0.84 was developed using stepwise MLR and a comparable PLS and FFNN
model with r? (cv) = 0.89, 0.88 and 0.86 respectively. After the data
reduction, five promising descriptors left were total dipole moment, Log P,
VAMP total energy, VAMP LUMO and VAMP HOMO. In addition of QSAR modeling,
Lipinski?s rule of five was also employed that check the pharmacokinetic
profile of the model. The similarity (CARBO and HODGKIN) analysis was also done
on the same series which positively support the previous results. The QSAR
study reported in the present study provide important structural situation,
related to anti-diabetic activity. Present study enlightens the path of
determining the potent lead compounds of DGAT-1 antagonist. QSAR (Quantitative
structure activity relationship) is a powerful and mathematical technique to
set off the correlation in between chemical structure to their biological
activity. It was performed on a series of amide-oxadiazole-aniline derivative
with activity against DGAT-1 employing various physiochemical parameters like
topological, lipophilic and electronic. The best model was generated and shows
good correlative and predictive ability with values S = 0.33, F = 41.91, r =
0.94, r? = 0.88, r? (cv) = - See more at:
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