Search for inhibitors of AminoAcyl-tRNA synthases by virtual click chemistry

Essentiality Assessment of Cysteinyl and Lysyl-tRNA Synthetases of Mycobacterium smegmatis

Discovery of mupirocin, an antibiotic that targets isoleucyl-tRNA synthetase, established aminoacyl-tRNA synthetase as an attractive target for the discovery of novel antibacterial agents. Despite a high degree of similarity between the bacterial and human aminoacyl-tRNA synthetases, the selectivity observed with mupirocin triggered the possibility of targeting other aminoacyl-tRNA synthetases as potential drug targets. These enzymes catalyse the condensation of a specific amino acid to its cognate tRNA in an energy-dependent reaction. Therefore, each organism is expected to encode at least twenty aminoacyl-tRNA synthetases, one for each amino acid. However, a bioinformatics search for genes encoding aminoacyl-tRNA synthetases from Mycobacterium smegmatis returned multiple genes for glutamyl (GluRS), cysteinyl (CysRS), prolyl (ProRS) and lysyl (LysRS) tRNA synthetases. The pathogenic mycobacteria, namely, Mycobacterium tuberculosis and Mycobacterium leprae, were also found to possess two genes each for CysRS and LysRS. A similar search indicated the presence of additional genes for LysRS in gram negative bacteria as well. Herein, we describe sequence and structural analysis of the additional aminoacyl-tRNA synthetase genes found in M. smegmatis. Characterization of conditional expression strains of Cysteinyl and Lysyl-tRNA synthetases generated in M. smegmatis revealed that the canonical aminoacyl-tRNA synthetase are essential, while the additional ones are not essential for the growth of M. smegmatis.

Aminoacyl-tRNA synthetase inhibitors as potential antibiotics

Increasing resistance to antibiotics is a major problem worldwide and provides the stimulus for development of new bacterial inhibitors with preferably different modes of action. In search for new leads, several new bacterial targets are being exploited beside the use of traditional screening methods. Hereto, inhibition of bacterial protein synthesis is a long-standing validated target. Aminoacyl-tRNA synthetases (aaRSs) play an indispensable role in protein synthesis and their structures proved quite conserved in prokaryotes and eukaryotes. However, some divergence has occurred allowing the development of selective aaRS inhibitors. Following an outline on the action mechanism of aaRSs, an overview will be given of already existing aaRS inhibitors, which are largely based on mimics of the aminoacyl-adenylates, the natural reaction intermediates. This is followed by a discussion on more recent developments in the field and the bioavailability problem.

Computational approaches for protein function prediction: a combined strategy from multiple sequence alignment to molecular docking-based virtual screening

The functional characterization of proteins represents a daily challenge for biochemical, medical and computational sciences. Although finally proved on the bench, the function of a protein can be successfully predicted by computational approaches that drive the further experimental assays. Current methods for comparative modeling allow the construction of accurate 3D models for proteins of unknown structure, provided that a crystal structure of a homologous protein is available. Binding regions can be proposed by using binding site predictors, data inferred from homologous crystal structures, and data provided from a careful interpretation of the multiple sequence alignment of the investigated protein and its homologs. Once the location of a binding site has been proposed, chemical ligands that have a high likelihood of binding can be identified by using ligand docking and structure-based virtual screening of chemical libraries. Most docking algorithms allow building a list sorted by energy of the lowest energy docking configuration for each ligand of the library. In this review the state-of-the-art of computational approaches in 3D protein comparative modeling and in the study of protein-ligand interactions is provided. Furthermore a possible combined/concerted multistep strategy for protein function prediction, based on multiple sequence alignment, comparative modeling, binding region prediction, and structure-based virtual screening of chemical libraries, is described by using suitable examples. As practical examples, Abl-kinase molecular modeling studies, HPV-E6 protein multiple sequence alignment analysis, and some other model docking-based characterization reports are briefly described to highlight the importance of computational approaches in protein function prediction.