Ligand efficiency outperforms pIC₅₀ on both 2D MLR and 3D CoMFA models: A case study on AR antagonists

The concept of ligand efficiency is defined as biological activity in each molecular size and is widely accepted throughout the drug design community. Among different LE indices, surface efficiency index (SEI) was reported to be the best one in support vector machine modeling, much better than the generally and traditionally used end-point pIC₅₀. In this study, 2D multiple linear regression and 3D comparative molecular field analysis methods are employed to investigate the structure-activity relationships of a series of androgen receptor antagonists, using pIC₅₀ and SEI as dependent variables to verify the influence of using different kinds of end-points. The obtained results suggest that SEI outperforms pIC₅₀ on both MLR and CoMFA models with higher stability and predictive ability. After analyzing the characteristics of the two dependent variables SEI and pIC₅₀, we deduce that the superiority of SEI maybe lie in that SEI could reflect the relationship between molecular structures and corresponding bioactivities, in nature, better than pIC₅₀. This study indicates that SEI could be a more rational parameter to be optimized in the drug discovery process than pIC₅₀. We expanded the application of the ligand efficiency SEI to MLR and CoMFA modeling to investigate the relationships between the hydantoin derivatives and AR antagonist activities. The obtained results indicate that the SEI-based models outperform the pIC₅₀-based models with higher stability, robustness, and predictive abilities. We put forward our opinion that SEI can incarnate the relationships between bioactivities and molecular structures better than pIC₅₀, in nature. SEI could be a more rational parameter to be optimized in the drug discovery.