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Improved strategy for the curation and classification of kinases, with broad applicability to other eukaryotic protein groups.

ABSTRACT: Despite the substantial amount of genomic and transcriptomic data available for a wide range of eukaryotic organisms, most genomes are still in a draft state and can have inaccurate gene predictions. To gain a sound understanding of the biology of an organism, it is crucial that inferred protein sequences are accurately identified and annotated. However, this can be challenging to achieve, particularly for organisms such as parasitic worms (helminths), as most gene prediction approaches do not account for substantial phylogenetic divergence from model organisms, such as Caenorhabditis elegans and Drosophila melanogaster, whose genomes are well-curated. In this paper, we describe a bioinformatic strategy for the curation of gene families and subsequent annotation of encoded proteins. This strategy relies on pairwise gene curation between at least two closely related species using genomic and transcriptomic data sets, and is built on recent work on kinase complements of parasitic worms. Here, we discuss salient technical aspects of this strategy and its implications for the curation of protein families more generally.

SUBMITTER: Stroehlein AJ

PROVIDER: S-EPMC5931623 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Improved strategy for the curation and classification of kinases, with broad applicability to other eukaryotic protein groups.

Stroehlein Andreas J AJ Young Neil D ND Gasser Robin B RB

Scientific reports 20180501 1

Despite the substantial amount of genomic and transcriptomic data available for a wide range of eukaryotic organisms, most genomes are still in a draft state and can have inaccurate gene predictions. To gain a sound understanding of the biology of an organism, it is crucial that inferred protein sequences are accurately identified and annotated. However, this can be challenging to achieve, particularly for organisms such as parasitic worms (helminths), as most gene prediction approaches do not a ...[more]

PMID: 29717207

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Project description:BACKGROUND: The Apicomplexa constitute an evolutionarily divergent phylum of protozoan pathogens responsible for widespread parasitic diseases such as malaria and toxoplasmosis. Many cellular functions in these medically important organisms are controlled by protein kinases, which have emerged as promising drug targets for parasitic diseases. However, an incomplete understanding of how apicomplexan kinases structurally and mechanistically differ from their host counterparts has hindered drug development efforts to target parasite kinases. RESULTS: We used the wealth of sequence data recently made available for 15 apicomplexan species to identify the kinome of each species and quantify the evolutionary constraints imposed on each family of apicomplexan kinases. Our analysis revealed lineage-specific adaptations in selected families, namely cyclin-dependent kinase (CDK), calcium-dependent protein kinase (CDPK) and CLK/LAMMER, which have been identified as important in the pathogenesis of these organisms. Bayesian analysis of selective constraints imposed on these families identified the sequence and structural features that most distinguish apicomplexan protein kinases from their homologs in model organisms and other eukaryotes. In particular, in a subfamily of CDKs orthologous to Plasmodium falciparum crk-5, the activation loop contains a novel PTxC motif which is absent from all CDKs outside Apicomplexa. Our analysis also suggests a convergent mode of regulation in a subset of apicomplexan CDPKs and mammalian MAPKs involving a commonly conserved arginine in the ?C helix. In all recognized apicomplexan CLKs, we find a set of co-conserved residues involved in substrate recognition and docking that are distinct from metazoan CLKs. CONCLUSIONS: We pinpoint key conserved residues that can be predicted to mediate functional differences from eukaryotic homologs in three identified kinase families. We discuss the structural, functional and evolutionary implications of these lineage-specific variations and propose specific hypotheses for experimental investigation. The apicomplexan-specific kinase features reported in this study can be used in the design of selective kinase inhibitors.

Project description:Schistosomiasis remains an important parasitic disease and a major economic problem in many countries. The Schistosoma mansoni genome and predicted proteome sequences were recently published providing the opportunity to identify new drug candidates. Eukaryotic protein kinases (ePKs) play a central role in mediating signal transduction through complex networks and are considered druggable targets from the medical and chemical viewpoints. Our work aimed at analyzing the S. mansoni predicted proteome in order to identify and classify all ePKs of this parasite through combined computational approaches. Functional annotation was performed mainly to yield insights into the parasite signaling processes relevant to its complex lifestyle and to select some ePKs as potential drug targets.We have identified 252 ePKs, which corresponds to 1.9% of the S. mansoni predicted proteome, through sequence similarity searches using HMMs (Hidden Markov Models). Amino acid sequences corresponding to the conserved catalytic domain of ePKs were aligned by MAFFT and further used in distance-based phylogenetic analysis as implemented in PHYLIP. Our analysis also included the ePK homologs from six other eukaryotes. The results show that S. mansoni has proteins in all ePK groups. Most of them are clearly clustered with known ePKs in other eukaryotes according to the phylogenetic analysis. None of the ePKs are exclusively found in S. mansoni or belong to an expanded family in this parasite. Only 16 S. mansoni ePKs were experimentally studied, 12 proteins are predicted to be catalytically inactive and approximately 2% of the parasite ePKs remain unclassified. Some proteins were mentioned as good target for drug development since they have a predicted essential function for the parasite.Our approach has improved the functional annotation of 40% of S. mansoni ePKs through combined similarity and phylogenetic-based approaches. As we continue this work, we will highlight the biochemical and physiological adaptations of S. mansoni in response to diverse environments during the parasite development, vector interaction, and host infection.

Project description: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.

Dataset Information

Improved strategy for the curation and classification of kinases, with broad applicability to other eukaryotic protein groups.

Publications

Improved strategy for the curation and classification of kinases, with broad applicability to other eukaryotic protein groups.

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