ABSTRACT Glutaminases are a unique group of hydrolytic enzymes with potential applications in cancer therapy and the food industry. This study focused on the biological characterisation and computational conformation dynamics of YLaM, a potential L-glutaminase from a halothermotolerant Bacillus licheniformis. The research integrated experimental and computational methods to identify the YLaM sequence and predict its structural and functional properties. YLaM was amplified using a polymerase chain reaction, cloned into a pET-22b(+) vector, sequenced, and submitted to BankIt/NCBI. This experimental work was complemented by in silico analysis, including structural modelling via the I-TASSER web server, molecular docking using AutoDockTools 1.5.6, and molecular dynamic (MD) simulations using GROMACS v5.1.4. The study resulted in the development of a high-quality 3D model of YLaM through homology modelling and structural refinement, enabling a detailed exploration of its binding affinity with L-glutamine (L-Gln). By identifying active site residues using the homotetramer structure of human glutaminase, crucial interactions with L-Gln were validated, confirming its catalytic function. Finally, MD simulations confirmed the stability of the complex under physiological conditions. This combined molecular identification and functional simulations provide comprehensive insights into the physicochemical properties of the enzyme, offering valuable information for subsequent assessments, including recombinant production and biological impact evaluations.