Hologram quantitative structure activity relationship studies on 5-HT 6 antagonists

Abstract

Predictive hologram quantitative structure activity relationship (HQSAR) models were developed for a series of arylsulfonamide compounds acting as specific 5-HT 6 antagonists. A training set containing 48 compounds served to establish the model. The best HQSAR model was generated using atoms, bond, and connectivity as fragment distinction and 4–7 as fragment size showing cross-validated r 2( q 2) value of 0.702 and conventional r 2 value of 0.971. The predictive ability of the model was validated by an external test set of 20 compounds giving satisfactory predictive r 2 value of 0.678. The efficiency of HQSAR approach was further evidenced by the generation of predictive models for a training set containing 30 highly diverse, both specific and nonspecific 5-HT 6 antagonists. The best HQSAR model for this training set was generated using atoms, bond, and connectivity as fragment distinction and 4–7 as fragment size showing cross-validated r 2( q 2) value of 0.693 and conventional r 2 value of 0.923. This model was also validated by using an external test set of 10 compounds giving satisfactory predictive r 2 value of 0.692. The contribution maps obtained from these models were used to explain the individual atomic contributions to the overall activity.