3D QSAR studies of synthetic compounds as potential inhibitors for Anti - hyperglycemic targets.

Dr. R. Balajee Ramachandran, Dr. M. S. Dhanarajan M S



Background: The identification of potential compounds for an anti-hyperglycemic makes real challenges in the pharmaceutical industry. Library of
compounds have introduced so far, but identifying the specific target, which makes more sensation.
Objective: In the present study, the quantitative structure-activity relationship (QSAR) studies have been analyzed from the compounds were
retrieved from online and literature survey.
Methods: The compound, 6, 7, 8, 9-tetrahydro-2h-11-oxa-2, 4, 10-triaza-benzo [b] fluoren-1-one has taken as a potential target to perform QSAR
study based on the principle of the molecular docking analysis and pharmacophoric features. QSAR models were generated a target from the first 10
potential targets in the training set.
Results: The predictive ability of both models was determined using a randomly chosen test set gave predictive correlation coefficients of r2=0.9.
Conclusion: This analysis shows the ADNRR shows very close to the interactions recorded in the active site of the ligand bound complex.
Keywords: Quantitative structure-activity relationship, Pharmacophore Alignment and Scoring Engine, Dipeptidyl peptidase 4, Anti-hyperglycemic
targets, Docking studies, Three dimensional quantitative structure-activity relationship.

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Andriole VT. Current and future antifungal therapy: New targets for antifungal therapy. Int J Antimicrob Agents 2000;16(3):317-21.

Tan YT, Tillett DJ, McKay IA. Molecular strategies for overcoming antibiotic resistance in bacteria. Mol Med Today 2000;6(8):309-14.

Dixon SL, Smondyrev AM, Rao SN. PHASE: A novel approach to pharmacophore modeling and 3D database searching. Chem Biol Drug Des 2006;67(5):370-2.

Balajee R, Dhanarajan MS. Identification and comparative molecular docking analysis of 6, 7, 8, 9-Tetrahydro-2H-11-oxa-2, 4, 10-triaza-benzo[B] fluoren-1-one (RBMS-01) bounds with DPP4 for anti-hyperglycemic activities. Chem Sci Trans 2012;1:279-88.

Balajee R, Dhanarajan MS. Comparative study of inhibition of drug potencies of tyrosine kinase inhibitors: A computational and molecular docking study. Asian J Pharm Clin Res 2012;5:104-8.

Dixon SL, Smondyrev AM, Knoll EH, Rao SN, Shaw DE, Friesner RA. PHASE: A new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results. J Comput Aided Mol Des 2006;20(10-11):647-71.

Thomsen R, Chirstensen MH. A new tequnique for high-accuracy molecular docking. J Med Chem 2006;49(11):3315-21.

Shah UA, Deokar HS, Kadam SS, Kulkarni VM. Pharmacophore generation and atom-based 3D-QSAR of novel 2-(4-methylsulfonylphenyl) pyrimidines as COX-2 inhibitors. Mol Divers 2010;14(3):559-68.

Murumkar PR, Zambre VP, Yadav MR. Development of predictive pharmacophore model for in silico screening, and 3D QSAR CoMFA and CoMSIA studies for lead optimization, for designing of potent tumor necrosis factor alpha converting enzyme inhibitors. J Comput Aided Mol Des 2010;24(2):143-56.

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3D QSAR studies of synthetic compounds as potential inhibitors for Anti - hyperglycemic targets.



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Asian Journal of Pharmaceutical and Clinical Research
Vol 8 Issue 1 (January-February) 2015 Page: 362-364

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Authors & Affiliations

Dr. R. Balajee Ramachandran
1 Asst. Professor, Department of Bioinformatics, FSH, SRM University, Kattankulathur

Dr. M. S. Dhanarajan M S
2 Principal Jaya college of Arts and Science, Thiruninrvur, Tamil Nadu, India

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