Functions of biomolecules can be regulated by allostery, where a molecule binds to a site far from the active site of the structure. Recently, nanobodies are promising for disease treatment and imaging. Exploration of the existence of allostery and new potential sites in nanobodies have not yet been studied in detail, and computational approaches help speed up research on allostery in nanobodies. For this aim, three nanobody-antigen complexes, namely Caplacizumab - von Willebrand factor (vWF), Nanobody 87 - NTCP, and Nanobody 2-67 - SARS-CoV-2 Spike, were computationally examined using Essential Site Scanning Analysis (ESSA) method to predict potential binding sites. The default cutoff distance value of ESSA (10 Å) is replaced with a lower (7.3 Å) and a higher (13 Å) cutoff value where the total number of modes is also increased to 20 in the new ESSA. The old and new ESSA are applied to all structures, and the results are compared to each other to better understand the effect of new parameters on the success of ESSA. It is observed that ESSA is improved with the new parameters, and more successful results are obtained when the cutoff value is 7.3 Å, especially in finding essential residues in complementarity-determining regions (CDRs) for the nanobodies studied. The improved ESSA also revealed some other binding sites in the antigens studied where they interact with other proteins and ligands. The improved method in this thesis might help develop antigen-specific new-generation therapeutics and better diagnostic tools.