Computational identification and multi-level validation of marine fungal metabolites as potent inhibitors of Acinetobacter baumannii GuaB.

Abstract

Acinetobacter baumannii is a multidrug-resistant pathogen that causes serious nosocomial infections with limited therapeutic options. GuaB (Inosine Monophosphate Dehydrogenase, IMPDH) is an important target in purine biosynthesis that has been identified as a promising target in anti-A. baumannii drug research. The dCBS regulatory domain of GuaB has been purposefully chosen for this research due to its role in allosteric regulation and structural dissimilarity with its human homologue. The integrated computational framework has been utilized to identify new GuaB inhibitors among marine fungal metabolites. The virtual screening of GuaB-dCBS with AutoDock Vina identified three lead compounds: CMNPD27312, CMNPD12442, and CMNPD28769. Density functional theory calculations were carried out to refine the structures of the ligands before redocking with GuaB-dCBS to evaluate their electronic compatibility with GuaB. The calculations showed good electronic compatibility with GuaB-dCBS compared to the positive control compound A1AUF. Long timescale molecular dynamics simulations of 500 ns were carried out to evaluate the stability of the ligand-GuaB-dCBS complexes. The structural stability of all ligand-GuaB-dCBS complexes has been shown in this research. The RMSD, RMSF, and hydrogen bond analysis showed that CMNPD27312 and CMNPD28769 have enhanced stability. The binding free energy calculations showed good ligand binding to GuaB-dCBS. The principal component analysis showed ligand-induced stability of GuaB-dCBS. The free energy landscape calculations showed ligand-induced stability of GuaB-dCBS. The QM/MM calculations showed good electronic compatibility of the ligands with GuaB-dCBS. The bioactivity prediction showed that CMNPD27312 and CMNPD28769 have high inhibitory potential (predicted pIC50 ≥ 7.2).