Title |
Computational analysis of bovine alpha-1 collagen sequences |
Authors |
Ayan Saha, Md. Jibran Alam, Kutub Uddin Muhammad Ashraf & Adnan Mannan* |
Affiliation |
Department of Genetic Engineering and Biotechnology, Faculty of Biological Sciences, University of Chittagong, Chittagong-4331, Bangladesh.
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adnan_orko@yahoo.com; *Corresponding author
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Article Type |
Hypothesis
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Date |
Received December 04, 2012; Accepted December 31, 2012; Published January 09, 2013 |
Abstract |
Bovine collagen alpha-1 is a naturally occurring extracellular matrix protein found in tendons and other connective tissues. It plays a vital role in cell growth, differentiation, attachment, and migration. Recent findings have established that collagen alpha-1 is involved in osteogenesis imperfecta phenotype in cattle but deep information about other members of this large family is not available so far. So with a view to finding a new edge and attempt to figure out a correlation among the well attributed Bovine alpha-1 collagen sequences are executed and analyzed. To do so, comparative analysis among the 28 members of collagen family has been carried out using Computational tools. Consequently, based on the physico-chemical, secondary structural, functional and phylogenetic classifications, we have selected collagen 12, 14 and 20 as targets for pathological conditions. These proteins belong to the FACIT family and significantly showed low glycine and proline content, high instability and aliphatic index. Moreover, FACIT family collagens contain multiple triple helical domains and being members of the FACIT family, bovine collagen 12, 14, 20 do not form fibrils by themselves but they are associated to collagen 1 associated fibrils. These collagen molecules might be crucial candidates to detect and understand the process of matrix remodeling in diseases especially in the arena of cellular compartments.
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Keywords |
Collagen, Extracellular matrix, computational tools.
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Citation |
Saha et al.
Bioinformation 9(1): 042-048 (2013) |
Edited by |
P Kangueane
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ISSN |
0973-2063
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Publisher |
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License |
This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License. |