Atom-based 3D QSAR studies on novel N-β-d-xylosylindole derivatives as SGLT2 inhibitors

Venkatesan, S.; Sudha, A.; Rajamanikandan, Sundararaj; Vanajothi, Ramar; Srinivasan, Pappu

doi:10.1007/s00044-012-0053-7

Cited by 14 publications

(2 citation statements)

References 15 publications

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“…Homology modeling, molecular docking were administered on 54 C-aryl glycosides analogues, providing fundamental structural insights into the active site and key interactions involved in the binding of inhibitors to hSGLT2 [8] . 3D pharmacophore models and atom-based 3D-QSAR models have inhibitors [9] . Optimization of Gaussian Kernel Function in Support Vector Machine…”

Section: Introductionmentioning

confidence: 99%

QSAR studies on triazole derivatives as sglt inhibitors via CoMFA and CoMSIA

Zhi

Zheng

Chang

et al. 2015

Journal of Molecular Structure

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Section: Introductionmentioning

confidence: 99%

QSAR studies on triazole derivatives as sglt inhibitors via CoMFA and CoMSIA

Zhi

Zheng

Chang

et al. 2015

Journal of Molecular Structure

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“…Most of the currently reported SGLT2 inhibitors are glucoside derivatives and are based on phlorizin (i.e., a naturallyoccurring O-aryl glycoside) [1]. Some quantitative structure-activity relationship (QSAR) models have been developed for glycoside molecules [2][3][4][5]. However, some SGLT2 inhibitors (dapagliflozin, canagliflozin, and empagliflozin are glucosides derived from the prototype phlorizin [6,7]) in clinical development inhibit only 30-50% of glucose reabsorption [8].…”

Section: Introductionmentioning

confidence: 99%

Predicting the biological activities of triazole derivatives as SGLT2 inhibitors using multilayer perceptron neural network, support vector machine, and projection pursuit regression models

Yuan

Gao

et al. 2016

Chemometrics and Intelligent Laboratory Systems

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Quantitative structure-activity relationship (QSAR) studies were performed in this work to predict the pIC 50 of non-glycoside sodium-dependent glucose cotransporter-2 (SGLT2) inhibitors (46 triazole derivatives). Four descriptors were selected from the pool of DRAGON descriptors using the enhanced replacement method. Three nonlinear regression methods-multilayer perceptron neural network (MLP NN), support vector machine (SVM), and projection pursuit regression (PPR)-were then used to build the QSAR models. The performance of the obtained models was assessed through the cross-validation and external validation of the test set. PPR produced a better model than MLP NN and SVM with coefficients of determination of 0.962 and 0.871 and root mean square errors of 0.162 and 0.471 for the training and test sets, respectively. This study developed simple and efficient approaches to predict the pIC 50 of triazole derivatives and provided some insights into their structural features for the development of more potential SGLT2 inhibitors.

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Involvement of Cholinergic and Cyclooxygenase Pathways in the Diuretic Effects of Rosmarinic Acid

Felício Macarini,

Bolda Mariano,

de Cássia Vilhena da Silva

et al. 2024

Chemistry & Biodiversity

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Rosmarinic acid (RA) is a natural antioxidant known for its diverse biological activities. Although its diuretic activity has been previously established, the mode of action remained unclear. To investigate this, we examined the diuretic activity of RA alone and in combination with hydrochlorothiazide (HCTZ), amiloride (AML), atropine (ATR), and indomethacin (INDO) to see if any of these drugs could interfere with RA's activity in an 8‐hour acute diuresis animal model. We observed that RA increases urine excretion and may have a synergistic effect in the HCTZ+RA group, with a potassium‐sparing capacity. In the AML+RA group, we also noted increased urine excretion while sodium and potassium excretion decreased. ATR and INDO prevented RA from increasing urine excretion, suggesting a potential interaction with muscarinic receptors or a role in promoting prostaglandin production. Additionally, molecular docking analysis indicated possible interactions with key receptors involved in increased diuresis or free‐electrolyte water excretion.

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Atom-based 3D QSAR studies on novel N-β-d-xylosylindole derivatives as SGLT2 inhibitors

Cited by 14 publications

References 15 publications

QSAR studies on triazole derivatives as sglt inhibitors via CoMFA and CoMSIA

QSAR studies on triazole derivatives as sglt inhibitors via CoMFA and CoMSIA

Predicting the biological activities of triazole derivatives as SGLT2 inhibitors using multilayer perceptron neural network, support vector machine, and projection pursuit regression models

Involvement of Cholinergic and Cyclooxygenase Pathways in the Diuretic Effects of Rosmarinic Acid

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