The elastic network interpolation (ENI)¹ is a computationally efficient and physically realistic method to generate conformational transition intermediates between two forms of a given protein. However it can be asked whether these calculated conformations provide good representatives for these intermediates. In this study, we use ENI to generate conformational transition intermediates between the open form and the closed forms of adenylate kinase (AK). Based on C^α-only intermediates, we construct atomic intermediates by grafting all the atoms of known AK structures onto the C^α atoms and then perform CHARMM energy minimization to remove steric conflicts and optimize these intermediate structures. We compare the energy profiles for all intermediates from both the CHARMM force-field and from knowledge-based energy functions. We find that the CHARMM energies can successfully capture the two energy minima representing the open AK and closed AK forms, while the energies computed from the knowledge-based energy functions can detect the local energy minimum representing the closed AK form and show some general features of the transition pathway with a somewhat similar energy profile as the CHARMM energies. The combinatorial extension (CE) structural alignment² and the k-means clustering algorithm are then used to show that known PDB structures closely resemble computed intermediates along the transition pathway.