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Ligand Efficiency Outperforms pIC 50 on Both 2D MLR and 3D Co MFA Models: A Case Study on AR Antagonists
Author(s) -
Li Jiazhong,
Bai Fang,
Liu Huanxiang,
Gramatica Paola
Publication year - 2015
Publication title -
chemical biology and drug design
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 77
eISSN - 1747-0285
pISSN - 1747-0277
DOI - 10.1111/cbdd.12619
Subject(s) - quantitative structure–activity relationship , linear regression , chemistry , stereochemistry , mathematics , biological system , computational biology , computer science , statistics , biology
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 pIC 50 . 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 pIC 50 and SEI as dependent variables to verify the influence of using different kinds of end‐points. The obtained results suggest that SEI outperforms pIC 50 on both MLR and Co MFA models with higher stability and predictive ability. After analyzing the characteristics of the two dependent variables SEI and pIC 50 , 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 pIC 50 . This study indicates that SEI could be a more rational parameter to be optimized in the drug discovery process than pIC 50 .