Molecular modelling studies on <i>d</i>-annulated benzazepinones as VEGF-R2 kinase inhibitors using docking and 3D-QSAR

Lan, Ping; Sun, Jun-Rong; Chen, Wan-Na; Sun, Ping-Hua; Chen, Wei-Min

doi:10.3109/14756366.2010.513331

Cited by 8 publications

(2 citation statements)

References 26 publications

(37 reference statements)

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“…The molecular geometry of each compound was first minimized using the standard Tripos molecular mechanics force field with 0.01 kcal/(mol A) energy gradient convergence criterion. Partial atomic charges were calculated by the Gasteiger-Hückel method and energy minimizations were performed using the Conjugate Gradient method with 1000 iterations [ 36 , 37 ].…”

Section: Methodsmentioning

confidence: 99%

The Discovery of Potentially Selective Human Neuronal Nitric Oxide Synthase (nNOS) Inhibitors: A Combination of Pharmacophore Modelling, CoMFA, Virtual Screening and Molecular Docking Studies

Chen

Shen

et al. 2014

IJMS

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Neuronal nitric oxide synthase (nNOS) plays an important role in neurotransmission and smooth muscle relaxation. Selective inhibition of nNOS over its other isozymes is highly desirable for the treatment of neurodegenerative diseases to avoid undesirable effects. In this study, we present a workflow for the identification and prioritization of compounds as potentially selective human nNOS inhibitors. Three-dimensional pharmacophore models were constructed based on a set of known nNOS inhibitors. The pharmacophore models were evaluated by Pareto surface and CoMFA (Comparative Molecular Field Analysis) analyses. The best pharmacophore model, which included 7 pharmacophore features, was used as a search query in the SPECS database (SPECS®, Delft, The Netherlands). The hit compounds were further filtered by scoring and docking. Ten hits were identified as potential selective nNOS inhibitors.

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Section: Methodsmentioning

confidence: 99%

The Discovery of Potentially Selective Human Neuronal Nitric Oxide Synthase (nNOS) Inhibitors: A Combination of Pharmacophore Modelling, CoMFA, Virtual Screening and Molecular Docking Studies

Chen

Shen

et al. 2014

IJMS

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“…VEGFR-2 is a likely target for computational drug design as small molecule inhibitors have been derived from many molecular scaffolds, including quinazolines [14,15], naphtamides [16], furo [2,3-d]pyrimidines [17], pyridinyltriazines [18], pyrimidinyllindazoles [19], and most recently thieno [3,2-d]pyrimidinones and thieno [1][2][3] triazines [20], offering an expansive data set for design and optimization. Using SciFinder Ò as a representative search tool for the literature, 17 publications were identified which used 3-D QSAR methods to study inhibitors of VEGFR-2 [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37]. Most of these studies built CoMFA/CoMSIA models using SYBYL software [21,22,[28][29][30][31][35][36][37], and all but one simply used these models for pharmacophore modeling and analysis; one study used the 3-D QSAR models as a virtual screening tool to identify novel N-(pyridin-4-ylmethyl)aniline derivates as potential VEGFR-2 inhibitors [37].…”

Section: Introductionmentioning

confidence: 99%

Vascular endothelial growth factor receptor-2 (VEGFR-2) inhibitors: development and validation of predictive 3-D QSAR models through extensive ligand- and structure-based approaches

Ragno

Ballante

Pirolli

et al. 2015

J Comput Aided Mol Des

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Vascular endothelial growth factor receptor-2, (VEGFR-2), is a key element in angiogenesis, the process by which new blood vessels are formed, and is thus an important pharmaceutical target. Here, 3-D quantitative structure-activity relationship (3-D QSAR) were used to build a quantitative screening and pharmacophore model of the VEGFR-2 receptors for design of inhibitors with improved activities. Most of available experimental data information has been used as training set to derive optimized and fully cross-validated eight mono-probe and a multi-probe quantitative models. Notable is the use of 262 molecules, aligned following both structure-based and ligand-based protocols, as external test set confirming the 3-D QSAR models' predictive capability and their usefulness in design new VEGFR-2 inhibitors. From a survey on literature, this is the first generation of a wide-ranging computational medicinal chemistry application on VEGFR2 inhibitors.

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Molecular modelling studies on d-annulated benzazepinones as VEGF-R2 kinase inhibitors using docking and 3D-QSAR

Cited by 8 publications

References 26 publications

The Discovery of Potentially Selective Human Neuronal Nitric Oxide Synthase (nNOS) Inhibitors: A Combination of Pharmacophore Modelling, CoMFA, Virtual Screening and Molecular Docking Studies

The Discovery of Potentially Selective Human Neuronal Nitric Oxide Synthase (nNOS) Inhibitors: A Combination of Pharmacophore Modelling, CoMFA, Virtual Screening and Molecular Docking Studies

Vascular endothelial growth factor receptor-2 (VEGFR-2) inhibitors: development and validation of predictive 3-D QSAR models through extensive ligand- and structure-based approaches

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