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Trends in Bioinformatics
  Year: 2020 | Volume: 13 | Issue: 1 | Page No.: 10-17
DOI: 10.3923/tb.2020.10.17
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Study on Role of Homology in Prediction of Protein Structure and Challenges of Homology
Bhaludra Chandra Sekhar Singh

Background and Objective: Homology modeling assumes a focal job in deciding protein structure in the basic genomics venture refers to modeling of the 3D structure of a protein by exploiting structural information from the known configurations of similar proteins. The docking studies are the inclusion of receptor flexibility is an important role because of the major consequences on molecular recognition binding sites of many therapeutic targets sample, which has a wide range of conformational states to make use of very large sets of X-ray structures and to assess the execution of flexible receptor docking in binding-mode prediction virtual screening experiments. To analyze the homology modeling of a protein 3D structure, this is helpful to design a drug. Materials and Methods: The homology model is evaluated based on a template for identification, alignments for single or multiple sequences, target 3D structure, model refinement and model validation. The on-going advances in homology modeling that improve the accuracy of modeling results especially in recognizing and adjusting successions to layout structures, far off homologs, modeling of loops and side chains just as identifying mistakes in a model added to the reliable forecast of protein structure. Results: A model is said to be legitimate just when a couple of mutilations in nuclear contacts are available. The Ramachandran plot is presumably the most dominant determinant of the nature of the protein. Conclusion: Protein structure prediction has been a fantasy for an academic network for decades, for computational scientific experts, yet also for physicist, mathematician and PC researcher.
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How to cite this article:

Bhaludra Chandra Sekhar Singh , 2020. Study on Role of Homology in Prediction of Protein Structure and Challenges of Homology. Trends in Bioinformatics, 13: 10-17.

DOI: 10.3923/tb.2020.10.17








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