Structure-based virtual screening for assessing the efficacy of NLRP3 small molecule compounds on sepsis

Abstract Background Because no clinically approved NLRP3 inhibitors are currently available, the identification of novel small-molecule candidates with optimal pharmacological and safety profiles is urgently needed. In this study, we rationally selected and systematically evaluated clinically relevant small-molecule NLRP3 inhibitors for the potential treatment of sepsis using an integrated computational and experimental strategy. Methods A semi-empirical (PM6)–optimized structure-based virtual screening of 34 clinically relevant NLRP3 inhibitors was conducted via molecular docking, followed by 50 docking runs with 20 generated poses for each ligand to ensure conformational reliability. The top-ranked compounds were subjected to the prediction of ADME/T properties, assessment of cytotoxicity, qPCR, and mechanistic correlation through density functional theory (DFT), potential energy surface (PES) analysis, and molecular dynamics (MD) simulations. Results : Among the tested inhibitors, ZYIL1 exhibited the strongest binding affinity (–7.23 kcal/mol) and superior pharmacokinetic stability, with moderate plasma protein binding and low predicted hepatotoxicity. ZYIL1 demonstrated potent suppression of inflammatory cytokines (IL-1β, IL-6, TNF-α, and NLRP3) comparable to MCC950 in vitro . DFT and MD analyses revealed that ZYIL1 has greater polarizability, lower HOMO–LUMO energy gap, and higher binding free energy (–49.46 kcal/mol) than MCC950, indicating superior electronic stability and binding dynamics. Conclusion This integrated multilevel approach identified ZYIL1 as a highly promising NLRP3 inhibitor with balanced pharmacological properties and strong molecular stability. The integrated multilevel screening strategy provides a robust framework for accelerating the development of targeted therapy for sepsis, requiring further biological and clinical validation.