This thesis presents a computational study of water and ion dynamics in modified hydrophobic silicon nitride (Si3N4) nanopores, aimed at enhancing protein sequenc- ing technologies. By employing molecular dynamics (MD) simulations, the research investigates the wetting-dewetting behavior within nanopores as an indirect measure of amino acid residue hydrophobicity, focusing on how post-translational modifications (PTMs) of lysine, particularly the acetylation of lysine residues, influence nanopore hydrophobicity and ionic conductance. The study reveals that nanopore radius and hydrophobicity significantly affect water and ion permeation, with smaller nanopores oscillating between open and closed states, while larger ones remain open.  Using umbrella sampling and the Weighted Histogram Analysis Method (WHAM), the potential of mean force (PMF) for potassium (K+), chloride (Cl−), and water within the nanopores was determined, showing distinct PMF profiles based on lysine and acetyl- lysine presence. The modulation of ionic currents as a tool for protein sequencing was explored, demonstrating that different amino acid residues affect ionic currents by par- tially blocking the pore and altering local permeability, thereby enabling differentiation based on size, shape, charge, and hydrophobicity.  The findings suggest that silicon nitride pore hydrophobicity can be tailored for nanopore sequencing, correlating changes in ionic currents with amino acid residue translocation. This research enhances the understanding of interactions within nanopore environments, potentially leading to more precise nanopore-based sequencing methods.