title: Ligand Efficiency Outperforms pIC50 on Both 2D MLR and 3D CoMFA Models: A Case Study on AR Antagonists.
abstract: 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.
authors.affiliation: School of Pharmacy, Lanzhou University, 199 West Donggang Road, 730000, Lanzhou, China.|The Separating Scientific Institute of Lanzhou, 3 Weiyi Road, 730000, Lanzhou, China.
authors.forename: Jiazhong
authors.initials: J
authors.lastname: Li
authors.affiliation: School of Pharmacy, Lanzhou University, 199 West Donggang Road, 730000, Lanzhou, China.
authors.forename: Fang
authors.initials: F
authors.lastname: Bai
authors.affiliation: School of Pharmacy, Lanzhou University, 199 West Donggang Road, 730000, Lanzhou, China.
authors.forename: Huanxiang
authors.initials: H
authors.lastname: Liu
authors.affiliation: Department of Theoretical and Applied Sciences, University of Insubria, via Dunant 3, 21100, Varese, Italy.
authors.forename: Paola
authors.initials: P
authors.lastname: Gramatica
mesh_terms: D059002:Androgen Receptor Antagonists / Q000737:chemistry* / Q000494:pharmacology*; D062126:Databases, Chemical; D015195:Drug Design; D008024:Ligands; D016014:Linear Models; D008958:Models, Molecular; D062105:Molecular Docking Simulation; D015394:Molecular Structure; D021281:Quantitative Structure-Activity Relationship; D060388:Support Vector Machine
chemical_list: D059002:Androgen Receptor Antagonists; D008024:Ligands
keywords: androgen receptor antagonist; comparative molecular field analysis; ligand efficiency; multiple linear regression; surface efficiency index