Cheminformatics-driven discovery of selective, nanomolar inhibitors for staphylococcal pyruvate kinase.

Research paper by Peter P Axerio-Cilies, Raymond H RH See, Roya R Zoraghi, Liam L Worral, Tian T Lian, Nikolay N Stoynov, Jihong J Jiang, Sukhbir S Kaur, Linda L Jackson, Huansheng H Gong, Rick R Swayze, Emily E Amandoron, Nag S NS Kumar, Anne A Moreau, Michael M Hsing, et al.

Indexed on: 10 Nov '11Published on: 10 Nov '11Published in: ACS Chemical Biology


We have recently mapped the protein interaction network of methicillin-resistant Staphylococcus aureus (MRSA), which revealed its scale-free organization with characteristic presence of highly connected hub proteins that are critical for bacterial survival. Here we report the discovery of inhibitors that are highly potent against one such hub target, staphylococcal pyruvate kinase (PK). Importantly, the developed compounds demonstrate complete selectivity for the bacterial enzyme compared to all human orthologues. The lead 91nM inhibitor IS-130 has been identified through ligand-based cheminformatic exploration of a chemical space around micromolar hits initially generated by experimental screening. The following crystallographic study resulted in identification of a tetrameric MRSA PK structure where IS-130 is bound to the interface between the protein's subunits. This newly described binding pocket is not present in otherwise highly similar human orthologues and can be effectively utilized for selective inhibition of bacterial PK. The following synthetic modifications of IS-130, guided by structure-based molecular modeling, resulted in the development of MRSA PK inhibitors with much improved antimicrobial properties. Considering a notable lack of recent reports on novel antibacterial targets and cognate antibacterial compounds, this study provides a valuable perspective on the development of a new generation of antimicrobials. Equally noteworthy, the results of the current work highlight the importance of rigorous cheminformatics-based exploration of the results of high-throughput experiments.

More like this: