Chemometric modelling of triphenylmethyl derivatives as potent anticancer agents
Priyanka Mridha, Pallabi Pal, Kunal Roy · Molecular Simulation · 2014
The increase in number of cancer-affected patients worldwide has amplified the need for the development of new anticancer drug-like molecules. In this background, the quantitative structure–activity relationship (QSAR) has proved to be an efficient tool for the drug-designing process. In this work, the in silico technique is applied to study the anticancer activity of two different sets of triphenyl methyl (TPM) derivatives on SK-MEL 5 cell line. Chemometric tools such as genetic partial least squares (G/PLS) algorithm was used for phenethylamine and d-phenylalanine TPM derivatives, whereas genetic function approximation technique was utilised for phosphonate and phosphonochloridate TPM derivatives in development of QSAR models. The calculated descriptors represent the influence of geometry, topology, molecular shape and polarisability of the molecules on the anticancer activity of TPM derivatives. Internal and external validation tests of the models provide satisfactory results (R2 = 0.823, 0.880, Q2 = 0.732, 0.771, = 0.644, 0.716) proving the fitness and predictivity of the model in compliance with Organization for Economic Co-operation and Development principles. The developed models can be effectively utilised further for the prediction of anticancer activity of new compounds that fall within the domain of applicability of the referred models.