Non-β Lactam Inhibitors of the Serine β-Lactamase blaCTX-M15 in Drug-Resistant Salmonella typhi

Abstract

Antibiotic resistance by bacterial pathogens against widely used β-lactam drugs is a major concern to public health worldwide, resulting in high healthcare cost. The present study aimed to extend previous research by investigating the potential activity of reported compounds against the S. typhi β-lactamase protein. 74 compounds from computational screening reported in our previous study against β-lactamase CMY-10 were subjected to docking studies against blaCTX-M15. Site-Identification by Ligand Competitive Saturation (SILCS)-Monte Carlo (SILCS-MC) was applied to the top two ligands selected from molecular docking studies to predict and refine their conformations for binding conformations against blaCTX-M15. The SILCS-MC method predicted affinities of −8.6 and −10.7 kcal/mol for Top1 and Top2, respectively, indicating low micromolar binding to the blaCTX-M15 active site. MD simulations initiated from SILCS-MC docked orientations were carried out to better characterize the dynamics and stability of the complexes. Important interactions anchoring the ligand within the active site include pi−pi stacked, amide−pi, and pi−alkyl interactions. Simulations of the Top2− blaCTX-M15 complex exhibited stability associated with a wide range of hydrogen-bond and aromatic interactions between the protein and the ligand. Experimental β-lactamase (BL) activity assays showed that Top1 has 0.1 u/mg BL activity, and Top2 has a BL activity of 0.038 u/mg with a minimum inhibitory concentration of 1 mg/mL. The inhibitors proposed in this study are non-βlactam-based β-lactamase inhibitors that exhibit the potential to be used in combination with β-lactam antibiotics against multidrugresistant clinical isolates. Thus, Top1 and Top2 represent lead compounds that increase the efficacy of β-lactam antibiotics with a low dose concentration.

Enhancing SILCS-MC via GPU Acceleration and Ligand Conformational Optimization with Genetic and Parallel Tempering Algorithms

“…Beyond the implementation and testing of additional algorithms in the present study the capabilities and efficiency of SILCS-MC has been improved through GPU acceleration. This development has increased the computational speed to surpass previous CPU-based implementations of SILCS-MC by 2 orders of magnitude. , Consequently, GPU-optimized SILCS-MC facilitates the processing of larger molecules and the increasingly large virtual libraries without compromising on the precision necessary for effective CADD efforts. ,,,,− ,− …”

“…SILCS-MC has been successfully applied in a number of studies and is computationally efficient, − ,− requiring minutes on a single CPU core for full docking of a ligand . However, the algorithm requires multiple SILCS-MC runs to obtain adequate convergence defined as 0.5 kcal/mol in the context of the LGFE.…”