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From Molecular Docking to 3D‐Quantitative Structure‐Activity Relationships (3D‐QSAR): Insights into the Binding Mode of 5‐Lipoxygenase Inhibitors
Author(s) -
Eren Gokcen,
Macchiarulo Antonio,
Banoglu Erden
Publication year - 2012
Publication title -
molecular informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.481
H-Index - 68
eISSN - 1868-1751
pISSN - 1868-1743
DOI - 10.1002/minf.201100101
Subject(s) - quantitative structure–activity relationship , chemistry , computational biology , docking (animal) , arachidonate 5 lipoxygenase , stereochemistry , test set , molecular model , computer science , machine learning , biology , biochemistry , enzyme , medicine , nursing , arachidonic acid
Pharmacological intervention with 5‐Lipoxygenase (5‐LO) is a promising strategy for treatment of inflammatory and allergic ailments, including asthma. With the aim of developing predictive models of 5‐LO affinity and gaining insights into the molecular basis of ligand‐target interaction, we herein describe QSAR studies of 59 diverse nonredox‐competitive 5‐LO inhibitors based on the use of molecular shape descriptors and docking experiments. These studies have successfully yielded a predictive model able to explain much of the variance in the activity of the training set compounds while predicting satisfactorily the 5‐LO inhibitory activity of an external test set of compounds. The inspection of the selected variables in the QSAR equation unveils the importance of specific interactions which are observed from docking experiments. Collectively, these results may be used to design novel potent and selective nonredox 5‐LO inhibitors.