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Understanding Mycobacteriophages Through their Unrevealed Proteins


Affiliations
1 Ecosystem Division, National Environmental Engineering Research Institute (NEERI), Nehru Marg, Nagpur-440020, Maharashtra, India
     

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The Mycobacteriophages are the bacteriophages infecting different Mycobacterium species in nature. The hypothetical proteins in 17 different Mycobacteriophages were structurally and functionally characterized by using computational tools like CDD-Blast, Interproscan, pfam, COGS and protein structure prediction server (PS2 server). Near about 2188 hypothetical proteins were screened for presence of functional domains and structural classification. The function predictions for 586 hypothetical proteins and structure predictions for 171 hypothetical proteins were possible by using these Bioinformatics web tools. These results can prove helpful for proper understanding of functional, evolutionary and metabolic development of Mycobacterium species.

Keywords

Mycobacterium Species, Hypothetical Proteins, Bioinformatics Web Tools, Evolutionary and Metabolic Development.
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  • Understanding Mycobacteriophages Through their Unrevealed Proteins

Abstract Views: 231  |  PDF Views: 3

Authors

Swapnil G. Sanmukh
Ecosystem Division, National Environmental Engineering Research Institute (NEERI), Nehru Marg, Nagpur-440020, Maharashtra, India
Waman N. Paunikar
Ecosystem Division, National Environmental Engineering Research Institute (NEERI), Nehru Marg, Nagpur-440020, Maharashtra, India

Abstract


The Mycobacteriophages are the bacteriophages infecting different Mycobacterium species in nature. The hypothetical proteins in 17 different Mycobacteriophages were structurally and functionally characterized by using computational tools like CDD-Blast, Interproscan, pfam, COGS and protein structure prediction server (PS2 server). Near about 2188 hypothetical proteins were screened for presence of functional domains and structural classification. The function predictions for 586 hypothetical proteins and structure predictions for 171 hypothetical proteins were possible by using these Bioinformatics web tools. These results can prove helpful for proper understanding of functional, evolutionary and metabolic development of Mycobacterium species.

Keywords


Mycobacterium Species, Hypothetical Proteins, Bioinformatics Web Tools, Evolutionary and Metabolic Development.