While nowadays approaches for equilibrium free energy estimation are well established, nonequilibrium simulations represent both an appealing computational opportunity and a challenge. This kind of simulations allows for a trivially parallel scheme, but at the same time the significant amount of irreversible work often generated during the steering process (either alchemical or physical) can hinder the convergence of free energy estimators. Here, we discuss in depth this issue for the protein-ligand binding free energy estimation carried out via physical paths. We found that the water model and the parametrization of the path collective variables have a remarkable impact on the convergence rate of the estimators (e.g., Crooks). Finally, we provide practical recipes to enhance the convergence speed and minimize dissipation.