Biological activities of triazine derivatives. Combining DFT and QSAR results

Larif, Majdouline; Adad, Azeddine; Hmammouchi, Rachid; Taghki, Abdelhafid Idrissi; Soulaymani, Abdelmajid; Elmidaoui, A.; Bouachrine, Mohammed; Lakhlifi, Tahar

doi:10.1016/j.arabjc.2012.12.033

Cited by 36 publications

(22 citation statements)

References 28 publications

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“…The structures of 18 hydroxamic acid compounds were studied by statistical methods based on Principal Component Analysis (PCA) [25] [26] [27] using the software XLSTAT version 2014 [20] to determine the descriptors that are related. direct with anticancer activity.…”

Section: Discussionmentioning

confidence: 99%

DFT Study, Linear and Nonlinear Multiple Regression in the Prediction of HDAC7 Inhibitory Activities on a Series of Hydroxamic Acids

Soro¹,

Ekou²,

Ouattara³

et al. 2019

CMB

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In this work, we conducted a QSAR study on 18 molecules using descriptors from the Density Functional Theory (DFT) in order to predict the inhibitory activity of hydroxamic acids on histone deacetylase 7. This study is performed using the principal component analysis (PCA) method, the Ascendant Hierarchical Classification (AHC), the linear multiple regression method (LMR) and the nonlinear multiple regression (NLMR). DFT calculations were performed to obtain information on the structure and information on the properties on a series of hydroxamic acids compounds studied. Multivariate statistical analysis yielded two quantitative models (model MLR and model MNLR) with the quantum descriptors: electronic affinity (AE), vibration frequency of the OH bond (ν(OH)) and that of the NH bond (ν(NH)). The LMR model gives statistically significant results and shows a good predictability R 2 = 0.9659, S = 0.488, F = 85 and p-value < 0.0001. Electronic affinity is the priority descriptor in predicting the activity of HDAC7 inhibitors in this study. The results obtained suggest that the descriptors derived from the DFT could be useful to predict the activity of histone deacetylase 7 inhibitors. These models were evaluated according to the criteria of Tropsha et al.

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Section: Discussionmentioning

confidence: 99%

DFT Study, Linear and Nonlinear Multiple Regression in the Prediction of HDAC7 Inhibitory Activities on a Series of Hydroxamic Acids

Soro¹,

Ekou²,

Ouattara³

et al. 2019

CMB

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“…RML minimizes differences between actual and expected values. The advantage of RML is that it is very transparent, since the algorithm is available, and that predictions can be made easily [28]. The RML method is based on the assumption that the property depends linearly on the different variables (the descriptors), according to the relation:…”

Section: Régressions Multiple Linéaires Et Non Linéaire (Rml Et Rmnl)mentioning

confidence: 99%

Predictive Modeling of the Human Hepatoma (Huh-7D12) Cancer Line of a Series of bis- (5-arylidene-rhodanine-3-yl) Diamine

Kouassi

Bénié

Koné

et al. 2019

AJOCS

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This work deals with the prediction of the antiproliferative activity of eighteen (18) substances derived from bis-5-arylidene rhodanine against human hepatoma tumor line (Huh-7D12). By applying the functional density theory (DFT) method to the B3LYP / 6-31G (d, p) level, theoretical descriptors were determined and correlated with antiproliferative (Huh-7) activity by linear Kouassi et al.; AJOCS, 6(2): 1-11, 2019; Article no.AJOCS.49740 2 CV = 0,998 ; RMSE = 0,006). Original Research Article

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“…On the other hand, quantitative structure-activity relationship (QSAR) searches predict the relationship of chemical structure to both biological and other activities through the use of predictive models (Larif et al, 2013;Sharma et al, 2013). Several molecular descriptors are employed to quantify the structural features of the lead molecule.…”

Section: Introductionmentioning

confidence: 99%

Experimental and theoretical study of bifunctionalized PEO–PPO–PEO triblock copolymers with applications as dehydrating agents for heavy crude oil

Flores-Sandoval

Castro

Flores

et al. 2017

Arabian Journal of Chemistry

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A series of a,x-diamines of polyoxyethylene-polyoxypropylene-polyoxyethylene (POE-POP-POE) triblock copolymer was synthesized and experimentally evaluated as dewatering agents for heavy crude oil. A quantitative structure-activity relationship (QSAR) study of the effect of the secondary amine structure over the yield of nucleophilic substitution reactions with a,x-ditosylate ester of PEO-PPO-PEO triblock copolymer was performed exclusively at the DFT level. Multiple linear regression (MLR) analysis including softness or hardness parameters gave R 2 = 0.9062, producing an equation with an acceptable r 2 mðtestÞ value. Furthermore, in order to understand the physicochemical interaction between the functionalizing copolymers and water, QSAR models

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Biological activities of triazine derivatives. Combining DFT and QSAR results

Cited by 36 publications

References 28 publications

DFT Study, Linear and Nonlinear Multiple Regression in the Prediction of HDAC7 Inhibitory Activities on a Series of Hydroxamic Acids

DFT Study, Linear and Nonlinear Multiple Regression in the Prediction of HDAC7 Inhibitory Activities on a Series of Hydroxamic Acids

Predictive Modeling of the Human Hepatoma (Huh-7D12) Cancer Line of a Series of bis- (5-arylidene-rhodanine-3-yl) Diamine

Experimental and theoretical study of bifunctionalized PEO–PPO–PEO triblock copolymers with applications as dehydrating agents for heavy crude oil

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