Prediction of Xanton Derivatives as Anti Heart Cancer using In Silico Quantitative Structure-Property Relationships

Abstract

Quantitative Structure-Activity Relationship (QSAR) study have been performed on Xanthone derivatives as anti-cancer activity. The objectives of this research is to design a new Xanthone derivatives from the best  QSAR equation model. The data set were taken from the previous study, involving 41 Xanthone derivatives and their biology activities in Inhibitor Concentration 50 % (IC50). The parameters (descriptors) were calculated by semiempirical PM3 method. The selection of the best QSAR equation models was determined by multilinear regression analysis. The best linear equation resulted from that analysis is: Log 1/IC50 = 13,099 + 2,837 qC1 + 0,098 qC2 + 11,214 qC10 + 2,065 qC13 – 1,236 qC14 + 35,356 qO15 + 0,001 (vol) – 0,025 (log P) + 0,283 (dipole) n = 41; r = 0.735; adjusted r2 = 0.360; Fhit/Ftab = 1.2911; PRESS = 5.0089. Based on that model, a new Xanthon derivatives has been design which show better predicted biology activity (log 1/IC50= 15,0863), new derivatives have the log 1/IC50 higher than the old one (log 1/IC50= 9). This result indicated that new Xanthone derivatives has potential to developed as new anti-cancer drug