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Trends in Bioinformatics
  Year: 2016 | Volume: 9 | Issue: 1 | Page No.: 23-29
DOI: 10.3923/tb.2016.23.29
 
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Homology Modeling and Structural Validation of Type 2 Diabetes Associated Transcription Factor 7-like 2 (TCF7L2)

Rajneesh Prajapat , Ijen Bhattacharya and Anoop Kumar

Abstract:
Background: New study findings indicate that variation in the transcription factor 7-like 2 (TCF7L2) gene, linked to the pathogenesis of type 2 diabetes. In the present study, the protein structure model of TCF7L2 was generated, to understand the structure, function and mechanism of the action of proteins. The present study was designed to enlist some of the physiochemical and functional properties of TCF7L2 protein and provides information about its three-dimensional structure. Materials and Methods: The PDB file of TCF7L2 [CAG38811] was generated by Phyre 2 servers. Model construction and regularization (including geometry optimization) of model were done by optimization protocol in YASARA. The energy of the model was minimized using the standard protocols of combined application of simulated annealing, conjugate gradient and steepest descent. The UCLA-DOE server was used to visual analysis of the quality of a putative crystal structure for protein. The validation for structure models was performed by using PROCHECK. The model was further analyzed by WHATIF, QMEAN and ProSA. Results: The model showed good stereo-chemical property in terms of overall G-factor value of -0.64 indicating that geometry of model corresponds to the probability conformation with 67.9% residue in the core region of Ramachandran plot showing high accuracy of model prediction. The Z-score of -6.07 predicted by ProSA represents the good quality of the model. The Z-score also measures the divergence of total energy of the structure with respect to an energy distribution derived from random conformations. The scores indicate a highly reliable structure and are well within the range of scores typically found for proteins of similar size. The energy plot shows the local model quality by plotting knowledge-based energies as a function of amino acid sequence position. Conclusions: The generated model could be supportive to understand the functional characteristics of transcription factor 7-like 2 (TCF7L2). The variants in TCF7L2 associated with the risk for type 2 diabetes.
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How to cite this article:

Rajneesh Prajapat, Ijen Bhattacharya and Anoop Kumar, 2016. Homology Modeling and Structural Validation of Type 2 Diabetes Associated Transcription Factor 7-like 2 (TCF7L2). Trends in Bioinformatics, 9: 23-29.

DOI: 10.3923/tb.2016.23.29

URL: https://scialert.net/abstract/?doi=tb.2016.23.29

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