Selection of antisense oligonucleotides based on multiple predicted target mRNA structures

<p>Abstract</p> <p>Background</p> <p>Local structures of target mRNAs play a significant role in determining the efficacies of antisense oligonucleotides (ODNs), but some structure-based target site selection methods are limited by uncertainties in RNA secondary structu...

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Main Authors: Yang Jing, Shu Wenjie, Sun Daochun, Lou Shaoke, Bo Xiaochen, Wang Shengqi
Format: Article
Language:English
Published: BMC 2006-03-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/7/122
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author Yang Jing
Shu Wenjie
Sun Daochun
Lou Shaoke
Bo Xiaochen
Wang Shengqi
author_facet Yang Jing
Shu Wenjie
Sun Daochun
Lou Shaoke
Bo Xiaochen
Wang Shengqi
author_sort Yang Jing
collection DOAJ
description <p>Abstract</p> <p>Background</p> <p>Local structures of target mRNAs play a significant role in determining the efficacies of antisense oligonucleotides (ODNs), but some structure-based target site selection methods are limited by uncertainties in RNA secondary structure prediction. If all the predicted structures of a given mRNA within a certain energy limit could be used simultaneously, target site selection would obviously be improved in both reliability and efficiency. In this study, some key problems in ODN target selection on the basis of multiple predicted target mRNA structures are systematically discussed.</p> <p>Results</p> <p>Two methods were considered for merging topologically different RNA structures into integrated representations. Several parameters were derived to characterize local target site structures. Statistical analysis on a dataset with 448 ODNs against 28 different mRNAs revealed 9 features quantitatively associated with efficacy. Features of structural consistency seemed to be more highly correlated with efficacy than indices of the proportion of bases in single-stranded or double-stranded regions. The local structures of the target site 5' and 3' termini were also shown to be important in target selection. Neural network efficacy predictors using these features, defined on integrated structures as inputs, performed well in "minus-one-gene" cross-validation experiments.</p> <p>Conclusion</p> <p>Topologically different target mRNA structures can be merged into integrated representations and then used in computer-aided ODN design. The results of this paper imply that some features characterizing multiple predicted target site structures can be used to predict ODN efficacy.</p>
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spelling doaj.art-cff2a52d914b412bb5c8f6fa53b229a52022-12-21T19:13:15ZengBMCBMC Bioinformatics1471-21052006-03-017112210.1186/1471-2105-7-122Selection of antisense oligonucleotides based on multiple predicted target mRNA structuresYang JingShu WenjieSun DaochunLou ShaokeBo XiaochenWang Shengqi<p>Abstract</p> <p>Background</p> <p>Local structures of target mRNAs play a significant role in determining the efficacies of antisense oligonucleotides (ODNs), but some structure-based target site selection methods are limited by uncertainties in RNA secondary structure prediction. If all the predicted structures of a given mRNA within a certain energy limit could be used simultaneously, target site selection would obviously be improved in both reliability and efficiency. In this study, some key problems in ODN target selection on the basis of multiple predicted target mRNA structures are systematically discussed.</p> <p>Results</p> <p>Two methods were considered for merging topologically different RNA structures into integrated representations. Several parameters were derived to characterize local target site structures. Statistical analysis on a dataset with 448 ODNs against 28 different mRNAs revealed 9 features quantitatively associated with efficacy. Features of structural consistency seemed to be more highly correlated with efficacy than indices of the proportion of bases in single-stranded or double-stranded regions. The local structures of the target site 5' and 3' termini were also shown to be important in target selection. Neural network efficacy predictors using these features, defined on integrated structures as inputs, performed well in "minus-one-gene" cross-validation experiments.</p> <p>Conclusion</p> <p>Topologically different target mRNA structures can be merged into integrated representations and then used in computer-aided ODN design. The results of this paper imply that some features characterizing multiple predicted target site structures can be used to predict ODN efficacy.</p>http://www.biomedcentral.com/1471-2105/7/122
spellingShingle Yang Jing
Shu Wenjie
Sun Daochun
Lou Shaoke
Bo Xiaochen
Wang Shengqi
Selection of antisense oligonucleotides based on multiple predicted target mRNA structures
BMC Bioinformatics
title Selection of antisense oligonucleotides based on multiple predicted target mRNA structures
title_full Selection of antisense oligonucleotides based on multiple predicted target mRNA structures
title_fullStr Selection of antisense oligonucleotides based on multiple predicted target mRNA structures
title_full_unstemmed Selection of antisense oligonucleotides based on multiple predicted target mRNA structures
title_short Selection of antisense oligonucleotides based on multiple predicted target mRNA structures
title_sort selection of antisense oligonucleotides based on multiple predicted target mrna structures
url http://www.biomedcentral.com/1471-2105/7/122
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AT sundaochun selectionofantisenseoligonucleotidesbasedonmultiplepredictedtargetmrnastructures
AT loushaoke selectionofantisenseoligonucleotidesbasedonmultiplepredictedtargetmrnastructures
AT boxiaochen selectionofantisenseoligonucleotidesbasedonmultiplepredictedtargetmrnastructures
AT wangshengqi selectionofantisenseoligonucleotidesbasedonmultiplepredictedtargetmrnastructures