In the present study, sixty phosphoramidate and phosphorothioamidate analogues of amiprophos methyl (APM) previously reported as potential antimalarial agents were selected to build GA-MLR QSAR models to determine the features that govern the antimalarial activity. In addition, field similarity analysis was performed to determine the molecular fields that are responsible for the difference in the activity. The two tautomeric forms, possible for the molecules in the present study, were considered to determine the effect of tautomerism on QSAR modelling. In the present analysis, a simplistic approach was employed with the assumption that all the molecules either exist in keto-type tautomeric form or in enol-type form. To get more results from QSAR analysis, multiple models were developed. All the models have been thoroughly validated according to the OECD principles. The best four-parametric GA-MLR QSAR model is with R2 = 0.787 and Rex2 = 0.806 for the keto form, and R2 = 0.785 and Rex2 = 0.770 for the enol form. In addition, optimum values for more easily interpretable descriptors like molecular weight (MW), lipophilicity (ALogP), etc., have been determined. The analysis reveals that consideration of tautomerism and multiple models development enhance the efficiency of QSAR analysis for lead optimization and for prediction of the activities of as-yet untested molecules.
Tautomerism and multiple modelling enhance the efficacy of QSAR: antimalarial activity of phosphoramidate and phosphorothioamidate analogues of amiprophos methyl
GRAMATICA, PAOLA;
2014-01-01
Abstract
In the present study, sixty phosphoramidate and phosphorothioamidate analogues of amiprophos methyl (APM) previously reported as potential antimalarial agents were selected to build GA-MLR QSAR models to determine the features that govern the antimalarial activity. In addition, field similarity analysis was performed to determine the molecular fields that are responsible for the difference in the activity. The two tautomeric forms, possible for the molecules in the present study, were considered to determine the effect of tautomerism on QSAR modelling. In the present analysis, a simplistic approach was employed with the assumption that all the molecules either exist in keto-type tautomeric form or in enol-type form. To get more results from QSAR analysis, multiple models were developed. All the models have been thoroughly validated according to the OECD principles. The best four-parametric GA-MLR QSAR model is with R2 = 0.787 and Rex2 = 0.806 for the keto form, and R2 = 0.785 and Rex2 = 0.770 for the enol form. In addition, optimum values for more easily interpretable descriptors like molecular weight (MW), lipophilicity (ALogP), etc., have been determined. The analysis reveals that consideration of tautomerism and multiple models development enhance the efficiency of QSAR analysis for lead optimization and for prediction of the activities of as-yet untested molecules.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.