creators_name: Kaur, Harpreet
creators_name: Raghava, G.P.S.
type: article
datestamp: 2012-01-09 04:23:27
lastmod: 2012-01-09 04:23:27
metadata_visibility: show
title: Prediction of C alpha-H...O and C alpha-H...pi interactions in proteins using recurrent neural network.
ispublished: pub
subjects: QR
full_text_status: public
keywords: weak hydrogen bonds, donor, acceptor, prediction, neural network, secondary structure 
note: OPEN ACCESS
abstract: In this study, an attempt has been made to develop a method for predicting weak hydrogen bonding interactions, namely, C alpha-H...O and C alpha-H...pi interactions in proteins using artificial neural network. Both standard feed-forward neural network (FNN) and recurrent neural networks (RNN) have been trained and tested using five-fold cross-validation on a non-homologous dataset of 2298 protein chains where no pair of sequences has more than 25% sequence identity. It has been found that the prediction accuracy varies with the separation distance between donor and acceptor residues. The maximum sensitivity achieved with RNN for C alpha-H...O is 51.2% when donor and acceptor residues are four residues apart (i.e. at delta D-A = 4) and for C alpha-H...pi is 82.1% at delta D-A = 3. The performance of RNN is increased by 1-3% for both types of interactions when PSIPRED predicted protein secondary structure is used. Overall, RNN performs better than feed-forward networks at all separation distances between donor-acceptor pair for both types of interactions. Based on the observations, a web server CHpredict (available at http://www.imtech.res.in/raghava/chpredict/) has been developed for predicting donor and acceptor residues in C alpha-H...O and C alpha-H...pi interactions in proteins.
date: 2006
date_type: published
publication: In silico biology
volume: 6
number: 1-2
publisher: Bioinformation Systems e.V.
pagerange: 111-25
refereed: TRUE
issn: 1386-6338
official_url: http://www.bioinfo.de/isb/2006060011/
related_url_url: http://www.imtech.res.in/raghava/chpredict
related_url_type: author
citation:   Kaur, Harpreet and Raghava, G.P.S.  (2006) Prediction of C alpha-H...O and C alpha-H...pi interactions in proteins using recurrent neural network.  In silico biology, 6 (1-2).  pp. 111-25.  ISSN 1386-6338     
document_url: http://crdd.osdd.net/open/148/1/raghava2006.mht