3D-QSAR studies of boron-containing dipeptides as proteasome inhibitors with CoMFA and CoMSIA methods

Three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were performed for a series of dipeptide boronate proteasome inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. A training set containing 46 molecules served to establish the models. The optimum CoMFA and CoMSIA models obtained for the training set were all statistically significant with cross-validated coefficients (q2) of 0.676 and 0.630 and conventional coefficients (r2) of 0.989 and 0.956, respectively. The predictive capacities of both models were successfully validated by calculating a test set of 13 molecules that were not included in the training set. The predicted correlation coefficients (r2pred) of CoMFA and CoMSIA are 0.963 and 0.919, respectively. The CoMFA and CoMSIA field contour maps agree well with the structural characteristics of the binding pocket of β5 subunit of 20S proteasome, which suggests that the 3D-QSAR models constructed in this paper can be used to guide the development of novel dipeptide boronate inhibitors of 20S proteasome.

Three-dimensional quantitative structure–activity relationship (3D-QSAR) method, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) studies were applied to a set of boron-containing dipeptides as inhibitors of the proteasome.Figure optionsDownload as PowerPoint slide