Organic chemistry
Rashid Heidarimoghadam; Seyede Shima Mortazavi; Abbas Farmany
Abstract
In the present paper, informatics-aided quantitative structure activity relationship (QSAR) models using genetic algorithm-partial least square (GA-PLS), genetic algorithm-Kernel partial least square (KPLS), and Levenberg-Marquardt artificial neural network (LM ANN) approach were constructed to access ...
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In the present paper, informatics-aided quantitative structure activity relationship (QSAR) models using genetic algorithm-partial least square (GA-PLS), genetic algorithm-Kernel partial least square (KPLS), and Levenberg-Marquardt artificial neural network (LM ANN) approach were constructed to access the antimalarial activity (pIC50) of 2,5-diaminobenzophenone derivatives. Comparison of errors and correlation coefficients obtained by the models it was shown that the LM ANN approach works with a high correlation coefficient and low prediction error. This model was applied to the prediction of pIC50 values of 2,5-diaminobenzophenone derivatives. Applying the extended model to a dataset of 20 compounds demonstrate the reliability and accuracy of the model. Comparing three models revealed the superiority of the L-M ANN to predict the pIC50 of 2,5-diaminobenzophenones derivatives.
Analytical chemistry
Mehdi Nekoei
Volume 5, Issue 1, pp. 1-120, Serial No. 14 , January 2017, , Pages 79-98
Abstract
In this paper, the quantitative structure activity-relationship (QSAR) of the CCR2b receptor inhibitors was scrutinized. Firstly, the molecular descriptors were calculated using the Dragon package. Then, the stepwise multiple linear regressions (SW-MLR) and the genetic algorithm multiple linear regressions ...
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In this paper, the quantitative structure activity-relationship (QSAR) of the CCR2b receptor inhibitors was scrutinized. Firstly, the molecular descriptors were calculated using the Dragon package. Then, the stepwise multiple linear regressions (SW-MLR) and the genetic algorithm multiple linear regressions (GA-MLR) variable selection methods were subsequently employed to select and implement the prominent descriptors having the most significant contributions to the activities of the molecules. A combined data set including numerical values of inhibition activity data (IC50) of 103 CCR2b receptor derivatives was adopted for our simulations. This study revealed that both SW-MLR and GA-MLR methods consisted of six molecular descriptors. The adopted descriptors belong to topological, charge, RDF and atom-centered fragments classes. A comparison of results by the two methodologies indicated the superiority of GA-MLR over the SW-MLR method. The authenticity of the proposed model (GA-MLR) was further confirmed using the cross-validation, validation through an external test set and Y-randomization.
Biochemistry
Alireza Banaei; Eslam Pourbasheer; Fatemeh Haggi
Volume 4, Issue 3, pp. 236-358, Serial No. 12 , July 2016, , Pages 318-336
Abstract
Quantitative structure-activity relationship (QSAR) models were employed for prediction the activity of P2X7 receptor antagonists. A data set consisted of 50 purine derivatives was utilized in the model construction where 40 and 10 of these compounds were in the training and test sets respectively. A ...
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Quantitative structure-activity relationship (QSAR) models were employed for prediction the activity of P2X7 receptor antagonists. A data set consisted of 50 purine derivatives was utilized in the model construction where 40 and 10 of these compounds were in the training and test sets respectively. A suitable group of calculated molecular descriptors was selected by employing stepwise multiple linear regressions (SW-MLR) and genetic algorithm-multiple linear regressions (GA-MLR) as variable selection tools. The proposed MLR models were fully confirmed applying internal and external validation techniques. The obtained results of this QSAR study showed the superiority of the GA-MLR model over the SW-MLR model. As a result, the obtained GA–MLR model could be applied as a valuable model for designing similar groups of P2X7 receptor antagonists.
Physical chemistry
Esmaeil Vessally; Ali Jafari; Elaheh Ahmadi
Volume 4, Issue 1, pp. 1-132, Serial No. 10 , January 2016, , Pages 123-132
Abstract
In this work, the optimization calculations were carried out on quetiapine hemifumarat, 4, and its analogues, 1-5. These calculations were carried out using the B3LYP/6-31G(d) level of theory. The DFT calculations clarified a boat structure for dibenzothiazepine moiety of the molecule which piperazine ...
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In this work, the optimization calculations were carried out on quetiapine hemifumarat, 4, and its analogues, 1-5. These calculations were carried out using the B3LYP/6-31G(d) level of theory. The DFT calculations clarified a boat structure for dibenzothiazepine moiety of the molecule which piperazine moiety has a chair conformation. Thermal energies (E), enthalpies (H), and free energies (G) of quetiapine and its analogues, 1-5 were calculated at the B3LYP/6-31G(d) level. The chemical hardness (η), chemical potential (μ), dipole moment (D), electrophilicity (ω) and the maximum amount of electronic charge, ΔNmax, were determined. Some molecular properties for quantitative structure activity relationships (QSAR) were investigated.