In silico characterization of antifreeze proteins using computational tools and servers |
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Authors: | K Sivakumar S Balaji and Gangaradhakrishnan |
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Institution: | (1) Department of Chemistry, Sri Chandrasekharendra Saraswathi Viswa Maha Vidyalaya (Deemed University), Enathur, Kanchipuram, 631 561, India;(2) EXCEL and Polymer Science Labs, Central Leather Research Institute, Adyar, Chennai, 600 020, India |
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Abstract: | In this paper, seventeen different fish Antifreeze Proteins (AFPs) retrieved from Swiss-Prot database are analysed and characterized
using in silico tools. Primary structure analysis shows that most of the AFPs are hydrophobic in nature due to the high content of non-polar
residues. The presence of 11 cysteines in the rainbow smelt fish and sea raven fish AFPs infer that these proteins may form
disulphide (SS) bonds, which are regarded as a positive factor for stability. The aliphatic index computed by Ex-Pasy’s ProtParam
infers that AFPs may be stable for a wide range of temperature. Secondary structure analysis shows that most of the fish AFPs
have predominant α-helical structures and rest of the AFPs have mixed secondary structure. The very high coil structural content
of rainbow smelt fish and sea raven fish AFPs are due to the rich content of more flexible glycine and hydrophobic proline
amino acids. Proline has a special property of creating kinks in polypetide chains and disrupting ordered secondary structure.
SOSUI server predicts one transmembrane region in winter flounder fish and atlantic cod and two transmembrane regions in yellowtail
flounder fish AFP. The predicted transmembrane regions were visualized and analysed using helical wheel plots generated by
EMBOSS pepwheel tool. The presence of disulphide (SS) bonds in the AFPs Q01758 and P05140 are predicted by CYS_REC tool and
also identified from the three-dimensional structure using Rasmol tool. The disulphide bonds identified from the three-dimensional
structure using the Rasmol tool might be correct as the evaluation parameters are within the acceptable limits for the modelled
3D structures. |
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Keywords: | Antifreeze proteins computational analysis disulphide bridges homology modelling proteomics tools |
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