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iCTX-Type: A Sequence-Based Predictor for Identifying the Types of Conotoxins in Targeting Ion Channels
Conotoxins are small disulfide-rich neurotoxic peptides, which can bind to ion channels with very high specificity and modulate their activities. Over the last few decades, conotoxins have been the drug candidates for treating chronic pain, epilepsy, spasticity, and cardiovascular diseases. Accordin...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4058692/ https://www.ncbi.nlm.nih.gov/pubmed/24991545 http://dx.doi.org/10.1155/2014/286419 |
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author | Ding, Hui Deng, En-Ze Yuan, Lu-Feng Liu, Li Lin, Hao Chen, Wei Chou, Kuo-Chen |
author_facet | Ding, Hui Deng, En-Ze Yuan, Lu-Feng Liu, Li Lin, Hao Chen, Wei Chou, Kuo-Chen |
author_sort | Ding, Hui |
collection | PubMed |
description | Conotoxins are small disulfide-rich neurotoxic peptides, which can bind to ion channels with very high specificity and modulate their activities. Over the last few decades, conotoxins have been the drug candidates for treating chronic pain, epilepsy, spasticity, and cardiovascular diseases. According to their functions and targets, conotoxins are generally categorized into three types: potassium-channel type, sodium-channel type, and calcium-channel types. With the avalanche of peptide sequences generated in the postgenomic age, it is urgent and challenging to develop an automated method for rapidly and accurately identifying the types of conotoxins based on their sequence information alone. To address this challenge, a new predictor, called iCTX-Type, was developed by incorporating the dipeptide occurrence frequencies of a conotoxin sequence into a 400-D (dimensional) general pseudoamino acid composition, followed by the feature optimization procedure to reduce the sample representation from 400-D to 50-D vector. The overall success rate achieved by iCTX-Type via a rigorous cross-validation was over 91%, outperforming its counterpart (RBF network). Besides, iCTX-Type is so far the only predictor in this area with its web-server available, and hence is particularly useful for most experimental scientists to get their desired results without the need to follow the complicated mathematics involved. |
format | Online Article Text |
id | pubmed-4058692 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-40586922014-07-02 iCTX-Type: A Sequence-Based Predictor for Identifying the Types of Conotoxins in Targeting Ion Channels Ding, Hui Deng, En-Ze Yuan, Lu-Feng Liu, Li Lin, Hao Chen, Wei Chou, Kuo-Chen Biomed Res Int Research Article Conotoxins are small disulfide-rich neurotoxic peptides, which can bind to ion channels with very high specificity and modulate their activities. Over the last few decades, conotoxins have been the drug candidates for treating chronic pain, epilepsy, spasticity, and cardiovascular diseases. According to their functions and targets, conotoxins are generally categorized into three types: potassium-channel type, sodium-channel type, and calcium-channel types. With the avalanche of peptide sequences generated in the postgenomic age, it is urgent and challenging to develop an automated method for rapidly and accurately identifying the types of conotoxins based on their sequence information alone. To address this challenge, a new predictor, called iCTX-Type, was developed by incorporating the dipeptide occurrence frequencies of a conotoxin sequence into a 400-D (dimensional) general pseudoamino acid composition, followed by the feature optimization procedure to reduce the sample representation from 400-D to 50-D vector. The overall success rate achieved by iCTX-Type via a rigorous cross-validation was over 91%, outperforming its counterpart (RBF network). Besides, iCTX-Type is so far the only predictor in this area with its web-server available, and hence is particularly useful for most experimental scientists to get their desired results without the need to follow the complicated mathematics involved. Hindawi Publishing Corporation 2014 2014-06-01 /pmc/articles/PMC4058692/ /pubmed/24991545 http://dx.doi.org/10.1155/2014/286419 Text en Copyright © 2014 Hui Ding et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Ding, Hui Deng, En-Ze Yuan, Lu-Feng Liu, Li Lin, Hao Chen, Wei Chou, Kuo-Chen iCTX-Type: A Sequence-Based Predictor for Identifying the Types of Conotoxins in Targeting Ion Channels |
title | iCTX-Type: A Sequence-Based Predictor for Identifying the Types of Conotoxins in Targeting Ion Channels |
title_full | iCTX-Type: A Sequence-Based Predictor for Identifying the Types of Conotoxins in Targeting Ion Channels |
title_fullStr | iCTX-Type: A Sequence-Based Predictor for Identifying the Types of Conotoxins in Targeting Ion Channels |
title_full_unstemmed | iCTX-Type: A Sequence-Based Predictor for Identifying the Types of Conotoxins in Targeting Ion Channels |
title_short | iCTX-Type: A Sequence-Based Predictor for Identifying the Types of Conotoxins in Targeting Ion Channels |
title_sort | ictx-type: a sequence-based predictor for identifying the types of conotoxins in targeting ion channels |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4058692/ https://www.ncbi.nlm.nih.gov/pubmed/24991545 http://dx.doi.org/10.1155/2014/286419 |
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