A novel QSAR model for predicting the inhibition of CXCR3 receptor by 4-N-aryl-[1,4] diazepane ureas

A linear quantitative structure–activity relationship (QSAR) model is presented for modeling and predicting the inhibition of CXCR3 receptor. The model was produced by using the multiple linear regression (MLR) technique on a database that consists of 32 recently discovered 4-N-aryl-[1,4] diazepane ureas. The key conclusion of this study is that 3k, ChiInf8, ChiInf0, AtomCompTotal and ClogP affect significantly the inhibition of CXCR3 receptor by diazepane ureas. The selected physicochemical descriptors serve as a first guideline for the design of novel and potent antagonists of CXCR3.

A linear quantitative structure–activity relationship (QSAR) model is presented for modeling and predicting the inhibition of CXCR3 receptor. The model was produced by using the multiple linear regression (MLR) technique on a database that consists of 32 recently discovered 4-N-aryl-[1,4] diazepane ureas. The key conclusion of this study is that kappa3, ChiInf8, ChiInf0, AtomCompTotal and C log P affect significantly the inhibition of CXCR3 receptor by diazepane ureas. The selected physicochemical descriptors serve as a first guideline for the design of novel and potent antagonists of CXCR3.log(1/IC50)=3.99−2.58ChiInf0−2.35ChiInf8−8.85−10−3AtomCompTot+7.78−10−1k3+1.94−10−1CLogPR2=0.82RMS=0.21F=16.94Q2=0.71SPRESS=0.23n=25Figure optionsDownload as PowerPoint slide