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Authors
Advisor(s)
Abstract(s)
Peroxisome Proliferator Activated Receptor b/d (PPAR b/d), one of three PPAR isoforms
is a member of nuclear receptor superfamily and ubiquitously expressed in several
metabolically active tissues such as liver, muscle, and fat. Tissue specific expression and
knock-out studies suggest a role of PPARd in obesity and metabolic syndrome. Specific
and selective PPARd ligands may play an important role in the treatment of metabolic
disorders. Indanylacetic acid derivatives reported as potent and specific ligands against
PPARd have been studied for the Quantitative Structure – Activity Relationships
(QSAR). Molecules were represented by chemical descriptors that encode constitutional,
topological, geometrical, and electronic structure features. Four different approaches, i.e.,
random selection, hierarchical clustering, k-means clustering, and sphere exclusion
method were used to classify the dataset into training and test subsets. Forward stepwise
Multiple Linear Regression (MLR) approach was used to linearly select the subset of
descriptors and establish the linear relationship with PPARd agonistic activity of the
molecules. The models were validated internally by Leave One Out (LOO) and externally
for the prediction of test sets. The best subset of descriptors was then fed to the Artificial
Neural Networks (ANN) to develop non-linear models. Statistically significant MLR
models; with R2 varying from 0.80 to 0.87 were generated based on the different training
and test set selection methods. Training of ANNs with different architectures for the
different training and test selection methods resulted in models with R2 values varying
from 0.83 to 0.94, which indicates the high predictive ability of the models.
Description
Keywords
Artificial neural network Indanylacetic acids Multiple linear regression (MLR) Peroxisome proliferator activated receptor (PPAR) QSAR . Faculdade de Ciências Exatas e da Engenharia
Citation
Lather, V., & Fernandes, M. X. (2009). QSAR models for prediction of PPARδ agonistic activity of indanylacetic acid derivatives. QSAR & Combinatorial Science, 28(4), 447-457.
Publisher
Wiley