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Authors
Advisor(s)
Abstract(s)
One of the biggest challenges in QSAR studies
using three-dimensional descriptors is to generate
the bioactive conformation of the molecules. Com parative QSAR analyses have been performed on a
dataset of 34 structurally diverse and competitive
CYP2C9 inhibitors by generating their lowest
energy conformers as well as additional multiple
conformers for the calculation of molecular de scriptors. Three-dimensional descriptors account ing for the spatial characteristics of the molecules
calculated using E-Dragon were used as the inde pendent variables. The robustness and the predic tive performance of the developed models were
verified using both the internal [leave-one-out
(LOO)] and external statistical validation (test set
of 12 inhibitors). The best models (MLR using GET AWAY descriptors and partial least squares using
3D-MoRSE) were obtained by using the multiple
conformers for the calculation of descriptors and
were selected based upon the higher external pre diction (R2
test values of 0.65 and 0.63, respectively)
and lower root mean square error of prediction
(0.48 and 0.48, respectively). The predictive ability
of the best model, i.e., MLR using GETAWAY de scriptors was additionally verified on an external
test set of quinoline-4-carboxamide analogs and
resulted in an R2
test value of 0.6. These simple and
alignment-independent QSAR models offer the
possibility to predict CYP2C9 inhibitory activity of
chemically diverse ligands in the absence of X-ray
crystallographic information of target protein
structure and can provide useful insights about
the ADMET properties of candidate molecules in
the early phases of drug discovery.
Description
Keywords
3D-MoRSE ADMET CYP2C9 GETAWAY QSAR RDF WHIM . Faculdade de Ciências Exatas e da Engenharia
Citation
Lather, V., & Fernandes, M. X. (2011). Comparative QSAR analyses of competitive CYP2C9 inhibitors using three-dimensional molecular descriptors. Chemical Biology & Drug Design, 78(1), 112-123.
Publisher
Wiley