Quantitative structure–activity relationship (QSAR) of aryl alkenyl amides/imines for bacterial efflux pump inhibitors
A quantitative structure–activity relationship (QSAR) analysis has been performed on a data set of 42 aryl alkenyl amides/imines as bacterial efflux pump inhibitors. Several types of descriptors including topological, spatial, thermodynamic, information content and E-state indices have been used to...
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Published in | European journal of medicinal chemistry Vol. 44; no. 1; pp. 229 - 238 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Kidlington
Elsevier Masson SAS
2009
Elsevier |
Subjects | |
Online Access | Get full text |
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Summary: | A quantitative structure–activity relationship (QSAR) analysis has been performed on a data set of 42 aryl alkenyl amides/imines as bacterial efflux pump inhibitors. Several types of descriptors including topological, spatial, thermodynamic, information content and E-state indices have been used to derive a quantitative relationship between the efflux pump inhibiting activity and structural properties. Algorithm based on genetic function approximation method of variable selection was used to generate the model. Statistically significant model (with
r
2
=
0.87) was obtained with the descriptors like radius of gyration and heat of formation besides E-state indices,
A
log
P atom types and solvent accessible charged surface area playing an important role in determining the activity of the compounds against bacterial efflux pump. The model was also tested successfully for external validation criteria. The model is not only able to predict the activity of new compounds but also explained the important regions in the molecules in quantitative manner.
[Display omitted] 2D quantitative structure–activity relationship (QSAR) model has been developed for a series of aryl alkenyl amides/imine based bacterial efflux pump inhibitors. Several types of descriptors including topological, spatial, thermodynamic, information content and E-state indices were used to derive the model and genetic function approximation technique was used for variable selection. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0223-5234 1768-3254 |
DOI: | 10.1016/j.ejmech.2008.02.015 |