QSARs for a series of inhibitory anilides

Zakarya, Driss; Larfaoui, E. M.; Boulaamail, A.; Tollabi, Mustapha; Lakhlifi, Tahar

doi:10.1016/s0045-6535(97)10239-9

Cited by 9 publications

(5 citation statements)

References 11 publications

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“…Almost all QSAR techniques are based on the use of molecular descriptors, which are numerical series that codify useful chemical information and enable the identification of correlations between statistical and biological properties [14,15]. Different QSAR studies from different research groups have identified important structural features that are responsible for activities [16,17] and aided the development of toxicity models for diverse chemicals [18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Predictive modelling of the LD₅₀ activities of coumarin derivatives using neural statistical approaches: Electronic descriptor-based DFT

Hmamouchi

Larif

Chtita

et al. 2016

Journal of Taibah University for Science

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A study of structure-activity relationship (QSAR) was performed on a set of 30 coumarin-based molecules. This study was performed using multiple linear regressions (MLRs) and an artificial neural network (ANN). The predicted values of the antioxidant activities of coumarins were in good agreement with the experimental results. Several statistical criteria, such as the mean square error (MSE) and the correlation coefficient (R), were studied to evaluate the developed models. The best results were obtained with a network architecture [8-4-1] (R = 0.908, MSE = 0.032), activation functions (tansig-purelin) and the Levenberg-Marquardt learning algorithm. The model proposed in this study consists of large electronic descriptors that are used to describe these molecules. The results suggested that the proposed combination of calculated parameters may be useful for predicting the antioxidant activities of coumarin derivatives.

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Section: Introductionmentioning

confidence: 99%

Predictive modelling of the LD₅₀ activities of coumarin derivatives using neural statistical approaches: Electronic descriptor-based DFT

Hmamouchi

Larif

Chtita

et al. 2016

Journal of Taibah University for Science

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“…Shimizu et al [9] reported a quantitative structure-activity relationship for inhibition of the photosystem II by the substituted anilides. Zakarya et al [10] applied neural network to study a series of anilide herbicides inhibiting & Mukesh C. Sharma mukeshcsharma@yahoo.com photosystem II. Teixeira et al [11] developed QSAR models with photosynthetic inhibitory activity of the naturally occurring toxin nostoclides.…”

Section: Introductionmentioning

confidence: 99%

Identification of 3-Nitro-2,4,6-trihydroxybenzamide Derivatives as Photosynthetic Electron Transport Inhibitors by QSAR and Pharmacophore Studies

Sharma

2015

Interdiscip Sci Comput Life Sci

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In the present investigation, quantitative structure-activity relationship (QSAR) analysis was performed on a data set consisting of structurally diverse compounds in order to investigate the role of their structural features on their photosynthetic electron transport Inhibitors. The best 2D-QSAR model was selected, having correlation coefficient r (2) = 0.8544 and cross-validated squared correlation coefficient q (2) = 0.7139 with external predictive ability of pred_r (2) = 0.7753. The results obtained in this study indicate that the presence of hydroxy and nitro groups, expressed by the SsOHcount and SddsN (nitro) count, is the most relevant molecular property determining efficiency of photosynthetic inhibitory. Molecular field analysis was used to construct the best k-nearest neighbor (kNN-MFA)-based 3D-QSAR model using SA-PLS method, showing good correlative and predictive capabilities in terms of [Formula: see text] and [Formula: see text]. The pharmacophore model includes three features viz. hydrogen bond donor, hydrogen bond acceptor, and one aromatic feature. The developed model was found to be predictive and can be used to design potent photosynthetic electron transport activities prior to their synthesis for further lead modification.

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“…In turn, the requirement that the tail must extend out of the Q B site constrains the size of the other herbicide substituents in the pocket [ 15 ]. In addition to phenylurea-type herbicides, various other compounds possessing an amide -NHCO- moiety were also found to inhibit the photosynthetic electron transport [ 16 , 17 , 18 , 19 , 20 , 21 ]. Better understanding of these SAR relationships are not only important for the design of modern agricultural agents, but can also provide remarkable insights into the photosynthetic mechanisms of green cells.…”

Section: Introductionmentioning

confidence: 99%

Ring-substituted 4-Hydroxy-1H-quinolin-2-ones: Preparation and Biological Activity

Jampílek¹,

Musioł

Peško

et al. 2009

Molecules

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In the study, a series of twelve ring-substituted 4-hydroxy-1H-quinolin-2-one derivatives were prepared. The procedures for synthesis of the compounds are presented. The compounds were analyzed using RP-HPLC to determine lipophilicity and tested for their photosynthesis-inhibiting activity using spinach (Spinacia oleracea L.) chloroplasts. All the synthesized compounds were also evaluated for antifungal activity using in vitro screening with eight fungal strains. For all the compounds, the relationships between the lipophilicity and the chemical structure of the studied compounds are discussed, as well as their structure-activity relationships (SAR).

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QSARs for a series of inhibitory anilides

Cited by 9 publications

References 11 publications

Predictive modelling of the LD₅₀ activities of coumarin derivatives using neural statistical approaches: Electronic descriptor-based DFT

Predictive modelling of the LD₅₀ activities of coumarin derivatives using neural statistical approaches: Electronic descriptor-based DFT

Identification of 3-Nitro-2,4,6-trihydroxybenzamide Derivatives as Photosynthetic Electron Transport Inhibitors by QSAR and Pharmacophore Studies

Ring-substituted 4-Hydroxy-1H-quinolin-2-ones: Preparation and Biological Activity

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QSARs for a series of inhibitory anilides

Cited by 9 publications

References 11 publications

Predictive modelling of the LD50 activities of coumarin derivatives using neural statistical approaches: Electronic descriptor-based DFT

Predictive modelling of the LD50 activities of coumarin derivatives using neural statistical approaches: Electronic descriptor-based DFT

Identification of 3-Nitro-2,4,6-trihydroxybenzamide Derivatives as Photosynthetic Electron Transport Inhibitors by QSAR and Pharmacophore Studies

Ring-substituted 4-Hydroxy-1H-quinolin-2-ones: Preparation and Biological Activity

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Predictive modelling of the LD₅₀ activities of coumarin derivatives using neural statistical approaches: Electronic descriptor-based DFT

Predictive modelling of the LD₅₀ activities of coumarin derivatives using neural statistical approaches: Electronic descriptor-based DFT