3D-QSAR CoMFA study on indenopyrazole derivatives as cyclin dependent kinase 4 (CDK4) and cyclin dependent kinase 2 (CDK2) inhibitors

Singh, Sanjeev Kumar; Dessalew, Nigus; Bharatam, Prasad V.

doi:10.1016/j.ejmech.2006.06.010

Cited by 43 publications

(21 citation statements)

References 25 publications

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“…Molecular structures are described with molecular interaction energies as steric and electrostatic fields surrounding the molecules; the statistics is computed by partial least square (PLS) regression analysis and the output is displayed as contours superimposed on the molecules. The comparative MFA, (CoMFA) methodology assumes that a suitable sampling of steric and electrostatic fields around a set of aligned molecules provides all the information necessary for understanding their biological properties 72. If no structural information is available, an alternative means to assess potential interactions is to use pharmacophore models.…”

Section: In Silico Ladmetmentioning

confidence: 99%

“…Dipeptide carrier145, 146 and P‐glycoprotein147, 148 (P‐gp) are some of the transporters expressed in Caco‐2 cells. Other cell lines are extensively used due to their low intrinsic expression of ATP‐binding cassette transporters superfamily149–151 (ABC) such us Madin–Darby Canine Kidney (MDCK) and LLC‐PK1 which make them ideal for transfections 72, 152–154. Another cell line that is being routinely used is 2/4/A1 which lacks functional expression of several important active drug transporters and does not present tight junctions, rendering this system ideal for studying paracellular permeability 142…”

Section: In Vitro Ladmetmentioning

confidence: 99%

See 1 more Smart Citation

Pharmacokinetics in Drug Discovery

Ruiz-Garcı́a

Bermejo

Moss

et al. 2008

Journal of Pharmaceutical Sciences

150

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Section: In Silico Ladmetmentioning

confidence: 99%

Section: In Vitro Ladmetmentioning

confidence: 99%

Pharmacokinetics in Drug Discovery

Ruiz-Garcı́a

Bermejo

Moss

et al. 2008

Journal of Pharmaceutical Sciences

150

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“…Quantitative Structure Activity Relationship (QSAR) studies have been investigated based on the fact that the biological activity of the compound is a function of its physicochemical properties. From literature it was observed that several attempts were made to build QSAR models of various CDK2 inhibitors such as indenopyrazoles [30], oxindoles [31 -32], bisarylmaleimide [33], 3-aminopyrazoles [34], aminothiazoles [35], and purine analogs [36 -37]. Moreover, none of the QSAR studies were reported on structures that covered two or more different kinds of ligands.…”

Section: Introductionmentioning

confidence: 98%

Identification of Novel CDK2 Inhibitors by QSAR and Virtual Screening Procedures

Babu

Smiles²,

Narasu

et al. 2008

QSAR Comb. Sci.

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Quantitative Structure -Activity Relationship (QSAR) studies were carried out on a set of 46 imidazo[1,2-a]pyridines, imidazo[1,2-b]pyridazines and 2,4-bis anilino pyrimidines, and nitroso-6-aminopyrimidine and 2,6-diaminopyrimidine inhibitors of CDK2 (Cyclin-dependent Kinase2) using a multiple regression procedure. The activity contributions of these compounds were determined from regression equation and the validation procedures such as external set cross-validation r 2 , (R 2 cv,ext ) and the regression of observed activities against predicted activities and vice versa for validation set were described to analyze the predictive ability of the QSAR model. An accurate and reliable QSAR model involving five descriptors was chosen based on the FIT Kubinyi function which defines the statistical quality of the model. The proposed model due to its high predictive ability was utilized to screen similar repertoire of compounds reported in the literature, and the biological activities are estimated. The screening study clearly demonstrated that the strategy presented shall be used as an alternative to the time-consuming experiments as the model tolerated a variety of structural modifications signifying its potential for drug design studies.

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“…3D-QSAR and docking approaches have emerged as one of the most powerful tools in ligand based drug design strategies [11,12]. They have been used to develop efficient models for identifying CDK2/cyclin A inhibitors [13,14]. …”

Section: Introductionmentioning

confidence: 99%

Molecular Modeling Studies of 4,5-Dihydro-1H-pyrazolo[4,3-h] quinazoline Derivatives as Potent CDK2/Cyclin A Inhibitors Using 3D-QSAR and Docking

Wang

Sun

et al. 2010

IJMS

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CDK2/cyclin A has appeared as an attractive drug targets over the years with diverse therapeutic potentials. A computational strategy based on comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) followed by molecular docking studies were performed on a series of 4,5-dihydro-1H-pyrazolo[4,3-h]quinazoline derivatives as potent CDK2/cyclin A inhibitors. The CoMFA and CoMSIA models, using 38 molecules in the training set, gave r2cv values of 0.747 and 0.518 and r2 values of 0.970 and 0.934, respectively. 3D contour maps generated by the CoMFA and CoMSIA models were used to identify the key structural requirements responsible for the biological activity. Molecular docking was applied to explore the binding mode between the ligands and the receptor. The information obtained from molecular modeling studies may be helpful to design novel inhibitors of CDK2/cyclin A with desired activity.

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3D-QSAR CoMFA study on indenopyrazole derivatives as cyclin dependent kinase 4 (CDK4) and cyclin dependent kinase 2 (CDK2) inhibitors

Cited by 43 publications

References 25 publications

Pharmacokinetics in Drug Discovery

Pharmacokinetics in Drug Discovery

Identification of Novel CDK2 Inhibitors by QSAR and Virtual Screening Procedures

Molecular Modeling Studies of 4,5-Dihydro-1H-pyrazolo[4,3-h] quinazoline Derivatives as Potent CDK2/Cyclin A Inhibitors Using 3D-QSAR and Docking

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