A constant pH molecular dynamics and experimental study on the effect of different pH on the structure of urease from...

Urease is pivotal in microbial-induced calcium carbonate precipitation (MICP), where its catalytic efficiency directly governs calcium carbonate formation. However, practical MICP applications in extreme environments (e.g., acidic mine drainage, industrial waste sites) are hindered by limited understanding of urease behavior under extreme pH conditions. This study combines laboratory experiments and constant pH molecular dynamics (CpHMD) simulations to investigate how pH variations (3-11) affect the structural stability of Sporosarcina pasteurii urease, focusing on its α-subunit (PDB: 4CEU). Experimental validation identified pH 7-8 as optimal for urease activity, aligning with molecular dynamics results showing minimal structural deviations (RMSD) and stable protonation states under neutral to mildly alkaline conditions. Extreme pH (3, 4, 11) disrupted active-site geometry and induced charge fluctuations, impairing catalytic function. CpHMD simulations revealed that the α-subunit retains structural integrity at pH 7-8, suggesting potential reassembly post-environmental stress. This work bridges gaps in enzymatic stability under harsh conditions, offering insights for optimizing MICP in geotechnical and environmental remediation applications.

The study combined experimental and computational approaches. Sporosarcina pasteurii urease activity was experimentally assessed across pH 3-11 by monitoring urea hydrolysis-induced conductivity changes. Computational analyses employed GROMACS constant pH with the CHARMM36 force field to perform pH-dependent molecular dynamics simulations. The urease structure was solvated, neutralized, energy-minimized, and subjected to constant pH simulations. Structural stability, active site dynamics, and protonation states of titratable residues were analyzed via RMSD, hydrogen bonds, solvent-accessible surface area (SASA), and Epock 1.0.5. Free energy landscapes and residue interactions were evaluated using principal component analysis (PCA) and λ-dynamics. Experimental data were processed with OriginPro 2024b and Python, linking pH-induced conformational shifts to enzymatic function.