Predicting the protein-protein interactions using primary structures with predicted protein surface
<p>Abstract</p> <p>Background</p> <p>Many biological functions involve various protein-protein interactions (PPIs). Elucidating such interactions is crucial for understanding general principles of cellular systems. Previous studies have shown the potential of predicting...
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doaj-92f83fb89bfb4a6caa06cf90d7ea0c042020-11-25T01:55:02ZengBMCBMC Bioinformatics1471-21052010-01-0111Suppl 1S310.1186/1471-2105-11-S1-S3Predicting the protein-protein interactions using primary structures with predicted protein surfaceSyu Yu-TangChang DarbyLin Po-Chang<p>Abstract</p> <p>Background</p> <p>Many biological functions involve various protein-protein interactions (PPIs). Elucidating such interactions is crucial for understanding general principles of cellular systems. Previous studies have shown the potential of predicting PPIs based on only sequence information. Compared to approaches that require other auxiliary information, these sequence-based approaches can be applied to a broader range of applications.</p> <p>Results</p> <p>This study presents a novel sequence-based method based on the assumption that protein-protein interactions are more related to amino acids at the surface than those at the core. The present method considers surface information and maintains the advantage of relying on only sequence data by including an accessible surface area (ASA) predictor recently proposed by the authors. This study also reports the experiments conducted to evaluate a) the performance of PPI prediction achieved by including the predicted surface and b) the quality of the predicted surface in comparison with the surface obtained from structures. The experimental results show that surface information helps to predict interacting protein pairs. Furthermore, the prediction performance achieved by using the surface estimated with the ASA predictor is close to that using the surface obtained from protein structures.</p> <p>Conclusion</p> <p>This work presents a sequence-based method that takes into account surface information for predicting PPIs. The proposed procedure of surface identification improves the prediction performance with an <it>F-measure </it>of 5.1%. The extracted surfaces are also valuable in other biomedical applications that require similar information.</p> |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Syu Yu-Tang Chang Darby Lin Po-Chang |
spellingShingle |
Syu Yu-Tang Chang Darby Lin Po-Chang Predicting the protein-protein interactions using primary structures with predicted protein surface BMC Bioinformatics |
author_facet |
Syu Yu-Tang Chang Darby Lin Po-Chang |
author_sort |
Syu Yu-Tang |
title |
Predicting the protein-protein interactions using primary structures with predicted protein surface |
title_short |
Predicting the protein-protein interactions using primary structures with predicted protein surface |
title_full |
Predicting the protein-protein interactions using primary structures with predicted protein surface |
title_fullStr |
Predicting the protein-protein interactions using primary structures with predicted protein surface |
title_full_unstemmed |
Predicting the protein-protein interactions using primary structures with predicted protein surface |
title_sort |
predicting the protein-protein interactions using primary structures with predicted protein surface |
publisher |
BMC |
series |
BMC Bioinformatics |
issn |
1471-2105 |
publishDate |
2010-01-01 |
description |
<p>Abstract</p> <p>Background</p> <p>Many biological functions involve various protein-protein interactions (PPIs). Elucidating such interactions is crucial for understanding general principles of cellular systems. Previous studies have shown the potential of predicting PPIs based on only sequence information. Compared to approaches that require other auxiliary information, these sequence-based approaches can be applied to a broader range of applications.</p> <p>Results</p> <p>This study presents a novel sequence-based method based on the assumption that protein-protein interactions are more related to amino acids at the surface than those at the core. The present method considers surface information and maintains the advantage of relying on only sequence data by including an accessible surface area (ASA) predictor recently proposed by the authors. This study also reports the experiments conducted to evaluate a) the performance of PPI prediction achieved by including the predicted surface and b) the quality of the predicted surface in comparison with the surface obtained from structures. The experimental results show that surface information helps to predict interacting protein pairs. Furthermore, the prediction performance achieved by using the surface estimated with the ASA predictor is close to that using the surface obtained from protein structures.</p> <p>Conclusion</p> <p>This work presents a sequence-based method that takes into account surface information for predicting PPIs. The proposed procedure of surface identification improves the prediction performance with an <it>F-measure </it>of 5.1%. The extracted surfaces are also valuable in other biomedical applications that require similar information.</p> |
work_keys_str_mv |
AT syuyutang predictingtheproteinproteininteractionsusingprimarystructureswithpredictedproteinsurface AT changdarby predictingtheproteinproteininteractionsusingprimarystructureswithpredictedproteinsurface AT linpochang predictingtheproteinproteininteractionsusingprimarystructureswithpredictedproteinsurface |
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