2014
DOI: 10.1002/pro.2581
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Use of a structural alphabet to find compatible folds for amino acid sequences

Abstract: The structural annotation of proteins with no detectable homologs of known 3D structure identified using sequence-search methods is a major challenge today. We propose an original method that computes the conditional probabilities for the amino-acid sequence of a protein to fit to known protein 3D structures using a structural alphabet, known as "Protein Blocks" (PBs). PBs constitute a library of 16 local structural prototypes that approximate every part of protein backbone structures. It is used to encode 3D … Show more

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Cited by 9 publications
(5 citation statements)
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“…The most recent impressive developments concern the inclusion of PBs in threading approaches (Mahajan, de Brevern, Sanejouand, Srinivasan & Offmann 2015;Vetrivel et al 2017) and fold recognition especially with ORION (Ghouzam, Postic, de Brevern & Gelly 2015;Ghouzam, Postic, Guerin, de Brevern & Gelly 2016).…”
Section: Introductionmentioning
confidence: 99%
“…The most recent impressive developments concern the inclusion of PBs in threading approaches (Mahajan, de Brevern, Sanejouand, Srinivasan & Offmann 2015;Vetrivel et al 2017) and fold recognition especially with ORION (Ghouzam, Postic, de Brevern & Gelly 2015;Ghouzam, Postic, Guerin, de Brevern & Gelly 2016).…”
Section: Introductionmentioning
confidence: 99%
“…I-TASSER [186], HHPred of the HH suite [187] and Alpha fold [188] can be used to predict the 3D structure of proteins from their aminoacid sequences. FoRSA [189] is able to identify a protein fold from its amino-acid sequence or a protein sequence in the proteome of a species from a crystal structure.…”
Section: Protein Structure Studymentioning
confidence: 99%
“…Protein Blocks are a 16 state classification of pentapeptide fragments that can abstract any part of a protein backbone structure [17][18] . The versatility of PBs to abstract protein structures have been exploited for diverse applications: to predict protein structure 19-21 , in fold recognition 22,23 , for structural motif identification [24][25][26] , molecular dynamics trajectory analysis 27,28 etc. 39 Furthermore,…”
Section: Introductionmentioning
confidence: 99%