Computational identification of multi-target natural compounds from Sesbania grandiflora as potential therapeutic agents against Klebsiella pneumoniae

Abstract Klebsiella pneumoniae (K. pneumoniae) is a Gram-negative bacterium that causes severe community- and hospital-acquired infections. Its rising multidrug resistance complicates therapy, highlighting the need for novel drugs with broad-spectrum, multi-target potential. Leveraging the traditional use and therapeutic evidence of Sesbania grandiflora, this study performed structure-based computational screening of its phytochemicals against K. pneumoniae targets. Initially, 93 proteins with high annotation scores and resolved X-ray structures were identified. Six key therapeutic targets, including LpxH, fabG, KPC-2, GlmU, chbG, and ompA, were prioritized for their pathogenic role. Molecular docking revealed that 59 of 73 compounds interacted with all six targets with high affinity, while the remaining 14 compounds interacted with five targets. Network pharmacology indicated KPC-2, fabG, and ompA had the highest connectivity (73 compounds), followed by chbG and LpxH (72), and GlmU (61). ‘3′,6-di-O-feruloylsucrose’ had the strongest affinity for ompA, LpxH, and GlmU, while ‘Acarbose hydrate’ ranked top for chbG, fabG, and KPC-2. Out of 47 drug-like compounds, 9 passed ADMET filters. Sonchuionoside A was selected for molecular dynamics simulations, demonstrating stable binding to all targets. This suggests S. grandiflora phytoconstituents as multi-target regulators against K. pneumoniae and highlights Sonchuionoside A as a promising lead for further validation.