ArticleBMC structural biology2008
CUSP: an algorithm to distinguish structurally conserved and unconserved regions in protein domain alignments and its application in the study of large length variations.
Article in BMC structural biology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- PASS2: update of database of structure-based sequence alignments.Database : the journal of biological databases and curation · 2025Article
- PASS2.7: a database containing structure-based sequence alignments and associated features of protein domain superfamilies from SCOPe.Database : the journal of biological databases and curation · 2022Article
- GenDiS database update with improved approach and features to recognize homologous sequences of protein domain superfamilies.Database : the journal of biological databases and curation · 2019Article
- PASS2 version 6: a database of structure-based sequence alignments of protein domain superfamilies in accordance with SCOPe.Database : the journal of biological databases and curation · 2019Article
- PASS2 database for the structure-based sequence alignment of distantly related SCOP domain superfamilies: update to version 5 and added features.Nucleic acids research · 2016Article
- The Recent De Novo Origin of Protein C-Termini.Genome biology and evolution · 2015Article
- LenVarDB: database of length-variant protein domains.Nucleic acids research · 2014Article
- Structural updates of alignment of protein domains and consequences on evolutionary models of domain superfamilies.BioData mining · 2013Article
- Defining and predicting structurally conserved regions in protein superfamilies.Bioinformatics (Oxford, England) · 2013Article
- PASS2 version 4: an update to the database of structure-based sequence alignments of structural domain superfamilies.Nucleic acids research · 2012Article
- Detailed analysis of function divergence in a large and diverse domain superfamily: toward a refined protocol of function classification.Structure (London, England : 1993) · 2010Article
- Identification of structurally conserved residues of proteins in absence of structural homologs using neural network ensemble.Bioinformatics (Oxford, England) · 2009Article
- Length variations amongst protein domain superfamilies and consequences on structure and function.PloS one · 2009Article
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6 authors.
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Abstract
backgroundDistantly related proteins adopt and retain similar structural scaffolds despite length variations that could be as much as two-fold in some protein superfamilies. In this paper, we describe an analysis of indel regions that accommodate length variations amongst related proteins. We have developed an algorithm CUSP, to examine multi-membered PASS2 superfamily alignments to identify indel regions in an automated manner. Further, we have used the method to characterize the length, structural type and biochemical features of indels in related protein domains.
resultsCUSP, examines protein domain structural alignments to distinguish regions of conserved structure common to related proteins from structurally unconserved regions that vary in length and type of structure. On a non-redundant dataset of 353 domain superfamily alignments from PASS2, we find that 'length- deviant' protein superfamilies show > 30% length variation from their average domain length. 60% of additional lengths that occur in indels are short-length structures (< 5 residues) while 6% of indels are > 15 residues in length. Structural types in indels also show class-specific trends.
conclusionThe extent of length variation varies across different superfamilies and indels show class-specific trends for preferred lengths and structural types. Such indels of different lengths even within a single protein domain superfamily could have structural and functional consequences that drive their selection, underlying their importance in similarity detection and computational modelling. The availability of systematic algorithms, like CUSP, should enable decision making in a domain superfamily-specific manner.
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