ProtoMap: automatic classification of protein sequences and hierarchy of protein families

Yona, Golan; Linial, Nathan; Linial, Michal

doi:10.1093/nar/28.1.49

Cited by 141 publications

(84 citation statements)

References 16 publications

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“…In a given round, new ORFs that participated in high-scoring pairs with e-values of Ͻ10 Ϫ5 became the query set for the next round, still against the same database. This process continued until no additional proteins with e-values below the specified cutoff were obtained (22,62). This method identified a total of 171 proteins, including the original 103 queries as S. cerevisiae cell wall components or their paralogs.…”

Section: Methodsmentioning

confidence: 99%

Conserved Processes and Lineage-Specific Proteins in Fungal Cell Wall Evolution

et al. 2007

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The cell wall is a defining organelle that differentiates fungi from its sister clades in the opisthokont superkingdom. With a sensitive technique to align low-complexity protein sequences, we have identified 187 cell wall-related proteins in Saccharomyces cerevisiae and determined the presence or absence of homologs in 17 other fungal genomes. There were both conserved and lineage-specific cell wall proteins, and the degree of conservation was strongly correlated with protein function. Some functional classes were poorly conserved and lineage specific: adhesins, structural wall glycoprotein components, and unannotated open reading frames. These proteins are primarily those that are constituents of the walls themselves. On the other hand, glycosyl hydrolases and transferases, proteases, lipases, proteins in the glycosyl phosphatidyl-inositol-protein synthesis pathway, and chaperones were strongly conserved. Many of these proteins are also conserved in other eukaryotes and are associated with wall synthesis in plants. This gene conservation, along with known similarities in wall architecture, implies that the basic architecture of fungal walls is ancestral to the divergence of the ascomycetes and basidiomycetes. The contrasting lineage specificity of wall resident proteins implies diversification. Therefore, fungal cell walls consist of rapidly diversifying proteins that are assembled by the products of an ancestral and conserved set of genes.

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Section: Methodsmentioning

confidence: 99%

Conserved Processes and Lineage-Specific Proteins in Fungal Cell Wall Evolution

et al. 2007

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“…For each method i and each sequence s in the database, we report the sequence, provided its E value E i (s) is below or equal to a cutoff value E C of 1,000. Then, one method is chosen to be used as a reference method, on the basis of which the E values of the other methods are rescaled (25). In CHASE, we use HMMSEARCH as our reference method.…”

Section: For Each Sequence S To Produce E Values Of Comparable Size mentioning

confidence: 99%

Comparative homology agreement search: An effective combination of homology-search methods

Álam

Dress

Rehmsmeier

et al. 2004

Proc. Natl. Acad. Sci. U.S.A.

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Many methods have been developed to search for homologous members of a protein family in databases, and the reliability of results and conclusions may be compromised if only one method is used, neglecting the others. Here we introduce a general scheme for combining such methods. Based on this scheme, we implemented a tool called comparative homology agreement search (CHASE) that integrates different search strategies to obtain a combined ''E value.'' Our results show that a consensus method integrating distinct strategies easily outperforms any of its component algorithms. More specifically, an evaluation based on the Structural Classification of Proteins database reveals that, on average, a coverage of 47% can be obtained in searches for distantly related homologues (i.e., members of the same superfamily but not the same family, which is a very difficult task), accepting only 10 false positives, whereas the individual methods obtain a coverage of 28 -38%.S equence-homology search algorithms are important computational tools in molecular biology. There exist at least three general classes of techniques used in searches for protein homologues, namely pairwise sequence comparisons such as basic local alignment search tool (BLAST), profile-based searches such as HMMSEARCH, and motif-or pattern-based analyses such as pattern-hit-initiated BLAST (PHI-BLAST) (1-5).In a pairwise search, a query sequence is compared to any database sequence, yielding a confidence estimate that is supposed to indicate the probability of finding a comparably similar sequence (of the same size) in a database of random sequences. The comparison is done for every sequence in the database, and the sequences with highest confidence (''hits'') are reported. The most popular pairwise-search tool is BLAST (1).Simple profile searches make use of position-specific scoring statistics and are usually more sensitive than pairwise comparisons. The introduction of hidden Markov models (HMMs) seems to provide a firmer statistical basis for profile search. The majority of currently available profile tools use HMMs (for example, the HMMER package) (6).Kinship between protein sequences can also lead to (and thus be recognized by) the occurrence of particular amino acid motifs (also known as patterns, signatures, or fingerprints) that were conserved throughout the evolution of the protein family in question and are believed to correlate with specific structural features and function. Motif analysis, therefore, can also be used for identifying new members of a protein family (7-10). Motifs are the backbone of homology-search methods such as PHI-BLAST (5). In contrast to profiles, motifs are usually short, they include a short stretch of very specific amino acids deemed relevant for function, and they are denoted by specific regular expressions.In this study, we will show that the overall performance of homology searches can be improved if these methods are combined appropriately. The combination of methods is an advanced form of a metastudy. Important medical...

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“…[78,88]). This provides a broader road map that includes all three SNARE prototypes as described in (Fig.…”

Section: A Road Map To All Snare Proteinsmentioning

confidence: 99%

“…The helical SNARE domains of syntaxin in both genomes share similar global features. This includes [78]). The number of proteins from each cluster that contribute to an edge is marked next to the cluster.…”

Section: Diversity Of Snares In Human and Plant Genomesmentioning

confidence: 99%

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SNARE Proteins - From Membranes to Genomes

Linial¹

2001

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Abstract:The function and the organization of eukaryotic cells require directional transport of vesicles between compartments. This sort of membrane flow relies on the presence of docking and fusion machinery. The core of this machinery is a protein complex composed of syntaxin, SNAP-25 and VAMP, collectively termed SNAREs. A correct interaction among SNARE prototypes is essential for fruitful docking and fusion. Analysis of large-scale sequencing projects reveals that each of the SNARE proteins (syntaxin, SNAP-25 and VAMP) is a member of a large protein family that is represented in every eukaryotic genome. The diversity among the three SNARE prototypes allows an enriched combinatorial make-up to meet a wide range of cellular demands for secretion.Herein, we discuss the diversity in SNARE proteins from a genomic perspective. We combine information from large-scale sequence data with structural and functional classifications of SNAREs. Using a sequence-based automated protein classification tool, we expose weak but significant connections among all three SNARE protein clusters. These connections define a local evolutionary network within the protein universe. Genomic data allows us to identify classical SNAREs as well as their remote evolutionary relatives. We focus on the SNARE representatives from human and plant genomes to discuss the source of complexity and specificity for docking and fusion in a eukaryotic cell. How many of the potential SNARE combinations are indeed valid in vivo, and to what extent does each combination specify a biochemical and biophysical unique entity, is yet to be experimentally determined. THE SNARE PROTEINS -PAST AND PRESENTThe process of vesicle trafficking and secretion has been investigated in great detail over the last decade (reviewed by [1][2][3][4][5]). Investigators in the field of secretion seem to have come to a consensus that the fusion event relies on a small number of interacting proteins [2,[6][7][8]. The key proteins in this set are syntaxin, SNAP-25, VAMP and variants thereof. These proteins are collectively known as SNAREs [9]. SNARE is an acronym for SNAP receptor, indicating that these proteins function as receptors for NSF (Nethylmaleimide Sensitive Fusion protein) and SNAPs (Soluble NSF Attachment Protein). Association with SNAPs and NSF forms a fusion particle that is essential for vesicular trafficking among subcellular compartments [10,11]. These receptors are localized to two separate membranes that are to be fused [12]. According to their expected localization, they are divided between those on the vesicular membrane (v-SNARE) and those on the target membrane (t-SNARE). The first set of SNAREs identified from solubilized brain extracts includes VAMP/ synaptobrevin on the synaptic vesicle membrane (v-SNARE) and two t-SNAREs, syntaxin and SNAP-25 (from the plasma membrane).Immediately following the identification of mammalian SNAREs, homologues were found in other organisms [13][14][15][16]. It became clear that all three SNARE prototypes are *Address corres...

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ProtoMap: automatic classification of protein sequences and hierarchy of protein families

Cited by 141 publications

References 16 publications

Conserved Processes and Lineage-Specific Proteins in Fungal Cell Wall Evolution

Conserved Processes and Lineage-Specific Proteins in Fungal Cell Wall Evolution

Comparative homology agreement search: An effective combination of homology-search methods

SNARE Proteins - From Membranes to Genomes

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