A criteria to classify biological activity of benzimidazoles from a model of structural similarity

We have classified a set of 250 benzimidazoles using a criterion of structu ral similarity. This criterion has led us to several clusters, which keep a close relationship between the molecules belonging to each one of them and their pharmacological activity. To study the structural similarity we have built a mathematical space where chemical structures are pictured as vecto rs. A set of well-chosen descriptors was used as variables. These descripto rs arise from graph theoretical studies and quantum mechanical calculations . Principal components analysis was employed to find the suitable dimension for the space. Finally, cluster analysis was performed to classify the set of molecules by similarity. A Euclidean metric was used as a similarity co efficient.