This chapter provides step-by-step instructions on applying a triangular spatial relationship (TSR) algorithm for precise molecular recognition studies, with a focus on kinase–ligand interactions. Given the central role of kinases in cellular processes and that their dysregulation is a hallmark of cancer, the development of kinase inhibitors is a major focus in drug discovery efforts. In particular, understanding the conformational changes involved in kinase signaling and drug binding is essential for elucidating regulatory mechanisms and designing effective therapeutics. Using three-dimensional structures from the Protein Data Bank, we demonstrate the utility of the TSR algorithm in characterizing and quantifying conformational changes in protein–ligand complexes. Our findings include: (i) the identification of a unique substructure specific to adenosine triphosphate (ATP) molecules, distinguishing them from related compounds such as adenosine diphosphate (ADP) and adenylyl imidodiphosphate (ANP); (ii) the discovery of a backbone substructure that differentiates bound from unbound forms of cyclic adenosine monophosphate-dependent kinases (cAMPDKs); and (iii) the observation that glutamate and asparagine residues within molecular recognition interfaces exhibit distinctive spatial geometries. These results support the existence of recognition codes—structural patterns that govern the specificity of interactions between cAMPDKs and their regulators (ATP, ADP, and ANP). The TSR algorithm and its variants are broadly applicable to other protein families, their ligands, and the complexes they form, beyond kinase–ligand interactions, offering a powerful framework for molecular recognition analysis.