Antimicrobial nanocoatings represent a pivotal advancement in reducing the spread of infectious diseases. Understanding their interactions with pathogens is essential to enhance their efficacy and design. This research extends the model proposed by G. Lazzini et al., which was designed to simulate these interactions, grounded in the work of I. Jančigová et al. on modelling red blood cells with a molecular dynamics-based approach. The enhanced and customised model employs a discrete element, elastic triangular mesh to simulate the pathogen within a particle-based Lattice-Boltzmann fluid. The mesh's elastic characteristics and the model's parameters are fine-tuned to reflect the mechanical properties of the pathogen under study. The nanocoated substrate is also represented by a triangular mesh, with the pathogen-substrate interaction characterised by a Lennard-Jones potential between the particles/nodes constituting each of them. The simulations performed focus on the pathogen's deposition on the nanocoated substrate, assessing the stress endured by the pathogen and the pathogen-substrate contact area. This methodology is applied to a Staphylococcus Aureus bacterium and a SARS-CoV-2 virion, considering the deposition of both on diverse surface geometries. The research extends the results obtained for Staphylococcus Aureus in a preceding article and presents the first results for the virus. In both cases, the influence of surface topography is studied by modifying substrate roughness and dispersion through scaling in the z-direction and (x,y)-plane. Results from these simulations reveal a direct correlation between the mechanical stress experienced by the pathogen upon deposition and the substrate's geometry. Notable correlations between stress and contact area are observed across a spectrum of roughness and dispersion parameters, offering insights into the design of more effective antimicrobial nanocoatings. These findings remark on the critical role of substrate topography in the pathogen-nanocoating interaction’s dynamic. MIRIA project is funded by the European Union under Grant Agreement Nº 101058751.