Open AccessQSAR Modeling of HIV‐1 Protease Inhibition on Six‐ and Seven‐membered Cyclic Ureas
Author(s) -
Takkis Kalev,
Sild Sulev
Publication year - 2009
Publication title -
qsar & combinatorial science
Language(s) - English
Resource type - Journals
eISSN - 1611-0218
pISSN - 1611-020X
DOI - 10.1002/qsar.200860006
Subject(s) - quantitative structure–activity relationship , molecular descriptor , linear regression , protease , hiv 1 protease , correlation coefficient , human immunodeficiency virus (hiv) , biological system , protease inhibitor (pharmacology) , chemistry , linear model , set (abstract data type) , mathematics , computer science , stereochemistry , statistics , biochemistry , biology , antiretroviral therapy , immunology , viral load , programming language , enzyme
A Quantitative Structure–Activity Relationship (QSAR) analysis was carried out on a dataset of 135 six‐ and seven‐membered cyclic urea‐based Human Immunodeficiency Virus Type 1 (HIV‐1) protease inhibitors. Using a larger and more diverse dataset than previous studies reported in literature allowed a more comprehensive analysis. A large set of molecular descriptors, calculated with CODESSA PRO, was used in Multiple Linear Regression (MLR) analysis and the resulting four‐parameter model enabled accurate prediction of inhibitory activity for the structures both in training and external validation sets. The squared correlation coefficient for both sets combined is 0.824. Descriptors in the final model characterize the size and shape of the molecule and its charge distribution. Non‐linear relationships between the HIV‐1 protease inhibition activity and some descriptors are significant and described with simple non‐linear transformations. After the model development, another dataset of 45 compounds was collected and additional external validation was performed.