Computational exploration of novel antimicrobial modalities targeting fucose-binding lectins and ribosomes in Mycobacterium smegmatis using tRNA-encoded peptides

tRNA-Encoded Peptides (tREPs), encoded by small open reading frames (smORFs) within tRNA genes, have recently emerged as a new class of functional peptides exhibiting antiparasitic activity. The discovery of tREPs has led to a re-evaluation of the role of tRNAs in biology and has expanded our understanding of the genetic code. This presents an immense, unexplored potential in the realm of tRNA-peptide interactions, paving the way for groundbreaking discoveries and innovative applications in various biological functions. This study explores the antimicrobial potential of tREPs against protein targets by employing a computational method that uses verified data sources and highly recognized predictive algorithms to provide a sorted list of likely antimicrobial peptides, which were then filtered for toxicity, cell permeability, allergenicity and half-life. These peptides were then docked with screened protein targets and computationally validated using molecular dynamics (MD) simulations for 150 ns and the binding free energy was estimated. The peptides Pep2 (VVLWRKPRVRKTG) and Pep6 (HRLRLRRRKPWW) exhibited good binding affinities of -110.5 +/- 2.5 and -129.0 +/- 3.9, respectively, with RMSD values of 0.4 and 0.25 nm against the fucose-binding lectin (7NEF) and the 30S ribosome of Mycobacterium smegmatis (5O5J) protein targets. The 7NEF-Pep2 and 5O5J-Pep6 complexes indicated higher negative binding free energies of -52.55 kcal/mol and -55.52 kcal/mol respectively, as calculated by Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA). Thus, the tREPs derived peptides designed as a part of this study, provide novel approaches for potential anti-bacterial therapeutic modalities.