Dataset Information

GeneSpeed: protein domain organization of the transcriptome.

ABSTRACT: The GeneSpeed database (http://genespeed.uchsc.edu/) is an online database and resource tool facilitating the detailed study of protein domain homology in the transcriptomes of Homo sapiens, Mus musculus, Drosophila melanogaster and Caenorhabditis elegans. The population schema for the GeneSpeed database takes advantage of HOWARD parallel cluster technology (http://www.massivelyparallel.com/) and performs exhaustive tBLASTn searches covering all pre-assigned PFAM domain classes in all species (currently 7973 domain families) against the respective Unigene EST databases of the selected four transcriptomes. The resulting database provides a complete annotation of presumed protein domain presence for each Unigene cluster. To complement this domain annotation we have also performed a custom transcription factor-family curation of all Pfam domains, incorporated the Gene Ontology classifications for these domains as well as integrated the Novartis SymAtlas2 dataset for both human and mouse which provides rapid and easy access to tissue-based expression analysis. Consequently, the GeneSpeed database provides the user with the capability to browse or search the database by any of these specialized criteria as well as more traditional means (gene identifier, gene symbol, etc.), thereby enabling a supervised analysis of gene families through a top-down hierarchical basis defined by domain content, all directly linked to an optimized gene expression dataset.

SUBMITTER: Kutchma A

PROVIDER: S-EPMC1716729 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Domains are the building blocks of proteins and play a crucial role in protein-protein interactions. Here, we propose a new approach for the analysis and prediction of domain-domain interfaces. Our method, which relies on the representation of domains as residue-interacting networks, finds an optimal decomposition of domain structures into modules. The resulting modules comprise highly cooperative residues, which exhibit few connections with other modules. We found that non-overlapping binding sites in a domain, involved in different domain-domain interactions, are generally contained in different modules. This observation indicates that our modular decomposition is able to separate protein domains into regions with specialized functions. Our results show that modules with high modularity values identify binding site regions, demonstrating the predictive character of modularity. Furthermore, the combination of modularity with other characteristics, such as sequence conservation or surface patches, was found to improve our predictions. In an attempt to give a physical interpretation to the modular architecture of domains, we analyzed in detail six examples of protein domains with available experimental binding data. The modular configuration of the TEM1-beta-lactamase binding site illustrates the energetic independence of hotspots located in different modules and the cooperativity of those sited within the same modules. The energetic and structural cooperativity between intramodular residues is also clearly shown in the example of the chymotrypsin inhibitor, where non-binding site residues have a synergistic effect on binding. Interestingly, the binding site of the T cell receptor beta chain variable domain 2.1 is contained in one module, which includes structurally distant hot regions displaying positive cooperativity. These findings support the idea that modules possess certain functional and energetic independence. A modular organization of binding sites confers robustness and flexibility to the performance of the functional activity, and facilitates the evolution of protein interactions.

Project description:Because regions on the messenger ribonucleic acid differ in the rate at which they are translated by the ribosome and because proteins can fold cotranslationally on the ribosome, a question arises as to whether the kinetics of translation influence the folding events in the growing nascent polypeptide chain. Translationally slow regions were identified on mRNAs for a set of 37 multidomain proteins from Escherichia coli with known three-dimensional structures. The frequencies of individual codons in mRNAs of highly expressed genes from E. coli were taken as a measure of codon translation speed. Analysis of codon usage in slow regions showed a consistency with the experimentally determined translation rates of codons; abundant codons that are translated with faster speeds compared with their synonymous codons were found to be avoided; rare codons that are translated at an unexpectedly higher rate were also found to be avoided in slow regions. The statistical significance of the occurrence of such slow regions on mRNA spans corresponding to the oligopeptide domain termini and linking regions on the encoded proteins was assessed. The amino acid type and the solvent accessibility of the residues coded by such slow regions were also examined. The results indicated that protein domain boundaries that mark higher-order structural organization are largely coded by translationally slow regions on the RNA and are composed of such amino acids that are stickier to the ribosome channel through which the synthesized polypeptide chain emerges into the cytoplasm. The translationally slow nucleotide regions on mRNA possess the potential to form hairpin secondary structures and such structures could further slow the movement of ribosome. The results point to an intriguing correlation between protein synthesis machinery and in vivo protein folding. Examination of available mutagenic data indicated that the effects of some of the reported mutations were consistent with our hypothesis.

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GeneSpeed: protein domain organization of the transcriptome.

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