This study explores the use of chemometric techniques to analyze opioids with varying degrees of inhibitory activity, aiming to support chemistry education while identifying potential analgesic compounds. The crystallographic structure of mitragynine was retrieved from the literature and fully optimized using multiple computational methods and basis sets. Through Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA), the B3LYP/6-31G** method was identified as the most suitable for further computational investigation.

The optimized structure of mitragynine served as the basis for constructing 3D models of nine additional opioids. These compounds underwent full geometric optimizations and molecular property calculations at their lowest energy conformations. The molecular descriptors derived were subjected to Exploratory Data Analysis using PCA and HCA, effectively grouping the ten opioids (training set) into two categories: the most active opioids (MAO – compounds 1, 2, 5, 6, 9, and 10) and the least active opioids (LAO – compounds 3, 4, 7, and 8).

To validate these groupings, classification methods including the K-Nearest Neighbor (KNN) method and Stepwise Discriminant Analysis (SDA) were applied, confirming the distinct separation of the MAO and LAO classes. Based on these findings and chemical reasoning, nine new mitragynine-derived opioids were proposed. Evaluation through the established chemometric models indicated that six of these novel compounds hold significant analgesic potential, making them candidates for synthesis and biological testing.