Title

A decision tree model for the prediction of homodimer folding mechanism

Authors

Abishek Suresh^{1, 2}, Velmurugan Karthikraja¹, Sajitha Lulu¹, Uma Kangueane¹, Pandjassarame Kangueane^{1, 2,*}

Affiliation

¹Biomedical Informatics, Pondicherry 607402, ²AIMST University, Semeling 08100, Malaysia

Email

kangueane@bioinformation.net

Article Type

Hypothesis

Date

Received October 20, 2009; Accepted November 09, 2009; Published November 17, 2009

Abstract

The formation of protein homodimer complexes for molecular catalysis and regulation is fascinating. The homodimer formation through 2S (2 state), 3SMI (3 state with monomer intermediate) and 3SDI (3 state with dimer intermediate) folding mechanism is known for 47 homodimer structures. Our dataset of forty-seven homodimers consists of twenty-eight 2S, twelve 3SMI and seven 3SDI. The dataset is characterized using monomer length, interface area and interface/total (I/T) residue ratio. It is found that 2S are often small in size with large I/T ratio and 3SDI are frequently large in size with small I/T ratio. Nonetheless, 3SMI have a mixture of these features. Hence, we used these parameters to develop a decision tree model. The decision tree model produced positive predictive values (PPV) of 72% for 2S, 58% for 3SMI and 57% for 3SDI in cross validation. Thus, the method finds application in assigning homodimers with folding mechanism.
 

Keywords

 folding, homodimer, decision tree, prediction, mechanism

Citation

Suresh et al., Bioinformation 4(5): 197-205 (2009)

Edited by

P. Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

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.