Exploring the Interplay of Sequence and Structural Features in Determining the Flexibility of AGC Kinase Protein Family : A Bioinformatics Approach
Amit Kumar Banerjee, Neelima Arora, Varakantham Pranitha, U.S.N.Murty*
Bioinformatics Group, Biology Division, Indian Institute of Chemical Technology, Hyderabad-500607, A.P., India.
- *Corresponding Author:
- Dr. U.S.N Murty
Deputy Director/ Scientist “F” Head
Biology Division, Indian Institute of Chemcal Technology
Hyderabad- 500607, India
Tel : +91 40 27193134
Fax : +91 40 27193227
E-mail: [email protected]
Received Date: May 02, 2008; Accepted Date: May 15, 2008; Published Date: May 20, 2008
Citation: Amit KB, Neelima A, Varakantham P, Murty USN (2008) Exploring the Interplay of Sequence and Structural Features in Determining the Flexibility of AGC Kinase Protein Family : A Bioinformatics Approach. J Proteomics Bioinform 1:077-089. doi:10.4172/jpb.1000013
Copyright: © 2008 Amit KB, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
In this study, data mining approach was used to generate association rules for predicting average flexibility from the various derived sequence and structural features. 21 parameters were calculated and their variable importance was calculated for 115 sequences of AGC kinase family belonging to mouse and human using Classification and Regression Tree (CART). Beta turns were found to have maximum influence on average flexibility while the total beta strands were found to exert minimum impact on average flexibility. Understanding the variable importance will prove useful as a simple pr edictor of flexibility from an amino acid sequence. This will aid in better understanding of phenomenon underlying the average flexibility and thus, will pave a way for rational design of therapeutics.