top inhibitor selected by both models after more rigorous docking using Maestro-implemented SP and XP. A 500-ns all-atom MD simulation of the EfNNAT:ligand complex revealed that the compound interacts mainly through hydrogen bonding and water bridges. Validation of the in-silico studies via molecular spectroscopy confirmed QGG's binding to EfNNAT by displacing the fluorescent probes from the protein binding site. Although the binding demonstrated minimal impact on the thermal stability of EfNNAT as deduced from the thermal shift assay, ITC showed that QGG exhibits moderate binding affinity for EfNNAT, with the interaction being spontaneous and thermodynamically favourable. Insights gleaned from this study offer a mechanistic basis that could be leveraged to develop new leads. Expansion of the compound library holds promise for identifying inhibitors with enhanced affinity for EfNNAT.