A Covalent Approach Against Antibiotic Resistance




01. January 2021 - 31. December 2023


0,53 FTE


Stanislav Gobec


1-09 Natural sciences and Mathematics - Pharmacy


The increased frequency of resistance among human bacterial pathogens represents a serious public threat in the treatment of infectious diseases. The United Nations, the World Health Organisation and the European Commission, have recently declared antimicrobial resistance (AMR) as a serious global threat to public health that has a tremendous impact on healthcare expenses and productivity. AMR may result in an estimate of > 300 million premature deaths and cost the global economy up to €100 trillion by 2050. Therefore, there is an urgent need for novel antibacterial agents with alternative or completely new mechanisms of action that call for novel approaches and research platforms in antibacterial drug discovery. 
In the present project, the development of inhibitors against three well-established antibacterial targets is planned. UDP-N-acetylglucosamine enolpyruvyl transferase (MurA) catalyses the first committed step in the biosynthesis of peptidoglycan, an essential component of the bacterial cell wall in both Gram-positive and Gram-negative bacteria. The final step of peptidoglycan biosynthesis, transpeptidation, is catalysed by the transpeptidase domain of the penicillin-binding proteins (PBPs). The Mycobacterium tuberculosis (Mtb) proteasome is a protease complex that performs proteolysis and thereby plays a pivotal role in protein turnover and homeostasis. The inactivation of Mtb proteasome has been associated with some detrimental consequences for bacterial virulence such as impaired survival in the mammalian host and sensitivity to nitrosative stress. All three enzymes are well validated targets for antimicrobial drug discovery and are amenable to covalent inhibitor development, as demonstrated by clinically used fosfomycin, beta-lactams and bortezomib, which are covalent inhibitors of MurA, PBPs and Mtb proteasome, respectively. In addition, these three enzymes represent excellent model enzymes to study new mechanisms of covalent inhibition as they contain three different nucleophiles in their active sites: cysteine (MurA), serine (PBPs) and threonine (Mtb proteasome). Our groups have experience in identifying and characterizing protein ligands including inhibitors against these targets and have already produced joint results.
The mechanism of covalent inhibition typically includes two steps. First a non-covalent complex between the inhibitor and the protein is formed. In the next step, the reactive group of the inhibitor chemically binds to a protein residue. Efficient modelling of covalent inhibition requires the proper computational description of both steps. The first step agrees with the conventional ligand-protein complex formation and recent progress in the computation of binding free-energies of compound series makes it possible to model the non-covalent complex formation. The second step, namely the covalent bond formation, has to be treated by quantum chemical (QM) methods. QM calculations have proved their ability to contribute to the understanding of organic reaction mechanisms involving catalysis. They have been also applied to calculate reactivity of covalent ligands, typically for Michael-addition reactions against thiols within series of limited diversity.
In the present proposal we plan to develop covalent inhibitors against bacterial targets with the combined application of computational design, modelling of covalent bond formation between enzyme and inhibitor, medicinal chemistry and biochemical activity profiling. Our objective is to identify compounds that are suitable starting points for developing inhibitors with therapeutic potential. In addition, our computational design applying a combination of state of the art methods to interpret and predict the activity of covalent inhibitors is expected to produce improved and more complete computational tools for supporting covalent drug discovery.



Phase 1: hit identification using computational methods

Bibliographical references, arising directly from the implementation of the project:

There is no record of the composition of the project group and bibliographic references in the SI CRIS database (17.3.2021)

Financed by: