Developing chemicals that inhibit N-myristoyltransferase (Nmt) is a promising adjuvant therapeutic to improve the efficacy and selectivity of antifungal agents. Reliable prediction of binding-free energy and binding affinity of Nmt inhibitors can provide a guide for rational drug design. In this study, Quantum Polarised Ligand Docking (QPLD) strategy and Prime/Molecular Mechanics Generalized Born Surface Area (Prime/MM-GBSA) calculations were applied to predict the binding mode and free energy for a series of celecoxib analogues as Nmt inhibitors which were also found to have good anti-inflammatory activity. Invitro antifungal assay indicated that these derivatives were also acting as potent antifungal agents. Reliable docking results showed superior performance on both ligand binding pose and docking score accuracy. Then, the Prime/MM–GBSA method based on the docking complex was used to predict the binding-free energy. The combined use of QM/MM docking and Prime/MM-GBSA method gave a good correlation between the predicted binding-free energy and experimentally determined zone of inhibition and Minimum Inhibitory Concentration (MIC) values. The molecular docking combined with Prime/MM-GBSA simulation can not only be used to rapidly and accurately predict the binding-free energy of novel Nmt inhibitors but also provide a novel strategy for lead discovery and optimization targeting Nmt.