Exploring species-specific inhibitors with multiple target sites on S. aureus pyruvate kinase using a computational workflow

Abstract

Experimental evidence indicated that bacterial pyruvate kinase of glycolysis can be evaluated as an alternative target to eliminate infections, while antibiotic resistance poses a global threat. Here, we use a computational workflow to reveal and investigate the potential allosteric sites of methicillin-resistant S. aureus PK, which can help in designing species-specific drugs to inhibit activity of this organism. Residue interaction networks point to a known allosteric site at the small C-C interface, a potential allosteric site near the small interface (site #1), and a second potential allosteric site at the large interface (site #2). 2 µs-long molecular dynamics (MD) simulations with AMBER16 generate different conformations of one narrow target site. Known and potential allosteric sites on the selected conformers are investigated using ensemble docking with AutoDock Vina and a library of 2447 FDA-approved drugs. We determine 18 hits, comprising ergot-alkaloids, anti-cancer-agents, antivirals, analgesics, cardiac glycosides, all with a high docking z-score for three sites. 5 selected compounds with high, average and low z-scores are subjected to 50 ns-long MD simulations for MM-GBSA calculations. ΔG_bind values up to −49.3 kcal/mol at the C-C interface, up to −32.7 kcal/mol at site #1, and up to −53.3 kcal/mol at site #2 support the docking calculations. We investigate mitapivat and TT-232 as reference compounds under clinical trial, targeting human PK isomers. We suggest 18 FDA-approved hits from the docking calculations and TT-232 as potential inhibitors with multiple target sites on S. aureus PK. This study also proposes pharmacophores models for de novo drug design.

Communicated by Ramaswamy H. Sarma

Keywords:

• Residue interaction networks
• molecular dynamics simulations
• allostery
• drug repurposing
• glycolytic pathway

Acknowledgements

The authors thank Erdem Cicek for his support for the MD simulations. Computing resources used in this work were provided by the National Center for High Performance Computing of Turkey (UHeM) under grant number 1009292021.

Data and software availability

The in-house Fortran and MATLAB scripts (with the academic license of Istanbul Technical University) to calculate residue betweenness scores for the residue interaction networks are available upon request. The open acess Autodock Vina docking package is used for the molecular docking calculations. Molecular dynamics simulations and binding free energy calculations are done using AMBER v.16 with the academic license of Istanbul Technical University. Molecular graphics are generated with freeware PyMol (DeLano Scientific LLC, 2002). 2 D ligand – protein interaction graphics are generated using freeware Accelrys Discovery Studio Visualizer. Data used in the analysis are given in the Supporting Information.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work is supported by the Scientific and Technological Research Council of Turkey (TÜBİTAK) Project No. 218M320. BA thanks to the 2020-TÜBİTAK STAR Scholarship.