Sets of quinolizidinyl derivatives of bi-and tri-cyclic (hetero) aromatic systems were studied as selective inhibitors. On the pattern, quantitative structure-activity relationship (QSAR) study has been done on quinolizidinyl derivatives as potent inhibitors of acetylcholinesterase in alzheimer's disease (AD). Multiple linear regression (MLR), partial least squares (PLSs), principal component regression (PCR), and least absolute shrinkage and selection operator (LASSO) were used to create QSAR models. Geometry optimization of compounds was carried out by B3LYP method employing 6-31 G basis set. HyperChem, Gaussian 98 W, and Dragon software programs were used for geometry optimization of the molecules and calculation of the quantum chemical descriptors. Finally, Unscrambler program was used for the analysis of data. In the present study, the root mean square error of the calibration and R 2 using MLR method were obtained as 0.1434 and 0.95, respectively. Also, the R and R 2 values were obtained as 0.79, 0.62 from stepwise MLR model. The R 2 and mean square values using LASSO method were obtained as 0.766 and 3.226, respectively. The root mean square error of the calibration and R 2 using PLS method were obtained as 0.3726 and 0.62, respectively. According to the obtained results, it was found that MLR model is the most favorable method in comparison with other statistical methods and is suitable for use in QSAR models.
The structure of model magnesium hydrate pyrimidine nucleotides (CMP, UMP, dTMP) adducts has been studied at the Hartree-Fock level and by using LANL2DZ basis set for magnesium and 6-31g* basis set for other atoms. The basis set superposition error (BSSE) begins to converge for used Method/basis set. A natural bond orbital calculation was carried out at the Hartree-Fock level and 6-3 lg* basis set of theory to determined donor-acceptor (bonding-antibonding) interactions. The gauge-invariant atomic orbital (GIAO) method and the continuous-set-of-gauge-transformation (CSGT) procedure were employed to calculate isotropic atomic shielding of the nucleotides and magnesium hydrate-pyrimidine nucleotides by using density functional theory at the B3LYP/6-31g** and HF/6-31g** level.
In this work quantitative structure-activity relationship (QSAR) study has been done on 1,2-ethylenediamine derivatives as anti-tuberculosis drugs. Genetic algorithm (GA), artificial neural network (ANN), multiple linear regressions (stepwise-MLR) and Imperialist Competitive Algorithm (ICA), were used to create the nonlinear and linear QSAR models. The root-mean square errors of the training set and the test set for GA-ANN models using the jack-knife method, were 0.1402, 0.1304 and Q 2 = 0.94. Also, the R and R 2 values 0.85, 0.73 in the gas phase were obtained from a GA-stepwise-MLR model. Q2 of training set for PLS was 0.52. The results obtained from this work indicate that ANN and ICA models are more effective than other statistical methods and exhibit reasonable prediction capabilities. The best descriptors are G3u,
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