Cargando…
Evaluation of function predictions by PFP, ESG, and PSI-BLAST for moonlighting proteins
BACKGROUND: Advancements in function prediction algorithms are enabling large scale computational annotation for newly sequenced genomes. With the increase in the number of functionally well characterized proteins it has been observed that there are many proteins involved in more than one function....
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3504920/ https://www.ncbi.nlm.nih.gov/pubmed/23173871 http://dx.doi.org/10.1186/1753-6561-6-S7-S5 |
_version_ | 1782250702625570816 |
---|---|
author | Khan, Ishita K Chitale, Meghana Rayon, Catherine Kihara, Daisuke |
author_facet | Khan, Ishita K Chitale, Meghana Rayon, Catherine Kihara, Daisuke |
author_sort | Khan, Ishita K |
collection | PubMed |
description | BACKGROUND: Advancements in function prediction algorithms are enabling large scale computational annotation for newly sequenced genomes. With the increase in the number of functionally well characterized proteins it has been observed that there are many proteins involved in more than one function. These proteins characterized as moonlighting proteins show varied functional behavior depending on the cell type, localization in the cell, oligomerization, multiple binding sites, etc. The functional diversity shown by moonlighting proteins may have significant impact on the traditional sequence based function prediction methods. Here we investigate how well diverse functions of moonlighting proteins can be predicted by some existing function prediction methods. RESULTS: We have analyzed the performances of three major sequence based function prediction methods, PSI-BLAST, the Protein Function Prediction (PFP), and the Extended Similarity Group (ESG) on predicting diverse functions of moonlighting proteins. In predicting discrete functions of a set of 19 experimentally identified moonlighting proteins, PFP showed overall highest recall among the three methods. Although ESG showed the highest precision, its recall was lower than PSI-BLAST. Recall by PSI-BLAST greatly improved when BLOSUM45 was used instead of BLOSUM62. CONCLUSION: We have analyzed the performances of PFP, ESG, and PSI-BLAST in predicting the functional diversity of moonlighting proteins. PFP shows overall better performance in predicting diverse moonlighting functions as compared with PSI-BLAST and ESG. Recall by PSI-BLAST greatly improved when BLOSUM45 was used. This analysis indicates that considering weakly similar sequences in prediction enhances the performance of sequence based AFP methods in predicting functional diversity of moonlighting proteins. The current study will also motivate development of novel computational frameworks for automatic identification of such proteins. |
format | Online Article Text |
id | pubmed-3504920 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-35049202012-11-29 Evaluation of function predictions by PFP, ESG, and PSI-BLAST for moonlighting proteins Khan, Ishita K Chitale, Meghana Rayon, Catherine Kihara, Daisuke BMC Proc Proceedings BACKGROUND: Advancements in function prediction algorithms are enabling large scale computational annotation for newly sequenced genomes. With the increase in the number of functionally well characterized proteins it has been observed that there are many proteins involved in more than one function. These proteins characterized as moonlighting proteins show varied functional behavior depending on the cell type, localization in the cell, oligomerization, multiple binding sites, etc. The functional diversity shown by moonlighting proteins may have significant impact on the traditional sequence based function prediction methods. Here we investigate how well diverse functions of moonlighting proteins can be predicted by some existing function prediction methods. RESULTS: We have analyzed the performances of three major sequence based function prediction methods, PSI-BLAST, the Protein Function Prediction (PFP), and the Extended Similarity Group (ESG) on predicting diverse functions of moonlighting proteins. In predicting discrete functions of a set of 19 experimentally identified moonlighting proteins, PFP showed overall highest recall among the three methods. Although ESG showed the highest precision, its recall was lower than PSI-BLAST. Recall by PSI-BLAST greatly improved when BLOSUM45 was used instead of BLOSUM62. CONCLUSION: We have analyzed the performances of PFP, ESG, and PSI-BLAST in predicting the functional diversity of moonlighting proteins. PFP shows overall better performance in predicting diverse moonlighting functions as compared with PSI-BLAST and ESG. Recall by PSI-BLAST greatly improved when BLOSUM45 was used. This analysis indicates that considering weakly similar sequences in prediction enhances the performance of sequence based AFP methods in predicting functional diversity of moonlighting proteins. The current study will also motivate development of novel computational frameworks for automatic identification of such proteins. BioMed Central 2012-11-13 /pmc/articles/PMC3504920/ /pubmed/23173871 http://dx.doi.org/10.1186/1753-6561-6-S7-S5 Text en Copyright ©2012 Khan et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Proceedings Khan, Ishita K Chitale, Meghana Rayon, Catherine Kihara, Daisuke Evaluation of function predictions by PFP, ESG, and PSI-BLAST for moonlighting proteins |
title | Evaluation of function predictions by PFP, ESG, and PSI-BLAST for moonlighting proteins |
title_full | Evaluation of function predictions by PFP, ESG, and PSI-BLAST for moonlighting proteins |
title_fullStr | Evaluation of function predictions by PFP, ESG, and PSI-BLAST for moonlighting proteins |
title_full_unstemmed | Evaluation of function predictions by PFP, ESG, and PSI-BLAST for moonlighting proteins |
title_short | Evaluation of function predictions by PFP, ESG, and PSI-BLAST for moonlighting proteins |
title_sort | evaluation of function predictions by pfp, esg, and psi-blast for moonlighting proteins |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3504920/ https://www.ncbi.nlm.nih.gov/pubmed/23173871 http://dx.doi.org/10.1186/1753-6561-6-S7-S5 |
work_keys_str_mv | AT khanishitak evaluationoffunctionpredictionsbypfpesgandpsiblastformoonlightingproteins AT chitalemeghana evaluationoffunctionpredictionsbypfpesgandpsiblastformoonlightingproteins AT rayoncatherine evaluationoffunctionpredictionsbypfpesgandpsiblastformoonlightingproteins AT kiharadaisuke evaluationoffunctionpredictionsbypfpesgandpsiblastformoonlightingproteins |