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An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions
Protein disordered regions are segments of a protein chain that do not adopt a stable structure. Thus far, a variety of protein disorder prediction methods have been developed and have been widely used, not only in traditional bioinformatics domains, including protein structure prediction, protein s...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4519904/ https://www.ncbi.nlm.nih.gov/pubmed/26198229 http://dx.doi.org/10.3390/ijms160715384 |
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author | Deng, Xin Gumm, Jordan Karki, Suman Eickholt, Jesse Cheng, Jianlin |
author_facet | Deng, Xin Gumm, Jordan Karki, Suman Eickholt, Jesse Cheng, Jianlin |
author_sort | Deng, Xin |
collection | PubMed |
description | Protein disordered regions are segments of a protein chain that do not adopt a stable structure. Thus far, a variety of protein disorder prediction methods have been developed and have been widely used, not only in traditional bioinformatics domains, including protein structure prediction, protein structure determination and function annotation, but also in many other biomedical fields. The relationship between intrinsically-disordered proteins and some human diseases has played a significant role in disorder prediction in disease identification and epidemiological investigations. Disordered proteins can also serve as potential targets for drug discovery with an emphasis on the disordered-to-ordered transition in the disordered binding regions, and this has led to substantial research in drug discovery or design based on protein disordered region prediction. Furthermore, protein disorder prediction has also been applied to healthcare by predicting the disease risk of mutations in patients and studying the mechanistic basis of diseases. As the applications of disorder prediction increase, so too does the need to make quick and accurate predictions. To fill this need, we also present a new approach to predict protein residue disorder using wide sequence windows that is applicable on the genomic scale. |
format | Online Article Text |
id | pubmed-4519904 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-45199042015-08-03 An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions Deng, Xin Gumm, Jordan Karki, Suman Eickholt, Jesse Cheng, Jianlin Int J Mol Sci Article Protein disordered regions are segments of a protein chain that do not adopt a stable structure. Thus far, a variety of protein disorder prediction methods have been developed and have been widely used, not only in traditional bioinformatics domains, including protein structure prediction, protein structure determination and function annotation, but also in many other biomedical fields. The relationship between intrinsically-disordered proteins and some human diseases has played a significant role in disorder prediction in disease identification and epidemiological investigations. Disordered proteins can also serve as potential targets for drug discovery with an emphasis on the disordered-to-ordered transition in the disordered binding regions, and this has led to substantial research in drug discovery or design based on protein disordered region prediction. Furthermore, protein disorder prediction has also been applied to healthcare by predicting the disease risk of mutations in patients and studying the mechanistic basis of diseases. As the applications of disorder prediction increase, so too does the need to make quick and accurate predictions. To fill this need, we also present a new approach to predict protein residue disorder using wide sequence windows that is applicable on the genomic scale. MDPI 2015-07-07 /pmc/articles/PMC4519904/ /pubmed/26198229 http://dx.doi.org/10.3390/ijms160715384 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Deng, Xin Gumm, Jordan Karki, Suman Eickholt, Jesse Cheng, Jianlin An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions |
title | An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions |
title_full | An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions |
title_fullStr | An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions |
title_full_unstemmed | An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions |
title_short | An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions |
title_sort | overview of practical applications of protein disorder prediction and drive for faster, more accurate predictions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4519904/ https://www.ncbi.nlm.nih.gov/pubmed/26198229 http://dx.doi.org/10.3390/ijms160715384 |
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