The extended protein kinase C superfamily.
Ontology highlight
ABSTRACT:
SUBMITTER: Mellor H
PROVIDER: S-EPMC1219479 | biostudies-other | 1998 Jun
REPOSITORIES: biostudies-other
Similar Datasets
Project description:The protein kinase family is large and important, but it is only one family in a larger superfamily of homologous kinases that phosphorylate a variety of substrates and play important roles in all three superkingdoms of life. We used a carefully constructed structural alignment of selected kinases as the basis for a study of the structural evolution of the protein kinase-like superfamily. The comparison of structures revealed a "universal core" domain consisting only of regions required for ATP binding and the phosphotransfer reaction. Remarkably, even within the universal core some kinase structures display notable changes, while still retaining essential activity. Hence, the protein kinase-like superfamily has undergone substantial structural and sequence revision over long evolutionary timescales. We constructed a phylogenetic tree for the superfamily using a novel approach that allowed for the combination of sequence and structure information into a unified quantitative analysis. When considered against the backdrop of species distribution and other metrics, our tree provides a compelling scenario for the development of the various kinase families from a shared common ancestor. We propose that most of the so-called "atypical kinases" are not intermittently derived from protein kinases, but rather diverged early in evolution to form a distinct phyletic group. Within the atypical kinases, the aminoglycoside and choline kinase families appear to share the closest relationship. These two families in turn appear to be the most closely related to the protein kinase family. In addition, our analysis suggests that the actin-fragmin kinase, an atypical protein kinase, is more closely related to the phosphoinositide-3 kinase family than to the protein kinase family. The two most divergent families, alpha-kinases and phosphatidylinositol phosphate kinases (PIPKs), appear to have distinct evolutionary histories. While the PIPKs probably have an evolutionary relationship with the rest of the kinase superfamily, the relationship appears to be very distant (and perhaps indirect). Conversely, the alpha-kinases appear to be an exception to the scenario of early divergence for the atypical kinases: they apparently arose relatively recently in eukaryotes. We present possible scenarios for the derivation of the alpha-kinases from an extant kinase fold.
| S-EPMC1261164 | biostudies-literature
Project description:BackgroundMost of the many mutations described in human protein kinases are tolerated without significant disruption of the corresponding structures or molecular functions, while some of them have been associated to a variety of human diseases, including cancer. In the last decade, a plethora of computational methods to predict the effect of missense single-nucleotide variants (SNVs) have been developed. Still, current high-throughput sequencing efforts and the concomitant need for massive interpretation of protein sequence variants will demand for more efficient and/or accurate computational methods in the forthcoming years.ResultsWe present KinMut, a support vector machine (SVM) approach, to identify pathogenic mutations in the protein kinase superfamily. KinMut relays on a combination of sequence-derived features that describe mutations at different levels: (1) Gene level: membership to a specific group in Kinbase and the annotation with GO terms; (2) Domain level: annotated PFAM domains; and (3) Residue level: physicochemical features of amino acids, specificity determining positions, and functional annotations from SwissProt and FireDB. The system has been trained with the set of 3492 human kinase mutations in UniProt for which experimental validation of their pathogenic or neutral character exists. In addition, we discuss the relative importance of these independent properties and their combination for the development of a kinase-specific predictor. Finally, we compare KinMut with other state-of-the-art prediction methods.ConclusionsFamily-specific features appear among the most discriminative information sources, which allow us to produce accurate results in a reliable and very simple way with minimal supervision. Our study aims to broaden the knowledge on the mechanisms by which mutations in the human kinome contribute to disease with a particular focus in cancer. The classifier as well as further documentation is available at http://kinmut.bioinfo.cnio.es/.
| S-EPMC3303724 | biostudies-literature
Project description:Protein kinases with a conserved catalytic domain make up one of the largest 'superfamilies' of eukaryotic proteins and play many key roles in biology and disease. Efforts to identify and classify all the members of the eukaryotic protein kinase superfamily have recently culminated in the mining of essentially complete human genome data.
| S-EPMC156577 | biostudies-literature
Project description:BackgroundThe extended light-harvesting complex (LHC) protein superfamily is a centerpiece of eukaryotic photosynthesis, comprising the LHC family and several families involved in photoprotection, like the LHC-like and the photosystem II subunit S (PSBS). The evolution of this complex superfamily has long remained elusive, partially due to previously missing families.ResultsIn this study we present a meticulous search for LHC-like sequences in public genome and expressed sequence tag databases covering twelve representative photosynthetic eukaryotes from the three primary lineages of plants (Plantae): glaucophytes, red algae and green plants (Viridiplantae). By introducing a coherent classification of the different protein families based on both, hidden Markov model analyses and structural predictions, numerous new LHC-like sequences were identified and several new families were described, including the red lineage chlorophyll a/b-binding-like protein (RedCAP) family from red algae and diatoms. The test of alternative topologies of sequences of the highly conserved chlorophyll-binding core structure of LHC and PSBS proteins significantly supports the independent origins of LHC and PSBS families via two unrelated internal gene duplication events. This result was confirmed by the application of cluster likelihood mapping.ConclusionsThe independent evolution of LHC and PSBS families is supported by strong phylogenetic evidence. In addition, a possible origin of LHC and PSBS families from different homologous members of the stress-enhanced protein subfamily, a diverse and anciently paralogous group of two-helix proteins, seems likely. The new hypothesis for the evolution of the extended LHC protein superfamily proposed here is in agreement with the character evolution analysis that incorporates the distribution of families and subfamilies across taxonomic lineages. Intriguingly, stress-enhanced proteins, which are universally found in the genomes of green plants, red algae, glaucophytes and in diatoms with complex plastids, could represent an important and previously missing link in the evolution of the extended LHC protein superfamily.
| S-EPMC3020630 | biostudies-literature
Project description:Gene duplication has been proposed to serve as the engine of evolutionary innovation. It is well recognized that eukaryotic genomes contain a large number of duplicated genes that evolve new functions or expression patterns. However, in mollusks, the evolutionary mechanisms underlying the divergence and the functional maintenance of duplicate genes remain little understood. In the present study, we performed a comprehensive analysis of duplicate genes in the protein kinase superfamily using whole genome and transcriptome data for the Pacific oyster. A total of 64 duplicated gene pairs were identified based on a phylogenetic approach and the reciprocal best BLAST method. By analyzing gene expression from RNA-seq data from 69 different developmental and stimuli-induced conditions (nine tissues, 38 developmental stages, eight dry treatments, seven heat treatments, and seven salty treatments), we found that expression patterns were significantly correlated for a number of duplicate gene pairs, suggesting the conservation of regulatory mechanisms following divergence. Our analysis also identified a subset of duplicate gene pairs with very high expression divergence, indicating that these gene pairs may have been subjected to transcriptional subfunctionalization or neofunctionalization after the initial duplication events. Further analysis revealed a significant correlation between expression and sequence divergence (as revealed by synonymous or nonsynonymous substitution rates) under certain conditions. Taken together, these results provide evidence for duplicate gene sequence and expression divergence in the Pacific oyster, accompanying its adaptation to harsh environments. Our results provide new insights into the evolution of duplicate genes and their expression levels in the Pacific oyster.
| S-EPMC4573066 | biostudies-literature
Project description:Protein kinases have been implicated in the regulation of many processes that guide pathogen development throughout the course of infection. A survey of the Sclerotinia sclerotiorum genome for genes encoding proteins containing the highly conserved eukaryotic protein kinase (ePK) domain, the largest protein kinase superfamily, revealed 92 S. sclerotiorum ePKs. This review examines the composition of the S. sclerotiorum ePKs based on conserved motifs within the ePK domain family, and relates this to orthologues found in other filamentous fungi and yeasts. The ePKs are also discussed in terms of their proposed role(s) in aspects of host pathogenesis, including the coordination of mycelial growth/development and deployment of pathogenicity determinants in response to environmental stimuli, nutrients and stress.
| S-EPMC6638376 | biostudies-literature
Project description:The association between aberrant signal processing by protein kinases and human diseases such as cancer was established long time ago. However, understanding the link between sequence variants in the protein kinase superfamily and the mechanistic complex traits at the molecular level remains challenging: cells tolerate most genomic alterations and only a minor fraction disrupt molecular function sufficiently and drive disease.KinMutRF is a novel random-forest method to automatically identify pathogenic variants in human kinases. Twenty six decision trees implemented as a random forest ponder a battery of features that characterize the variants: a) at the gene level, including membership to a Kinbase group and Gene Ontology terms; b) at the PFAM domain level; and c) at the residue level, the types of amino acids involved, changes in biochemical properties, functional annotations from UniProt, Phospho.ELM and FireDB. KinMutRF identifies disease-associated variants satisfactorily (Acc: 0.88, Prec:0.82, Rec:0.75, F-score:0.78, MCC:0.68) when trained and cross-validated with the 3689 human kinase variants from UniProt that have been annotated as neutral or pathogenic. All unclassified variants were excluded from the training set. Furthermore, KinMutRF is discussed with respect to two independent kinase-specific sets of mutations no included in the training and testing, Kin-Driver (643 variants) and Pon-BTK (1495 variants). Moreover, we provide predictions for the 848 protein kinase variants in UniProt that remained unclassified. A public implementation of KinMutRF, including documentation and examples, is available online ( http://kinmut2.bioinfo.cnio.es ). The source code for local installation is released under a GPL version 3 license, and can be downloaded from https://github.com/Rbbt-Workflows/KinMut2 .KinMutRF is capable of classifying kinase variation with good performance. Predictions by KinMutRF compare favorably in a benchmark with other state-of-the-art methods (i.e. SIFT, Polyphen-2, MutationAssesor, MutationTaster, LRT, CADD, FATHMM, and VEST). Kinase-specific features rank as the most elucidatory in terms of information gain and are likely the improvement in prediction performance. This advocates for the development of family-specific classifiers able to exploit the discriminatory power of features unique to individual protein families.
| S-EPMC4928150 | biostudies-literature
Project description:Kinases of the eukaryotic protein kinase superfamily are key regulators of most aspects eukaryotic cellular behavior and have provided several drug targets including kinases dysregulated in cancers. The rapid increase in the number of genomic sequences has created an acute need to identify and classify members of this important class of enzymes efficiently and accurately.Kinannote produces a draft kinome and comparative analyses for a predicted proteome using a single line command, and it is currently the only tool that automatically classifies protein kinases using the controlled vocabulary of Hanks and Hunter [Hanks and Hunter (1995)]. A hidden Markov model in combination with a position-specific scoring matrix is used by Kinannote to identify kinases, which are subsequently classified using a BLAST comparison with a local version of KinBase, the curated protein kinase dataset from www.kinase.com. Kinannote was tested on the predicted proteomes from four divergent species. The average sensitivity and precision for kinome retrieval from the test species are 94.4 and 96.8%. The ability of Kinannote to classify identified kinases was also evaluated, and the average sensitivity and precision for full classification of conserved kinases are 71.5 and 82.5%, respectively. Kinannote has had a significant impact on eukaryotic genome annotation, providing protein kinase annotations for 36 genomes made public by the Broad Institute in the period spanning 2009 to the present.Kinannote is freely available at http://sourceforge.net/projects/kinannote.
| S-EPMC3777111 | biostudies-literature
Project description:Aberrant regulation of metabolic kinases by altered redox homeostasis substantially contributes to aging and various diseases, such as diabetes. We found that the catalytic activity of a conserved family of fructosamine-3-kinases (FN3Ks), which are evolutionarily related to eukaryotic protein kinases, is regulated by redox-sensitive cysteine residues in the kinase domain. The crystal structure of the FN3K homolog from Arabidopsis thaliana revealed that it forms an unexpected strand-exchange dimer in which the ATP-binding P-loop and adjoining β strands are swapped between two chains in the dimer. This dimeric configuration is characterized by strained interchain disulfide bonds that stabilize the P-loop in an extended conformation. Mutational analysis and solution studies confirmed that the strained disulfides function as redox "switches" to reversibly regulate the activity and dimerization of FN3K. Human FN3K, which contains an equivalent P-loop Cys, was also redox sensitive, whereas ancestral bacterial FN3K homologs, which lack a P-loop Cys, were not. Furthermore, CRISPR-mediated knockout of FN3K in human liver cancer cells altered the abundance of redox metabolites, including an increase in glutathione. We propose that redox regulation evolved in FN3K homologs in response to changing cellular redox conditions. Our findings provide insights into the origin and evolution of redox regulation in the protein kinase superfamily and may open new avenues for targeting human FN3K in diabetic complications.
| S-EPMC8455029 | biostudies-literature
Project description:The SET-domain protein methyltransferase superfamily includes all but one of the proteins known to methylate histones on lysine. Histone methylation is important in the regulation of chromatin and gene expression.
| S-EPMC1273623 | biostudies-literature