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Structure prediction for the helical skeletons detected from the low resolution protein density map

BACKGROUND: The current advances in electron cryo-microscopy technique have made it possible to obtain protein density maps at about 6-10 Å resolution. Although it is hard to derive the protein chain directly from such a low resolution map, the location of the secondary structures such as helices an...

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Detalles Bibliográficos
Autores principales: Al Nasr, Kamal, Sun, Weitao, He, Jing
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3009517/
https://www.ncbi.nlm.nih.gov/pubmed/20122218
http://dx.doi.org/10.1186/1471-2105-11-S1-S44
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author Al Nasr, Kamal
Sun, Weitao
He, Jing
author_facet Al Nasr, Kamal
Sun, Weitao
He, Jing
author_sort Al Nasr, Kamal
collection PubMed
description BACKGROUND: The current advances in electron cryo-microscopy technique have made it possible to obtain protein density maps at about 6-10 Å resolution. Although it is hard to derive the protein chain directly from such a low resolution map, the location of the secondary structures such as helices and strands can be computationally detected. It has been demonstrated that such low-resolution map can be used during the protein structure prediction process to enhance the structure prediction. RESULTS: We have developed an approach to predict the 3-dimensional structure for the helical skeletons that can be detected from the low resolution protein density map. This approach does not require the construction of the entire chain and distinguishes the structures based on the conformation of the helices. A test with 35 low resolution density maps shows that the highest ranked structure with the correct topology can be found within the top 1% of the list ranked by the effective energy formed by the helices. CONCLUSION: The results in this paper suggest that it is possible to eliminate the great majority of the bad conformations of the helices even without the construction of the entire chain of the protein. For many proteins, the effective contact energy formed by the secondary structures alone can distinguish a small set of likely structures from the pool.
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spelling pubmed-30095172010-12-23 Structure prediction for the helical skeletons detected from the low resolution protein density map Al Nasr, Kamal Sun, Weitao He, Jing BMC Bioinformatics Research BACKGROUND: The current advances in electron cryo-microscopy technique have made it possible to obtain protein density maps at about 6-10 Å resolution. Although it is hard to derive the protein chain directly from such a low resolution map, the location of the secondary structures such as helices and strands can be computationally detected. It has been demonstrated that such low-resolution map can be used during the protein structure prediction process to enhance the structure prediction. RESULTS: We have developed an approach to predict the 3-dimensional structure for the helical skeletons that can be detected from the low resolution protein density map. This approach does not require the construction of the entire chain and distinguishes the structures based on the conformation of the helices. A test with 35 low resolution density maps shows that the highest ranked structure with the correct topology can be found within the top 1% of the list ranked by the effective energy formed by the helices. CONCLUSION: The results in this paper suggest that it is possible to eliminate the great majority of the bad conformations of the helices even without the construction of the entire chain of the protein. For many proteins, the effective contact energy formed by the secondary structures alone can distinguish a small set of likely structures from the pool. BioMed Central 2010-01-18 /pmc/articles/PMC3009517/ /pubmed/20122218 http://dx.doi.org/10.1186/1471-2105-11-S1-S44 Text en Copyright ©2010 Al Nasr 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 Research
Al Nasr, Kamal
Sun, Weitao
He, Jing
Structure prediction for the helical skeletons detected from the low resolution protein density map
title Structure prediction for the helical skeletons detected from the low resolution protein density map
title_full Structure prediction for the helical skeletons detected from the low resolution protein density map
title_fullStr Structure prediction for the helical skeletons detected from the low resolution protein density map
title_full_unstemmed Structure prediction for the helical skeletons detected from the low resolution protein density map
title_short Structure prediction for the helical skeletons detected from the low resolution protein density map
title_sort structure prediction for the helical skeletons detected from the low resolution protein density map
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3009517/
https://www.ncbi.nlm.nih.gov/pubmed/20122218
http://dx.doi.org/10.1186/1471-2105-11-S1-S44
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