دورية أكاديمية

A probabilistic fragment-based protein structure prediction algorithm.

التفاصيل البيبلوغرافية
العنوان: A probabilistic fragment-based protein structure prediction algorithm.
المؤلفون: David Simoncini, Francois Berenger, Rojan Shrestha, Kam Y J Zhang
المصدر: PLoS ONE, Vol 7, Iss 7, p e38799 (2012)
بيانات النشر: Public Library of Science (PLoS), 2012.
سنة النشر: 2012
المجموعة: LCC:Medicine
LCC:Science
مصطلحات موضوعية: Medicine, Science
الوصف: Conformational sampling is one of the bottlenecks in fragment-based protein structure prediction approaches. They generally start with a coarse-grained optimization where mainchain atoms and centroids of side chains are considered, followed by a fine-grained optimization with an all-atom representation of proteins. It is during this coarse-grained phase that fragment-based methods sample intensely the conformational space. If the native-like region is sampled more, the accuracy of the final all-atom predictions may be improved accordingly. In this work we present EdaFold, a new method for fragment-based protein structure prediction based on an Estimation of Distribution Algorithm. Fragment-based approaches build protein models by assembling short fragments from known protein structures. Whereas the probability mass functions over the fragment libraries are uniform in the usual case, we propose an algorithm that learns from previously generated decoys and steers the search toward native-like regions. A comparison with Rosetta AbInitio protocol shows that EdaFold is able to generate models with lower energies and to enhance the percentage of near-native coarse-grained decoys on a benchmark of [Formula: see text] proteins. The best coarse-grained models produced by both methods were refined into all-atom models and used in molecular replacement. All atom decoys produced out of EdaFold's decoy set reach high enough accuracy to solve the crystallographic phase problem by molecular replacement for some test proteins. EdaFold showed a higher success rate in molecular replacement when compared to Rosetta. Our study suggests that improving low resolution coarse-grained decoys allows computational methods to avoid subsequent sampling issues during all-atom refinement and to produce better all-atom models. EdaFold can be downloaded from http://www.riken.jp/zhangiru/software.html [corrected].
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1932-6203
Relation: https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22829868/?tool=EBI; https://doaj.org/toc/1932-6203
DOI: 10.1371/journal.pone.0038799
URL الوصول: https://doaj.org/article/ac0972fe533943f886e4f1d6b9473e36
رقم الأكسشن: edsdoj.0972fe533943f886e4f1d6b9473e36
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:19326203
DOI:10.1371/journal.pone.0038799