Yellow fever is a major problem associated with the health particularly in the Africa and South America region. In last few years scientist focus on in silico approach before synthesizing a compound to accelerate the drug discovery process. In the present study a series of 20 compounds of imidazole-4, 5- and pyrazine-2,3- dicarboxamides derivatives having anti yellow fever activity were subjected QSAR analysis using 2D PaDEL descriptors available online. Three different splitting techniques namely activity sorting, distance based and Kennard stone based splitting were used to divide the whole data set and GFA was used a statistical method to develop a model to investigate the physicochemical and structural requirement of potential yellow fever virus inhibitor. All the models are statistically robust both internally and externally (Q2Loo:0.605-0.739,
R_((pred))^2: 0.711-0.934) with low RMSEP (0.106-0.250) values. Additionally the full model shows statistically significant Q2Lmo value of 0.684. The activity mostly affected by polarizabilities, electro negativities as well as charges in the compounds indicates the importance of heterocyclic ring system attached. Finally the randomization results indicate the models are not by chance.
Keywords: Yellow fever, GFA, RMSEP, PaDEL, drug discovery, randomization.
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