In silico QSAR and molecular docking studies of sulfur containing shikonin oxime derivatives as anti-cancer agent for colon cancer

Abstract

ObjectivesThis study is aimed at generating a statistically valid model using molecular descriptors and physicochemical parameters on sulfur-containing shikonin oxime derivatives and to have better understanding of binding affinity of these compounds as well as their various interactions with the target receptor so as to pave way for the designing of highly potent anti-colon cancer drug. Materials and methodsQuantitative structure–activity relationship and molecular docking studies were carried out on 40 dataset of sulfur containing shikonin oxime derivatives. Density functional theory were employed in optimizing the molecule with B3LYP/6-31G* as basis set, while descriptor selection and generation of multiple linear regression model that correlates the structural feature of the compounds to their experimental activities was done by employing Genetic Function Algorithm (GFA). The softwares that was used in this study include Chemdraw, Spartan software, Padel, Material studio, Pyrex, Vina wizard, Autoduck, as well as Discovery studio. ResultsAmong the models generated, the one with best statistical significance was selected and it has R2 value of 0.92, adjusted R2 value of 0.89, and leave one out (LOO) cross validation coefficient (Q2) value of 0.85. To confirm the predictive capacity of the selected model, external validation was carried out using the test set compounds and it has the R2ext value of 0.88. Molecular docking study revealed that all the compounds have favorable binding affinity to the target receptor, compound number 23 has the highest binding affinity of −8.3 kcal/mol and favorable number of various interactions. ConclusionBased on the parameters of internal and external validation, the robustness, stability and predictive ability of the selected model was verified, compounds number 23 with highest binding affinity and favorable number of various interactions can be used as lead compound in the feature design of highly potent anti-colon cancer drug.