HORIBALFRE program: Higher Order Residue Interactions Based ALgorithm for Fold REcognition



Pandurangan Sundaramurthy 1, 2, Raashi Sreenivasan 1, 3, 4#, Khader Shameer 1,5#, Sunita Gakkhar 2 & Ramanathan Sowdhamini 1*



1National Center for Biological Sciences, Tata Institute of Fundamental Research, GKVK Campus, Bellary Road, Bangalore - 560065, India; 2Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee -247667, India; 3Centre for Biotechnology, Anna University, Chennai - 600025, India; 4University of Wisconsin-Madison, Madison, WI 53706-1481, USA; 5Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN 55901 USA


Email; *Corresponding author


Article Type




RReceived October 21, 2011; Accepted November 24, 2011; Published December 10, 2011



Understanding the functional and structural implication of a protein encoded in novel genes using function association or fold recognition approaches remains to be a challenging task in the current era of genomes, metagenomes and personal genomes. In an attempt to enhance potential-based fold-recognition methods in recognizing remote homology between proteins, we propose a new approach “Higher Order Residue Interaction Based ALgorithm for Fold REcognition (HORIBALFRE)”. Higher order residue interactions refer to a class of interactions in protein structures mediated by Cα or Cβ atoms within a pre-defined distance cut-off. Higher order residue interactions (pairwise, triplet and quadruplet interactions) play a vital role in attaining the stable conformation of a protein structure. In HORIBALFRE, we incorporated the potential contributions from two body (pairwise) interactions, three body (triplet interactions) and four-body (quadruple interaction) interactions, to implement a new fold recognition algorithm. Core of HORIBALFRE algorithm includes the potentials generated from a library of protein structure derived from manually curated CAMPASS database of structure based sequence alignment. We used Fischer’s dataset, with 68 templates and 56 target sequences, derived from SCOP database and performed one-against-all sequence alignment using TCoffee. Various potentials were derived using custom scripts and these potentials were incorporated in the HORIBALFRE algorithm. In this manuscript, we report outline of a novel fold recognition algorithm and initial results. Our results show that inclusion of quadruplet class of higher order residue interaction improves fold recognition.



fold recognition, fold prediction algorithm, protein folding, residue interactions, higher order residue interactions.



Sundaramurthy et al. Bioinformation 7(7): 352-359 (2011)

Edited by

P Kangueane






Biomedical Informatics



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