Tunnels are structural conduits in biomolecules responsible for transporting chemical compounds and solvent molecules to and from the active site. Tunnels have been shown to be present in a wide variety of enzymes across all their functional and structural classes. However, the study of such pathways is experimentally challenging, as they are typically transient. Alternatively, computational methods such as molecular dynamics (MD) simulations have been successfully proposed to explore tunnels. Conventional MD (cMD) has been shown to provide structural details to characterize tunnels, but suffers from sampling limitations to capture rare tunnels opening on longer timescales. Therefore, in this study, we explored the potential of Gaussian Accelerated MD (GaMD) simulations to improve exploration of complex tunnel networks in enzymes. Here, we used the haloalkane dehalogenase LinB with its two variants with engineered transport pathways, which is not only well known for its application potential, but in particular has been extensively studied experimentally and computationally from the perspective of its tunnel network and their importance in multi-step catalytic reaction. Our study demonstrates that GaMD efficiently improves tunnel sampling and allows identification of all known tunnels for LinB and its two mutants. Furthermore, the improved sampling provided insight into previously unknown transient side tunnel (ST). The extensive conformational landscape explored by GaMD simulations allowed us to investigate in detail the mechanism of ST opening. We were able to determine variant-specific dynamic properties of ST opening, which were previously inaccessible due to limited sampling of cMD. Our comprehensive analysis supports multiple indicators of the functional relevance of the ST, emphasizing its potential significance beyond structural considerations. In conclusion, our research proves that the GaMD method can be used to overcome the sampling limitations of cMD also for effective study of tunnels in enzymes, providing further means for the identification of rare tunnels in enzymes with potential for drug development, precision medicine, and rational protein engineering.