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QSAR study of dihydrofolate reductase inhibitors activities based on optimization of correlation weights of local graph invariants
by
Khoshkam, Maryam
, Kompany-Zareh, Mohsen
in
Algorithms
/ Biological activity
/ Correlation
/ Datasets
/ Dihydrofolate reductase
/ E coli
/ Enzymes
/ Genetic algorithms
/ Inhibitors
/ Invariants
/ Modelling
/ Neural networks
/ Optimization
/ Physicochemical properties
/ Radial basis function
/ Reductases
2012
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QSAR study of dihydrofolate reductase inhibitors activities based on optimization of correlation weights of local graph invariants
by
Khoshkam, Maryam
, Kompany-Zareh, Mohsen
in
Algorithms
/ Biological activity
/ Correlation
/ Datasets
/ Dihydrofolate reductase
/ E coli
/ Enzymes
/ Genetic algorithms
/ Inhibitors
/ Invariants
/ Modelling
/ Neural networks
/ Optimization
/ Physicochemical properties
/ Radial basis function
/ Reductases
2012
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Do you wish to request the book?
QSAR study of dihydrofolate reductase inhibitors activities based on optimization of correlation weights of local graph invariants
by
Khoshkam, Maryam
, Kompany-Zareh, Mohsen
in
Algorithms
/ Biological activity
/ Correlation
/ Datasets
/ Dihydrofolate reductase
/ E coli
/ Enzymes
/ Genetic algorithms
/ Inhibitors
/ Invariants
/ Modelling
/ Neural networks
/ Optimization
/ Physicochemical properties
/ Radial basis function
/ Reductases
2012
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QSAR study of dihydrofolate reductase inhibitors activities based on optimization of correlation weights of local graph invariants
Journal Article
QSAR study of dihydrofolate reductase inhibitors activities based on optimization of correlation weights of local graph invariants
2012
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Overview
The aim of this work is modeling the activities of 67 E. coli dihydrofolate reductase (DHFR) inhibitors 2,4-diamino-5-(substituted benzyl) pyramidines by optimization of correlation weights of local graph invariants (cwlgis), assisting genetic algorithm (GA). The relationship between the descriptors and molecular activities was modeled using radial basis function partial least squares (rbfPLS). Proper relation between activities and the optimized molecular descriptors were shown, Rtraining = 0.92 and rtest = 0.85. The results indicate promising potential for the optimization of a correlation weights scheme. It is the first application of GA in optimization of cwlgis. The study also shows the ability of rbfPLS, combined with GA, in a factor-based nonlinear QSAR modeling using simple flexible descriptors.
Publisher
Springer Nature B.V
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