Improvement of protein structure comparison using a structural alphabet

Joseph, Agnel Praveen; Srinivasan, Narayanaswamy; Brevern, Alexandre G. de

doi:10.1016/j.biochi.2011.04.010

Cited by 39 publications

(63 citation statements)

References 95 publications

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“…This structural alphabet allows a reasonable approximation of local protein 3D structures [34] with a root mean square deviation (rmsd) recently evaluated to be 0.42 Å [46]. PBs [46] have been assigned using in-house Python software as in the previous studies [41,42]. Figure 1 gives an outline of the steps involved in mulPBA alignment approach.…”

Section: Protein Blocksmentioning

confidence: 99%

“…The pairwise alignments are obtained using iPBA which performs an anchor based alignment by finding structurally conserved regions, identified as local alignments [41,42]. A combination of local [47] and global [39] dynamic programming algorithms is used for the alignment.…”

Section: Pairwise Alignmentsmentioning

confidence: 99%

“…A combination of local [47] and global [39] dynamic programming algorithms is used for the alignment. A set of local alignments (anchors) associated with these two sequences is derived using a modified version of SIM algorithm [42,47]. The remaining segments between anchors (linkers) are then aligned with relaxed gap penalties, using Needleman-Wunsch algorithm.…”

Section: Pairwise Alignmentsmentioning

confidence: 99%

“…The remaining segments between anchors (linkers) are then aligned with relaxed gap penalties, using Needleman-Wunsch algorithm. The PB substitution matrix was generated using substitution frequencies obtained from alignments of domain pairs in PALI [48] with no more than 40% sequence identity [41,42].…”

Section: Pairwise Alignmentsmentioning

confidence: 99%

“…It first identifies all high scoring and structurally favorable local alignments (anchors) and then aligns the segments between them to obtain a global alignment. This improved PB based structure alignment approach (iPBA) outperformed other established methods when tested on benchmark datasets [41,42].…”

Section: Introductionmentioning

confidence: 99%

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Progressive structure-based alignment of homologous proteins: Adopting sequence comparison strategies

2012

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Comparison of multiple protein structures has a broad range of applications in the analysis of protein structure, function and evolution. Multiple structure alignment tools (MSTAs) are necessary to obtain a simultaneous comparison of a family of related folds. In this study, we have developed a method for multiple structure comparison largely based on sequence alignment techniques. A widely used Structural Alphabet named Protein Blocks (PBs) was used to transform the information on 3D protein backbone conformation as a 1D sequence string.A progressive alignment strategy similar to CLUSTALW was adopted for multiple PB sequence alignment (mulPBA). Highly similar stretches identified by the pairwise alignments are given higher weights during the alignment. The residue equivalences from PB based alignments are used to obtain a three dimensional fit of the structures followed by an iterative refinement of the structural superposition.Systematic comparisons using benchmark datasets of MSTAs underlines that the alignment quality is better than MULTIPROT, MUSTANG and the alignments in HOMSTRAD, in more than 85% of the cases. Comparison with other rigid-body and flexible MSTAs also indicate that mulPBA alignments are superior to most of the rigid-body MSTAs and highly comparable to the flexible alignment methods.3

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Section: Protein Blocksmentioning

confidence: 99%

Section: Pairwise Alignmentsmentioning

confidence: 99%

Section: Pairwise Alignmentsmentioning

confidence: 99%

Section: Pairwise Alignmentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Progressive structure-based alignment of homologous proteins: Adopting sequence comparison strategies

2012

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β‐Bulges: Extensive structural analyses of β‐sheets irregularities

et al. 2013

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b-Sheets are quite frequent in protein structures and are stabilized by regular main-chain hydrogen bond patterns. Irregularities in b-sheets, named b-bulges, are distorted regions between two consecutive hydrogen bonds. They disrupt the classical alternation of side chain direction and can alter the directionality of b-strands. They are implicated in protein-protein interactions and are introduced to avoid b-strand aggregation. Five different types of b-bulges are defined. Previous studies on b-bulges were performed on a limited number of protein structures or one specific family. These studies evoked a potential conservation during evolution. In this work, we analyze the bbulge distribution and conservation in terms of local backbone conformations and amino acid composition. Our dataset consists of 66 times more b-bulges than the last systematic study (Chan et al. Protein Science 1993, 2:1574-1590. Novel amino acid preferences are underlined and local structure conformations are highlighted by the use of a structural alphabet. We observed that bbulges are preferably localized at the N-and C-termini of b-strands, but contrary to the earlier studies, no significant conservation of b-bulges was observed among structural homologues. Displacement of b-bulges along the sequence was also investigated by Molecular Dynamics simulations.

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Use of a structural alphabet to find compatible folds for amino acid sequences

et al. 2014

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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 protein structures into 1D PB sequences and to capture sequence to structure relationships. Our method relies on amino acid occurrence matrices, one for each PB, to score global and local threading of query amino acid sequences to protein folds encoded into PB sequences. It does not use any information from residue contacts or sequencesearch methods or explicit incorporation of hydrophobic effect. The performance of the method was assessed with independent test datasets derived from SCOP 1.75A. With a Z-score cutoff that achieved 95% specificity (i.e., less than 5% false positives), global and local threading showed sensitivity of 64.1% and 34.2%, respectively. We further tested its performance on 57 difficult CASP10 targets that had no known homologs in PDB: 38 compatible templates were identified by our Additional Supporting Information may be found in the online version of this article. approach and 66% of these hits yielded correctly predicted structures. This method scales-up well and offers promising perspectives for structural annotations at genomic level. It has been implemented in the form of a web-server that is freely available at http://www.bo-protscience.fr/forsa.

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Improvement of protein structure comparison using a structural alphabet

Cited by 39 publications

References 95 publications

Progressive structure-based alignment of homologous proteins: Adopting sequence comparison strategies

Progressive structure-based alignment of homologous proteins: Adopting sequence comparison strategies

β‐Bulges: Extensive structural analyses of β‐sheets irregularities

Use of a structural alphabet to find compatible folds for amino acid sequences

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