A protein-dependent side-chain rotamer library
<p>Abstract</p> <p>Background</p> <p>Protein side-chain packing problem has remained one of the key open problems in bioinformatics. The three main components of protein side-chain prediction methods are a rotamer library, an energy function and a search algorithm. Rota...
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doaj-7330fa8a9bd54f90aee10bf3e4ae4b952020-11-25T01:03:01ZengBMCBMC Bioinformatics1471-21052011-12-0112Suppl 14S1010.1186/1471-2105-12-S14-S10A protein-dependent side-chain rotamer libraryBhuyan Md SharifulGao Xin<p>Abstract</p> <p>Background</p> <p>Protein side-chain packing problem has remained one of the key open problems in bioinformatics. The three main components of protein side-chain prediction methods are a rotamer library, an energy function and a search algorithm. Rotamer libraries summarize the existing knowledge of the experimentally determined structures quantitatively. Depending on how much contextual information is encoded, there are backbone-independent rotamer libraries and backbone-dependent rotamer libraries. Backbone-independent libraries only encode sequential information, whereas backbone-dependent libraries encode both sequential and locally structural information. However, side-chain conformations are determined by spatially local information, rather than sequentially local information. Since in the side-chain prediction problem, the backbone structure is given, spatially local information should ideally be encoded into the rotamer libraries.</p> <p>Methods</p> <p>In this paper, we propose a new type of backbone-dependent rotamer library, which encodes structural information of all the spatially neighboring residues. We call it protein-dependent rotamer libraries. Given any rotamer library and a protein backbone structure, we first model the protein structure as a Markov random field. Then the marginal distributions are estimated by the inference algorithms, without doing global optimization or search. The rotamers from the given library are then re-ranked and associated with the updated probabilities.</p> <p>Results</p> <p>Experimental results demonstrate that the proposed protein-dependent libraries significantly outperform the widely used backbone-dependent libraries in terms of the side-chain prediction accuracy and the rotamer ranking ability. Furthermore, without global optimization/search, the side-chain prediction power of the protein-dependent library is still comparable to the global-search-based side-chain prediction methods.</p> |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Bhuyan Md Shariful Gao Xin |
spellingShingle |
Bhuyan Md Shariful Gao Xin A protein-dependent side-chain rotamer library BMC Bioinformatics |
author_facet |
Bhuyan Md Shariful Gao Xin |
author_sort |
Bhuyan Md Shariful |
title |
A protein-dependent side-chain rotamer library |
title_short |
A protein-dependent side-chain rotamer library |
title_full |
A protein-dependent side-chain rotamer library |
title_fullStr |
A protein-dependent side-chain rotamer library |
title_full_unstemmed |
A protein-dependent side-chain rotamer library |
title_sort |
protein-dependent side-chain rotamer library |
publisher |
BMC |
series |
BMC Bioinformatics |
issn |
1471-2105 |
publishDate |
2011-12-01 |
description |
<p>Abstract</p> <p>Background</p> <p>Protein side-chain packing problem has remained one of the key open problems in bioinformatics. The three main components of protein side-chain prediction methods are a rotamer library, an energy function and a search algorithm. Rotamer libraries summarize the existing knowledge of the experimentally determined structures quantitatively. Depending on how much contextual information is encoded, there are backbone-independent rotamer libraries and backbone-dependent rotamer libraries. Backbone-independent libraries only encode sequential information, whereas backbone-dependent libraries encode both sequential and locally structural information. However, side-chain conformations are determined by spatially local information, rather than sequentially local information. Since in the side-chain prediction problem, the backbone structure is given, spatially local information should ideally be encoded into the rotamer libraries.</p> <p>Methods</p> <p>In this paper, we propose a new type of backbone-dependent rotamer library, which encodes structural information of all the spatially neighboring residues. We call it protein-dependent rotamer libraries. Given any rotamer library and a protein backbone structure, we first model the protein structure as a Markov random field. Then the marginal distributions are estimated by the inference algorithms, without doing global optimization or search. The rotamers from the given library are then re-ranked and associated with the updated probabilities.</p> <p>Results</p> <p>Experimental results demonstrate that the proposed protein-dependent libraries significantly outperform the widely used backbone-dependent libraries in terms of the side-chain prediction accuracy and the rotamer ranking ability. Furthermore, without global optimization/search, the side-chain prediction power of the protein-dependent library is still comparable to the global-search-based side-chain prediction methods.</p> |
work_keys_str_mv |
AT bhuyanmdshariful aproteindependentsidechainrotamerlibrary AT gaoxin aproteindependentsidechainrotamerlibrary AT bhuyanmdshariful proteindependentsidechainrotamerlibrary AT gaoxin proteindependentsidechainrotamerlibrary |
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