The limits of protein sequence comparison?

Pearson, William R.; Sierk, Michael

doi:10.1016/j.sbi.2005.05.005

Cited by 74 publications

(60 citation statements)

References 57 publications

(55 reference statements)

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“…Furthermore, we aim to improve protein structure prediction approaches on the basis of nonsequential structural relations. In this context, multiple structure alignments with GANGSTA+ that can be used to define new sequence similarity measures for sequence alignment methods could be a promising direction (Schwartz and Dayhoff 1978;Pearson and Lipman 1988;Henikoff and Henikoff 1992;Altschul et al 1997;Pearson and Sierk 2005).…”

Section: Discussionmentioning

confidence: 99%

Novel protein folds and their nonsequential structural analogs

Guerler

Knapp

2008

Protein Science

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Newly determined protein structures are classified to belong to a new fold, if the structures are sufficiently dissimilar from all other so far known protein structures. To analyze structural similarities of proteins, structure alignment tools are used. We demonstrate that the usage of nonsequential structure alignment tools, which neglect the polypeptide chain connectivity, can yield structure alignments with significant similarities between proteins of known three-dimensional structure and newly determined protein structures that possess a new fold. The recently introduced protein structure alignment tool, GANGSTA, is specialized to perform nonsequential alignments with proper assignment of the secondary structure types by focusing on helices and strands only. In the new version, GANGSTA+, the underlying algorithms were completely redesigned, yielding enhanced quality of structure alignments, offering alignment against a larger database of protein structures, and being more efficient. We applied DaliLite, TM-align, and GANGSTA+ on three protein crystal structures considered to be novel folds. Applying GANGSTA+ to these novel folds, we find proteins in the ASTRAL40 database, which possess significant structural similarities, albeit the alignments are nonsequential and in some cases involve secondary structure elements aligned in reverse orientation. A web server is available at http:// agknapp.chemie.fu-berlin.de/gplus for pairwise alignment, visualization, and database comparison.

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Section: Discussionmentioning

confidence: 99%

Novel protein folds and their nonsequential structural analogs

Guerler

Knapp

2008

Protein Science

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“…Specifically, BLAST was not designed to calculate protein homology but uses a heuristic method to produce an e-value and bitscore; what can be derived from BLAST output has been usefully discussed by Pearson and Sierk (2005): "if a similarity score is not random, then the sequences must be not unrelated." In other terms, every alignment that passes a reasonable e-value test denotes statistically significant sequence similarity, suggesting the sequences are related.…”

Section: Annotationmentioning

confidence: 99%

“…Hits with similar bitscores do not necessarily align to the same part of the protein or have similar alignment length, underlining the risk in considering them as "similar." We believe this apparent pitfall, sometimes made due to a misconception regarding the nature of bitscore in BLAST output (Pertsemlidis and Fondon, 2001;Pearson and Sierk, 2005), could be avoided by considering an optimal bitscore, representing the highest possible bitscore generated by a given alignment. Simply aligning the part of the protein involved in the alignment with itself gives the optimal bitscore (previous scoring parameters are maintained).…”

Section: Percentage Optimal Bitscorementioning

confidence: 99%

Comparative Transcriptomic Approaches Exploring Contamination Stress Tolerance in Salix sp. Reveal the Importance for a Metaorganismal de Novo Assembly Approach for Nonmodel Plants

et al. 2016

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Metatranscriptomic study of nonmodel organisms requires strategies that retain the highly resolved genetic information generated from model organisms while allowing for identification of the unexpected. A real-world biological application of phytoremediation, the field growth of 10 Salix cultivars on polluted soils, was used as an exemplar nonmodel and multifaceted crop response well-disposed to the study of gene expression. Sequence reads were assembled de novo to create 10 independent transcriptomes, a global transcriptome, and were mapped against the Salix purpurea 94006 reference genome. Annotation of assembled contigs was performed without a priori assumption of the originating organism. Global transcriptome construction from 3.03 billion paired-end reads revealed 606,880 unique contigs annotated from 1588 species, often common in all 10 cultivars. Comparisons between transcriptomic and metatranscriptomic methodologies provide clear evidence that nonnative RNA can mistakenly map to reference genomes, especially to conserved regions of common housekeeping genes, such as actin, a/b-tubulin, and elongation factor 1-a. In Salix, Rubisco activase transcripts were down-regulated in contaminated trees across all 10 cultivars, whereas thiamine thizole synthase and CP12, a Calvin Cycle master regulator, were uniformly up-regulated. De novo assembly approaches, with unconstrained annotation, can improve data quality; care should be taken when exploring such plant genetics to reduce de facto data exclusion by mapping to a single reference genome alone. Salix gene expression patterns strongly suggest cultivar-wide alteration of specific photosynthetic apparatus and protection of the antenna complexes from oxidation damage in contaminated trees, providing an insight into common stress tolerance strategies in a real-world phytoremediation system.Coppiced willows have the ability to produce high biomass yields in temperate regions under challenging conditions and have positive impacts on biodiversity (Labrecque et al

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“…The objective when using a sequence alignment for database searching [objective (iii)] is to maximise the distinction between homologous and non-homologous sequences (reviewed by Pearson and Sierk 2005). That is, we want the high-scoring database matches to be sequences that are homologous to our query sequence, and nonhomologous sequences to be low-scoring matches.…”

Section: Tpchtsghicyfvsk-pggseppavftgdtlf Structure ----------Ssss---mentioning

confidence: 99%

Multiple sequence alignment for phylogenetic purposes

Morrison¹

2006

Aust. Systematic Bot.

135

113

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I have addressed the biological rather than bioinformatics aspects of molecular sequence alignment by covering a series of topics that have been under-valued, particularly within the context of phylogenetic analysis. First, phylogenetic analysis is only one of the many objectives of sequence alignment, and the most appropriate multiple alignment may not be the same for all of these purposes. Phylogenetic alignment thus occupies a specific place within a broader context. Second, homology assessment plays an intricate role in phylogenetic analysis, with sequence alignment consisting of primary homology assessment and tree building being secondary homology assessment. The objective of phylogenetic alignment thus distinguishes it from other sorts of alignment. Third, I summarise what is known about the serious limitations of using phenetic similarity as a criterion for automated multiple alignment, and provide an overview of what is currently being done to improve these computerised procedures. This synthesises information that is apparently not widely known among phylogeneticists. Fourth, I then consider the recent development of automated procedures for combining alignment and tree building, thus integrating primary and secondary homology assessment. Finally, I outline various strategies for increasing the biological content of sequence alignment procedures, which consists of taking into account known evolutionary processes when making alignment decisions. These procedures can be objective and repeatable, and can involve computerised algorithms to automate much of the work. Perhaps the most important suggestion is that alignment should be seen as a process where new sequences are added to a pre-existing alignment that has been manually curated by the biologist.

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The limits of protein sequence comparison?

Cited by 74 publications

References 57 publications

Novel protein folds and their nonsequential structural analogs

Novel protein folds and their nonsequential structural analogs

Comparative Transcriptomic Approaches Exploring Contamination Stress Tolerance in Salix sp. Reveal the Importance for a Metaorganismal de Novo Assembly Approach for Nonmodel Plants

Multiple sequence alignment for phylogenetic purposes

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