Dataset Information

4SCOPmap: automated assignment of protein structures to evolutionary superfamilies.

ABSTRACT: Inference of remote homology between proteins is very challenging and remains a prerogative of an expert. Thus a significant drawback to the use of evolutionary-based protein structure classifications is the difficulty in assigning new proteins to unique positions in the classification scheme with automatic methods. To address this issue, we have developed an algorithm to map protein domains to an existing structural classification scheme and have applied it to the SCOP database.The general strategy employed by this algorithm is to combine the results of several existing sequence and structure comparison tools applied to a query protein of known structure in order to find the homologs already classified in SCOP database and thus determine classification assignments. The algorithm is able to map domains within newly solved structures to the appropriate SCOP superfamily level with approximately 95% accuracy. Examples of correctly mapped remote homologs are discussed. The algorithm is also capable of identifying potential evolutionary relationships not specified in the SCOP database, thus helping to make it better. The strategy of the mapping algorithm is not limited to SCOP and can be applied to any other evolutionary-based classification scheme as well. SCOPmap is available for download.The SCOPmap program is useful for assigning domains in newly solved structures to appropriate superfamilies and for identifying evolutionary links between different superfamilies.

SUBMITTER: Cheek S

PROVIDER: S-EPMC544345 | biostudies-literature | 2004 Dec

REPOSITORIES: biostudies-literature

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4SCOPmap: automated assignment of protein structures to evolutionary superfamilies.

Cheek Sara S Qi Yuan Y Krishna S Sri SS Kinch Lisa N LN Grishin Nick V NV

BMC bioinformatics 20041214

<h4>Background</h4>Inference of remote homology between proteins is very challenging and remains a prerogative of an expert. Thus a significant drawback to the use of evolutionary-based protein structure classifications is the difficulty in assigning new proteins to unique positions in the classification scheme with automatic methods. To address this issue, we have developed an algorithm to map protein domains to an existing structural classification scheme and have applied it to the SCOP databa ...[more]

PMID: 15598351

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Project description:BackgroundThe functional selection and three-dimensional structural constraints of proteins in nature often relates to the retention of significant sequence similarity between proteins of similar fold and function despite poor sequence identity. Organization of structure-based sequence alignments for distantly related proteins, provides a map of the conserved and critical regions of the protein universe that is useful for the analysis of folding principles, for the evolutionary unification of protein families and for maximizing the information return from experimental structure determination. The Protein Alignment organised as Structural Superfamily (PASS2) database represents continuously updated, structural alignments for evolutionary related, sequentially distant proteins.DescriptionAn automated and updated version of PASS2 is, in direct correspondence with SCOP 1.63, consisting of sequences having identity below 40% among themselves. Protein domains have been grouped into 628 multi-member superfamilies and 566 single member superfamilies. Structure-based sequence alignments for the superfamilies have been obtained using COMPARER, while initial equivalencies have been derived from a preliminary superposition using LSQMAN or STAMP 4.0. The final sequence alignments have been annotated for structural features using JOY4.0. The database is supplemented with sequence relatives belonging to different genomes, conserved spatially interacting and structural motifs, probabilistic hidden markov models of superfamilies based on the alignments and useful links to other databases. Probabilistic models and sensitive position specific profiles obtained from reliable superfamily alignments aid annotation of remote homologues and are useful tools in structural and functional genomics. PASS2 presents the phylogeny of its members both based on sequence and structural dissimilarities. Clustering of members allows us to understand diversification of the family members. The search engine has been improved for simpler browsing of the database.ConclusionsThe database resolves alignments among the structural domains consisting of evolutionarily diverged set of sequences. Availability of reliable sequence alignments of distantly related proteins despite poor sequence identity and single-member superfamilies permit better sampling of structures in libraries for fold recognition of new sequences and for the understanding of protein structure-function relationships of individual superfamilies. PASS2 is accessible at http://www.ncbs.res.in/~faculty/mini/campass/pass2.html

Project description:Heat shock protein 20 (Hsp20) genes play important roles in plant growth, development, and response to environmental stress. However, the Hsp20 gene family has not yet been systematically investigated, and its function in red algae (Rhodophyta) remains poorly understood. Herein, we characterized Hsp20 gene families in red algae by studying gene structure, conserved motifs, phylogenetic relationships, chromosome location, gene duplication, cis-regulatory elements, and expression profiles. In this study, 97 Hsp20 genes were identified using bioinformatic methods and classified into 13 subfamilies based on phylogenetic relationships. Phylogenetic analysis revealed that Hsp20 genes might have a polyphyletic origin and a complex evolutionary pattern. Gene structure analysis revealed that most Hsp20 genes possessed no introns, and all Hsp20 genes contained a conserved α-crystalline domain in the C-terminal region. Conserved motif analysis revealed that Hsp20 genes belonging to the same subfamily shared similar motifs. Gene duplication analysis demonstrated that tandem and segmental duplication events occurred in these gene families. Additionally, these gene families in red algae might have experienced strong purifying selection pressure during evolution, and Hsp20 genes in Pyropia yezoensis, Pyropia haitanensis, and Porphyra umbilicalis were highly evolutionarily conserved. The cis-elements of phytohormone-, light-, stress-responsive, and development-related were identified in the red algal Hsp20 gene promoter sequences. Finally, using Py. yezoensis, as a representative of red algae, the Hsp20 gene expression profile was explored. Based on the RNA-seq data, Py. yezoensis Hsp20 (PyyHsp20) genes were found to be involved in Py. yezoensis responses against abiotic and biotic stresses and exhibited diverse expression patterns. Moreover, PyyHsp20 is involved in Py. yezoensis growth and development and revealed spatial and temporal expression patterns. These results provide comprehensive and valuable information on Hsp20 gene families in red algae and lay a foundation for their functional characterization. In addition, our study provides new insights into the evolution of Hsp20 gene families in red algae and will help understand the adaptability of red algae to diverse environments.

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Dataset Information

4SCOPmap: automated assignment of protein structures to evolutionary superfamilies.

Publications

4SCOPmap: automated assignment of protein structures to evolutionary superfamilies.

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