Molecular basis for diaryldiamine selectivity and competition with tRNA in a type 2 methionyl-tRNA synthetase from a Gram-negative bacterium

Biochemical and structural characterization of chlorhexidine as an ATP-assisted inhibitor against type 1 methionyl-tRNA synthetase from Gram-positive bacteria

Methionyl-tRNA synthetase (MetRS) catalyzes the attachment of l-methionine (l-Met) to tRNAMet to generate methionyl-tRNAMet, an essential substrate for protein translation within ribosome. Owing to its indispensable biological function and the structural discrepancies with human counterpart, bacterial MetRS is considered an ideal target for developing antibacterials. Herein, chlorhexidine (CHX) was identified as a potent binder of Staphylococcus aureus MetRS (SaMetRS) through an ATP-aided affinity screening. The co-crystal structure showed that CHX simultaneously occupies the enlarged l-Met pocket (EMP) and the auxiliary pocket (AP) of SaMetRS with its two chlorophenyl groups, while its central hexyl linker swings upwards to interact with some conserved hydrophobic residues. ATP adopts alternative conformations in the active site cavity, and forms ionic bonds and water-mediated hydrogen bonds with CHX. Consistent with this synergistic binding mode, ATP concentration-dependently enhanced the binding affinity of CHX to SaMetRS from 10.2 μM (no ATP) to 0.45 μM (1 mM ATP). While it selectively inhibited two representative type 1 MetRSs from S. aureus and Enterococcus faecalis, CHX did not show significant interactions with three tested type 2 MetRSs, including human cytoplasmic MetRS, in the enzyme inhibition and biophysical binding assays, probably due to the conformational differences between two types of MetRSs at their EMP and AP. Our findings on CHX may inspire the design of MetRS-directed antimicrobials in future.

Computational Insight into Substrate-Induced Conformational Changes in Methionyl-tRNA Synthetase of Mycobacterium Tuberculosis

Tuberculosis caused by Mycobacterium tuberculosis (M.tb) has killed millions worldwide. Antibiotic resistance leads to the ineffectiveness of the current therapies. Aminoacyl tRNA synthetase (aaRS) class of proteins involved in protein synthesis are promising bacterial targets for developing new therapies. Here, we carried out a systematic comparative study on the aaRS sequences from M.tb and human. We listed important M.tb aaRS that could be explored as potential M.tb targets alongside the detailed conformational space analysis of methionyl-tRNA synthetase (MetRS) in apo- and substrate-bound form, which is among the proposed targets. Understanding the conformational dynamics is central to the mechanistic understanding of MetRS, as the substrate binding leads to the conformational changes causing the reaction to proceed. We performed the most complete simulation study of M.tb MetRS for 6 microseconds (2 systems × 3 runs × 1 microsecond) in the apo and substrate-bound states. Interestingly, we observed differential features, showing comparatively large dynamics for the holo simulations, whereas the apo structures became slightly compact with reduced solvent exposed area. In contrast, the ligand size decreased significantly in holo structures possibly to relax ligand conformation. Our findings correlate with experimental studies, thus validating our protocol. Adenosine monophosphate moiety of the substrate exhibited quite higher fluctuations than the methionine. His21 and Lys54 were found to be the important residues forming prominent hydrogen bond and salt-bridge interactions with the ligand. The ligand-protein affinity decreased during simulations as computed by MMGBSA analysis over the last 500 ns trajectories, which indicates the conformational changes upon ligand binding. These differential features could be further explored for designing new M.tb inhibitors.

Aminoacyl-tRNA synthetase (AARS) as an attractive drug target in neglected tropical trypanosomatid diseases-Leishmaniasis, Human African Trypanosomiasis and Chagas disease

TriTryp diseases (Leishmaniasis, Human African Trypanosomiasis (HAT), and Chagas disease) are devastating parasitic neglected tropical diseases (NTDs) that affect billions of people in developing countries, cause high mortality in humans, and impose a large socio-economic burden. The current treatment options against tritryp diseases are suboptimal and challenging due to the emergence of resistance against available tritryp drugs. Hence, designing and developing effective anti-tritryp drugs with novel targets are required. Aminoacyl-tRNA synthetases (AARSs) involved in specific aminoacylation of transfer RNAs (tRNAs), interrupt protein synthesis through inhibitors, and retard the parasite growth. AaRSs have long been studied as therapeutic targets in bacteria, and three aaRS inhibitors, mupirocin (against IleRS), tavaborole AN2690 (against LeuRS), and halofuginone (against ProRS), are already in clinical practice. The structural differences between tritryp and human aaRSs and the presence of unique sequences (N-terminal domain/C-terminal domain/catalytic domain) make them potential target for developing selective inhibitors. Drugs based on a single aaRS target developed by high-throughput screening (HTS) are less effective due to the emergence of resistance. However, designing multi-targeted drugs may be a better strategy for resistance development. In this perspective, we discuss the characteristics of tritryp aaRSs, sequence conservation in their orthologs and their peculiarities, recent advancements towards the single-target and multi-target aaRS inhibitors developed through rational design.

Fragment screening and structural analyses highlight the ATP-assisted ligand binding for inhibitor discovery against type 1 methionyl-tRNA synthetase

Methionyl-tRNA synthetase (MetRS) charges tRNAMet with l-methionine (L-Met) to decode the ATG codon for protein translation, making it indispensable for all cellular lives. Many gram-positive bacteria use a type 1 MetRS (MetRS1), which is considered a promising antimicrobial drug target due to its low sequence identity with human cytosolic MetRS (HcMetRS, which belongs to MetRS2). Here, we report crystal structures of a representative MetRS1 from Staphylococcus aureus (SaMetRS) in its apo and substrate-binding forms. The connecting peptide (CP) domain of SaMetRS differs from HcMetRS in structural organization and dynamic movement. We screened 1049 chemical fragments against SaMetRS preincubated with or without substrate ATP, and ten hits were identified. Four cocrystal structures revealed that the fragments bound to either the L-Met binding site or an auxiliary pocket near the tRNA CCA end binding site of SaMetRS. Interestingly, fragment binding was enhanced by ATP in most cases, suggesting a potential ATP-assisted ligand binding mechanism in MetRS1. Moreover, co-binding with ATP was also observed in our cocrystal structure of SaMetRS with a class of newly reported inhibitors that simultaneously occupied the auxiliary pocket, tRNA site and L-Met site. Our findings will inspire the development of new MetRS1 inhibitors for fighting microbial infections.

A Systematic Strategy to Find Potential Therapeutic Targets for Pseudomonas aeruginosa Using Integrated Computational Models

Pseudomonas aeruginosa is an opportunistic human pathogen that has been a constant global health problem due to its ability to cause infection at different body sites and its resistance to a broad spectrum of clinically available antibiotics. The World Health Organization classified multidrug-resistant Pseudomonas aeruginosa among the top-ranked organisms that require urgent research and development of effective therapeutic options. Several approaches have been taken to achieve these goals, but they all depend on discovering potential drug targets. The large amount of data obtained from sequencing technologies has been used to create computational models of organisms, which provide a powerful tool for better understanding their biological behavior. In the present work, we applied a method to integrate transcriptome data with genome-scale metabolic networks of Pseudomonas aeruginosa. We submitted both metabolic and integrated models to dynamic simulations and compared their performance with published in vitro growth curves. In addition, we used these models to identify potential therapeutic targets and compared the results to analyze the assumption that computational models enriched with biological measurements can provide more selective and (or) specific predictions. Our results demonstrate that dynamic simulations from integrated models result in more accurate growth curves and flux distribution more coherent with biological observations. Moreover, identifying drug targets from integrated models is more selective as the predicted genes were a subset of those found in the metabolic models. Our analysis resulted in the identification of 26 non-host homologous targets. Among them, we highlighted five top-ranked genes based on lesser conservation with the human microbiome. Overall, some of the genes identified in this work have already been proposed by different approaches and (or) are already investigated as targets to antimicrobial compounds, reinforcing the benefit of using integrated models as a starting point to selecting biologically relevant therapeutic targets.