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1.
Joel A Malek  Daniel H Haft 《Genome biology》2001,2(5):preprint00-23

Background  

Conserved domains (CD) in proteins play a crucial role in protein interactions, DNA binding, enzyme activity, and other important cellular processes. We proposed to study ratios of genes containing these domains to ratios of proteome size of different eukaryotes.  相似文献   

2.

Background  

Detection of sequence homologues represents a challenging task that is important for the discovery of protein families and the reliable application of automatic annotation methods. The presence of domains in protein families of diverse function, inhomogeneity and different sizes of protein families create considerable difficulties for the application of published clustering methods.  相似文献   

3.

Background  

Sterile alpha motif (Sam) domains are small protein modules that can be involved in homotypic or heterotypic associations and exhibit different functions. Previous studies have demonstrated that the Sam domain of the lipid phosphatase Ship2 can hetero-dimerize with the Sam domain of the PI3K effector protein Arap3.  相似文献   

4.

Background  

PDZ domain is a well-conserved, structural protein domain found in hundreds of signaling proteins that are otherwise unrelated. PDZ domains can bind to the C-terminal peptides of different proteins and act as glue, clustering different protein complexes together, targeting specific proteins and routing these proteins in signaling pathways. These domains are classified into classes I, II and III, depending on their binding partners and the nature of bonds formed. Binding specificities of PDZ domains are very crucial in order to understand the complexity of signaling pathways. It is still an open question how these domains recognize and bind their partners.  相似文献   

5.

Background  

Protein domains are the structural and functional units of proteins. The ability to parse proteins into different domains is important for effective classification, understanding of protein structure, function, and evolution and is hence biologically relevant. Several computational methods are available to identify domains in the sequence. Domain finding algorithms often employ stringent thresholds to recognize sequence domains. Identification of additional domains can be tedious involving intense computation and manual intervention but can lead to better understanding of overall biological function. In this context, the problem of identifying new domains in the unassigned regions of a protein sequence assumes a crucial importance.  相似文献   

6.

Background  

Alternative exons encode different isoforms of the human insulin-like growth factor-I (IGF-I) precursor without altering mature IGF-I. We hypothesized that the various IGF-I precursors may traffic IGF-I differently. Chimeric IGF-I precursors were made with green fluorescent protein (GFP) cloned between the signal and mature IGF-I domains.  相似文献   

7.

Background  

Proteins, especially larger ones, are often composed of individual evolutionary units, domains, which have their own function and structural fold. Predicting domains is an important intermediate step in protein analyses, including the prediction of protein structures.  相似文献   

8.

Background  

In this paper we describe an analysis of the size evolution of both protein domains and their indels, as inferred by changing sizes of whole domains or individual unaligned regions or "spacers". We studied relatively early evolutionary events and focused on protein domains which are conserved among various taxonomy groups.  相似文献   

9.

Background  

Hotspots are defined as the minimal functional domains involved in protein:protein interactions and sufficient to induce a biological response.  相似文献   

10.

Background  

Protein domains are protein regions that are shared among different proteins and are frequently functionally and structurally independent from the rest of the protein. Novel domain combinations have a major role in evolutionary innovation. However, the relative contributions of the different molecular mechanisms that underlie domain gains in animals are still unknown. By using animal gene phylogenies we were able to identify a set of high confidence domain gain events and by looking at their coding DNA investigate the causative mechanisms.  相似文献   

11.

Background  

The study of functional subfamilies of protein domain families and the identification of the residues which determine substrate specificity is an important question in the analysis of protein domains. One way to address this question is the use of clustering methods for protein sequence data and approaches to predict functional residues based on such clusterings. The locations of putative functional residues in known protein structures provide insights into how different substrate specificities are reflected on the protein structure level.  相似文献   

12.

Background  

Genome size and complexity, as measured by the number of genes or protein domains, is remarkably similar in most extant eukaryotes and generally exhibits no correlation with their morphological complexity. Underlying trends in the evolution of the functional content and capabilities of different eukaryotic genomes might be hidden by simultaneous gains and losses of genes.  相似文献   

13.

Background  

Many protein interactions, especially those involved in signaling, involve short linear motifs consisting of 5-10 amino acid residues that interact with modular protein domains such as the SH3 binding domains and the kinase catalytic domains. One straightforward way of identifying these interactions is by scanning for matches to the motif against all the sequences in a target proteome. However, predicting domain targets by motif sequence alone without considering other genomic and structural information has been shown to be lacking in accuracy.  相似文献   

14.

Background  

It is well known the strong relationship between protein structure and flexibility, on one hand, and biological protein function, on the other hand. Technically, protein flexibility exploration is an essential task in many applications, such as protein structure prediction and modeling. In this contribution we have compared two different approaches to explore the flexibility space of protein domains: i) molecular dynamics (MD-space), and ii) the study of the structural changes within superfamily (SF-space).  相似文献   

15.

Background  

The functional sites of a protein present important information for determining its cellular function and are fundamental in drug design. Accordingly, accurate methods for the prediction of functional sites are of immense value. Most available methods are based on a set of homologous sequences and structural or evolutionary information, and assume that functional sites are more conserved than the average. In the analysis presented here, we have investigated the conservation of location and type of amino acids at functional sites, and compared the behaviour of functional sites between different protein domains.  相似文献   

16.

Background  

The PDZ-LIM proteins are a family of signalling adaptors that interact with the actin cross-linking protein, α-actinin, via their PDZ domains or via internal regions between the PDZ and LIM domains. Three of the PDZ-LIM proteins have a conserved 26-residue ZM motif in the internal region, but the structure of the internal region is unknown.  相似文献   

17.
18.

Background  

Membrane-associated guanylate kinases (MAGUKs) form a family of scaffolding proteins, which are often associated with cellular junctions, such as the vertebrate tight junction, the Drosophila septate junction or the neuromuscular junction. Their capacity to serve as platforms for organising larger protein assemblies results from the presence of several protein-protein interaction domains. They often appear in different variants suggesting that they also mediate dynamic changes in the composition of the complexes.  相似文献   

19.

Background  

We apply a new machine learning method, the so-called Support Vector Machine method, to predict the protein structural class. Support Vector Machine method is performed based on the database derived from SCOP, in which protein domains are classified based on known structures and the evolutionary relationships and the principles that govern their 3-D structure.  相似文献   

20.
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