SENTRA, a database of signal transduction proteins

Maltsev, Natalia; Marland, Elizabeth; Yu, Guoying Karen; Bhatnagar, Saurabha; Lusk, Richard W.

doi:10.1093/nar/28.1.335

Cited by 15 publications

(3 citation statements)

References 6 publications

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“…Sequence analysis of these prokaryotic Ser/Thr kinases depicts that these are distantly related to eukaryotic protein kinase superfamily [44] . Apart from KinG, SENTRA [45] , [46] , [47] which is a manually curated database provides information on signal transduction proteins. SENTRA has information for Two-component histidine kinases and response regulators, Serine/Threonine protein kinases and protein phosphatases, as well as adenylate and diguanylate cyclases and c-di-GMP phosphodiesterases from 202 completely sequenced prokaryotic genomes.…”

Section: Introductionmentioning

confidence: 99%

A Framework for Classification of Prokaryotic Protein Kinases

2010

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BackgroundOverwhelming majority of the Serine/Threonine protein kinases identified by gleaning archaeal and eubacterial genomes could not be classified into any of the well known Hanks and Hunter subfamilies of protein kinases. This is owing to the development of Hanks and Hunter classification scheme based on eukaryotic protein kinases which are highly divergent from their prokaryotic homologues. A large dataset of prokaryotic Serine/Threonine protein kinases recognized from genomes of prokaryotes have been used to develop a classification framework for prokaryotic Ser/Thr protein kinases.Methodology/Principal FindingsWe have used traditional sequence alignment and phylogenetic approaches and clustered the prokaryotic kinases which represent 72 subfamilies with at least 4 members in each. Such a clustering enables classification of prokaryotic Ser/Thr kinases and it can be used as a framework to classify newly identified prokaryotic Ser/Thr kinases. After series of searches in a comprehensive sequence database we recognized that 38 subfamilies of prokaryotic protein kinases are associated to a specific taxonomic level. For example 4, 6 and 3 subfamilies have been identified that are currently specific to phylum proteobacteria, cyanobacteria and actinobacteria respectively. Similarly subfamilies which are specific to an order, sub-order, class, family and genus have also been identified. In addition to these, we also identify organism-diverse subfamilies. Members of these clusters are from organisms of different taxonomic levels, such as archaea, bacteria, eukaryotes and viruses.Conclusion/SignificanceInterestingly, occurrence of several taxonomic level specific subfamilies of prokaryotic kinases contrasts with classification of eukaryotic protein kinases in which most of the popular subfamilies of eukaryotic protein kinases occur diversely in several eukaryotes. Many prokaryotic Ser/Thr kinases exhibit a wide variety of modular organization which indicates a degree of complexity and protein-protein interactions in the signaling pathways in these microbes.

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Section: Introductionmentioning

confidence: 99%

A Framework for Classification of Prokaryotic Protein Kinases

2010

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“…Progress in understanding of prokaryotic signal transduction systems, as well as availability of a large number of newly sequenced genomes, prompted us to perform a major update of Sentra (), a database of signal transduction proteins developed by the Bioinformatics group at Argonne National Laboratory (13,14). The objective of further development of Sentra was to provide users with an analytical environment containing expert-curated information describing prokaryotic signal transduction systems, as well as up-to-date knowledge base and interactive analytical tools for further analysis of signal transduction proteins in all completely sequenced genomes as they become publicly available.…”

Section: Introductionmentioning

confidence: 99%

Sentra: a database of signal transduction proteins for comparative genome analysis

D’Souza¹,

Glass²,

Syed³

et al. 2007

Nucleic Acids Research

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Sentra (), a database of signal transduction proteins encoded in completely sequenced prokaryotic genomes, has been updated to reflect recent advances in understanding signal transduction events on a whole-genome scale. Sentra consists of two principal components, a manually curated list of signal transduction proteins in 202 completely sequenced prokaryotic genomes and an automatically generated listing of predicted signaling proteins in 235 sequenced genomes that are awaiting manual curation. In addition to two-component histidine kinases and response regulators, the database now lists manually curated Ser/Thr/Tyr protein kinases and protein phosphatases, as well as adenylate and diguanylate cyclases and c-di-GMP phosphodiesterases, as defined in several recent reviews. All entries in Sentra are extensively annotated with relevant information from public databases (e.g. UniProt, KEGG, PDB and NCBI). Sentra's infrastructure was redesigned to support interactive cross-genome comparisons of signal transduction capabilities of prokaryotic organisms from a taxonomic and phenotypic perspective and in the framework of signal transduction pathways from KEGG. Sentra leverages the PUMA2 system to support interactive analysis and annotation of signal transduction proteins by the users.

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“…(11)(12)(13)(14)) and the availability of extensive databases cataloging genes, proteins, and metabolic pathways (cf. (15)(16)(17)(18)), we are no longer limited by the availability of experimental data. The challenge, rather, is to interpret and integrate all of the data available.…”

Section: Introductionmentioning

confidence: 99%

Control Motifs for Intracellular Regulatory Networks

Rao

Arkin

2001

Annu. Rev. Biomed. Eng.

110

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A number of technological innovations are yielding unprecedented data on the networks of biochemical, genetic, and biophysical reactions that underlie cellular behavior and failure. These networks are composed of hundreds to thousands of chemical species and structures, interacting via nonlinear and possibly stochastic physical processes. A central goal of modern biology is to optimally use the data on these networks to understand how their design leads to the observed cellular behaviors and failures. Ultimately, this knowledge should enable cellular engineers to redesign cellular processes to meet industrial needs (such as optimal natural product synthesis), aid in choosing the most effective targets for pharmaceuticals, and tailor treatment for individual genotypes. The size and complexity of these networks and the inevitable lack of complete data, however, makes reaching these goals extremely difficult. If it proves possible to modularize these networks into functional subnetworks, then these smaller networks may be amenable to direct analysis and might serve as regulatory motifs. These motifs, recurring elements of control, may help to deduce the structure and function of partially known networks and form the basis for fulfilling the goals described above. A number of approaches to identifying and analyzing control motifs in intracellular networks are reviewed.

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SENTRA, a database of signal transduction proteins

Cited by 15 publications

References 6 publications

A Framework for Classification of Prokaryotic Protein Kinases

A Framework for Classification of Prokaryotic Protein Kinases

Sentra: a database of signal transduction proteins for comparative genome analysis

Control Motifs for Intracellular Regulatory Networks

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