Quantitative structure–activity relationship study on potent anticancer compounds against MOLT-4 and P388 leukemia cell lines

• Main Authors: David Ebuka Arthur, Adamu Uzairu, Paul Mamza, Stephen Abechi
• Format: Article
• Language: English
• Published: Elsevier 2016-09-01
• Series: Journal of Advanced Research
• Subjects: QSAR method; Anticancer; paDEL descriptors; Applicability domain; Cell lines; NCI database
• Online Access: http://www.sciencedirect.com/science/article/pii/S2090123216300121

A quantitative structure–activity relationship (QSAR) study was carried out on 112 anticancer compounds to develop a robust model for the prediction of anti-leukemia activity (pGI50) against MOLT-4 and P388 leukemia cell lines. The Genetic algorithm (GA) and multiple linear regression analysis (MLRA) were used to select the descriptors and to generate the correlation models that relate the structural features to the biological activities. The final equations consist of 15 and 10 molecular descriptors calculated using the paDEL molecular descriptor software. The GA-MLRA analysis showed that the Conventional bond order ID number of order 1 (piPC1), number of atomic composition (nAtomic), and Largest absolute eigenvalue of Burden modified matrix – n 7/weighted by relative mass (SpMax7_Bhm) play a significant role in predicting the anticancer activities of these compounds. The best QSAR model for MOLT-4 was obtained with R2 value of 0.902, Q2LOO = 0.881 and R2pred = 0.635, while for P388 cell line R2 = 0.904, Q2LOO = 0.856 and R2pred = 0.670. The Y-scrambling/randomization validation also confirms the statistical significance of the models. These models are expected to be useful for predicting the inhibitory activity (pGI50) against MOLT-4 and P388 leukemia cell lines.