دورية أكاديمية
Efficient sampling in fragment-based protein structure prediction using an estimation of distribution algorithm.
| العنوان: | Efficient sampling in fragment-based protein structure prediction using an estimation of distribution algorithm. |
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| المؤلفون: | David Simoncini, Kam Y J Zhang |
| المصدر: | PLoS ONE, Vol 8, Iss 7, p e68954 (2013) |
| بيانات النشر: | Public Library of Science (PLoS), 2013. |
| سنة النشر: | 2013 |
| المجموعة: | LCC:Medicine LCC:Science |
| مصطلحات موضوعية: | Medicine, Science |
| الوصف: | Fragment assembly is a powerful method of protein structure prediction that builds protein models from a pool of candidate fragments taken from known structures. Stochastic sampling is subsequently used to refine the models. The structures are first represented as coarse-grained models and then as all-atom models for computational efficiency. Many models have to be generated independently due to the stochastic nature of the sampling methods used to search for the global minimum in a complex energy landscape. In this paper we present EdaFold(AA), a fragment-based approach which shares information between the generated models and steers the search towards native-like regions. A distribution over fragments is estimated from a pool of low energy all-atom models. This iteratively-refined distribution is used to guide the selection of fragments during the building of models for subsequent rounds of structure prediction. The use of an estimation of distribution algorithm enabled EdaFold(AA) to reach lower energy levels and to generate a higher percentage of near-native models. [Formula: see text] uses an all-atom energy function and produces models with atomic resolution. We observed an improvement in energy-driven blind selection of models on a benchmark of EdaFold(AA) in comparison with the [Formula: see text] AbInitioRelax protocol. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1932-6203 |
| Relation: | http://europepmc.org/articles/PMC3723781?pdf=render; https://doaj.org/toc/1932-6203 |
| DOI: | 10.1371/journal.pone.0068954 |
| URL الوصول: | https://doaj.org/article/4ec6acbde5fe4d56b6dae532837f4689 |
| رقم الأكسشن: | edsdoj.4ec6acbde5fe4d56b6dae532837f4689 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 19326203 |
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| DOI: | 10.1371/journal.pone.0068954 |