Antimalarial Activity: A QSAR Modeling of NF54 Strain of Plasmodium falciparum by Physicochemical Descriptor Calculation
Journal Title: International Journal of Research in Pharmacy and Science - Year 2011, Vol 1, Issue 3
Abstract
Multiple linear regression analysis and other statistical analysis were carried out on all the compounds of training set. Descriptors were selected for the model based on their correlation coefficient and those descriptors having interred correlation coefficient below 0.5 were considered. Various models were obtained after performing multiple linear regression analysis. The dataset are based on the NF54 strains of P. falciparum consisting of 69 organic compounds. The size of the final training set therefore became 53 compounds and test set 16 compounds. Descriptors were selected for the model based on their correlation coefficient and that descriptor having intercorrelation coefficient below 0.5 were considered. Various models were obtained after performing multiple linear regression (MLR) analysis. Model predictive power was judged based on various statistical parameters like correlation coefficient, regression coefficient (r2), fisher statistical value (F), and standard error. The initial regression analysis was performed on all the 37 molecules which resulted in regression model. The best QSAR model has the characters of large F, low P value, r2 and q2 values close to 1, as well as P< 0.001.
Authors and Affiliations
Vinayaditya Singh , Ameeta Argal
Keywords
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