QSAR and Molecular Docking Studies of novel thiophene, pyrimidine, coumarin, pyrazole and pyridine derivatives as Potential Anti-Breast Cancer Agent

Year 2020, , 12 - 23, 15.06.2020

İdris Momohjimoh Ovaku , Abechi Stephehe Eyije Shallangwa Gideon Adamu Uzairu Adamu

https://doi.org/10.33435/tcandtc.614263

Cited By: 2

Abstract

Quantitative Structure Activity Relationship
(QSAR) and molecular Docking studies were carried out on some novel compounds to
generate a good QSAR models that relate the anti-breast cancer activity values
with the molecular structure of the compounds. Genetic Function Algorithm (GFA)
and Multiple Linear Regression Analysis (MLRA) were used to select the
descriptors that were used to build the models. The best model built was found
to have statistical validation values of squared correlation coefficient (R²) = 0.999, adjusted squared
correlation coefficient ( = 0.998, cross validation coefficient  = 0.998 and an external squared correlation coefficient
=
0.879 which was used to confirm the validation of the model. The docking results
showed that ligands 6 and 5 with binding energy (-9.2kcalmol^-1 and
-9.0kcalmol^-1) respectively have the highest binding affinity when
compared to the reference drug doxorubicin with binding energy (-6.8kcalmol^-1).
The stability and robustness of the built model showed that new anti-breast
cancer agents can be design from these derivatives.

Keywords

Keywords: Breast Cancer, QSAR model, Model Validation, Binding Affinity

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