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Title: Assessing the relationship among physicochemical properties of proteins with respect to hydrophobicity: A case study on AGC kinase superfamily
Authors: Banerjee, Amit Kumar
Manasa, B Poorna
Murty, Upadhyayula Suryanarayana
Keywords: CART;AGC Kinase;Hydrophobicity;Data Mining;In Silico;Stochastic method
Issue Date: Dec-2010
Publisher: NISCAIR-CSIR, India
Abstract: Understanding the protein structures is crucial, as it is involved in every cellular activity. Several experimental techniques, such as X-Ray crystallography, nuclear magnetic resonance and electron microscopy are available to gain insight about the structure and function of a protein molecule. Gigantic data on protein structural and sequential information is deposited in various repositories regularly which provide us the scope for more theoretical studies. Hydrophobicity always plays a vital role in tertiary structure formation and behavior of a protein molecule. This study focuses on elucidating influence of several physicochemical properties on hydrophobicity of AGC kinase proteins. AGC kinase superfamily is selected due to its tremendous structural and functional variability and sequence data availability. A combined data mining and stochastic approach confirmed that out of 47 parameters, transmembrane tendency influences the target variable most, followed by percent buried residues, GRAVY (Grand Average Hydropathicity) and aliphatic index. Calculating the influence of different physicochemical parameters and their interrelation will aid tremendously in the future of protein science.
Page(s): 370-377
ISSN: 0975-0959 (Online); 0301-1208 (Print)
Appears in Collections:IJBB Vol.47(6) [December 2010]

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