The application of modular protein domains in proteomics

Jadwin, Joshua A.; Ogiue-Ikeda, Mari; Machida, Kazuya

doi:10.1016/j.febslet.2012.04.019

Cited by 39 publications

(40 citation statements)

References 163 publications

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“…Jadwin et al termed this "domainomics” [182]. In particular, applications of phosphotyrosine-recognition domains have been reported for therapeutic and diagnostic purposes.…”

Section: Introductionmentioning

confidence: 99%

Phosphotyrosine recognition domains: the typical, the atypical and the versatile

et al. 2012

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SH2 domains are long known prominent players in the field of phosphotyrosine recognition within signaling protein networks. However, over the years they have been joined by an increasing number of other protein domain families that can, at least with some of their members, also recognise pTyr residues in a sequence-specific context. This superfamily of pTyr recognition modules, which includes substantial fractions of the PTB domains, as well as much smaller, or even single member fractions like the HYB domain, the PKCδ and PKCθ C2 domains and RKIP, represents a fascinating, medically relevant and hence intensely studied part of the cellular signaling architecture of metazoans. Protein tyrosine phosphorylation clearly serves a plethora of functions and pTyr recognition domains are used in a similarly wide range of interaction modes, which encompass, for example, partner protein switching, tandem recognition functionalities and the interaction with catalytically active protein domains. If looked upon closely enough, virtually no pTyr recognition and regulation event is an exact mirror image of another one in the same cell. Thus, the more we learn about the biology and ultrastructural details of pTyr recognition domains, the more does it become apparent that nature cleverly combines and varies a few basic principles to generate a sheer endless number of sophisticated and highly effective recognition/regulation events that are, under normal conditions, elegantly orchestrated in time and space. This knowledge is also valuable when exploring pTyr reader domains as diagnostic tools, drug targets or therapeutic reagents to combat human diseases.

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“…Jadwin et al termed this "domainomics” [182]. In particular, applications of phosphotyrosine-recognition domains have been reported for therapeutic and diagnostic purposes.…”

Section: Introductionmentioning

confidence: 99%

Phosphotyrosine recognition domains: the typical, the atypical and the versatile

et al. 2012

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“…Moreover, the usage of these tools in EvoProDom provides a general method to obtain protein domain content and orthologous protein annotation. This method may be applicable to other research fields such as proteomics (9), protein design (10) and host-virus interactions (11). Thus, EvoProDom presents a novel model for protein evolution based on “mix and merge” of protein domains rather than DNA based models.…”

Section: Discussionmentioning

confidence: 99%

“…By applying these protein sequence-based methods to obtain protein domain content and orthologous protein annotation, new organisms were easily added to EvoProDom. Moreover, this method is unique to EvoProDom and is applicable to other protein domain-based applications such as proteomics (9), protein design (10) and host-virus interactions (11).…”

Section: Methodsmentioning

confidence: 99%

“…We presented in EvoProDom, a general method to obtain protein domain content and orthologous protein annotation, by predicting these data from protein sequences using the Pfam search tool (6, 7) and KoFamKOALA (8), respectively. This method can be implemented in other research fields such as proteomics (9), protein design (10) and host-virus interactions (11).…”

Section: Introductionmentioning

confidence: 99%

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EvoProDom: Evolutionary model of protein families by means of translocations of protein domains

Carmi

Gorohovski

Frenkel‐Morgenstern

2020

Preprint

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† These authors contributed equally to this work. AbstractHere, we developed a novel evolution of protein domains (EvoProDom) model for evolution of proteins, which was based on mix and merge of protein domains. We collected and integrated genomic and proteome data for 109 organisms. These data include protein domain content and orthologous protein families. In EvoProDom, we defined evolutionary events, such as translocations, as reciprocal exchanges of protein domains between orthologous proteins of different organisms. We found that protein domains, which frequently appear in translocation events, were enriched in trans-splicing events, i.e., producing novel transcripts fused from two distinct genes. We presented in EvoProDom, a general method to obtain protein domain content and orthologous protein annotation, by predicting these data from protein sequences using the Pfam search tool and KoFamKOALA, respectively. This method can be implemented in other research such as proteomics, protein design and host-virus interactions.We hypothesized that proteins evolve by means of "mix and merge" or "shuffling" of 113 protein domains, which are distinct functional units (1, 20). The evolutionary model that 114 7 described protein evolution by means of protein domain dynamics was termed 115EvoProDom. The EvoProDom model defined and formulated standard evolutionary 116 mechanisms such as translocations, duplications and indel (insertion and deletion) events, 117 which acted on protein domains that were realized as Pfam domains (6, 7). Therefore, 118proteins, under the EvoProDom model, gained or lost their function based on the 119 presence or absence of respective function-conferring domains. Accordingly, proteins 120 were modeled as sets of protein domains; and evolutionary events, such as translocations, 121 were defined. These describe the gain and loss of particular domains between domain sets 122 or DAs. The KEGG database catalogs diverse taxa and forms groups of orthologous 123 proteins (KO) based on shared function. Thus, all members of the KO group were 124 orthologous proteins (8, 12, 13). Additionally, in the EvoProDom model, proteins were 125 assigned to KO groups (see Materials and Methods). Consequently, translocation events 126 were mapped to groups of organisms according to underlying changes in DA. Thus, 127 evolutionary events, which acted upon domains and manifested as changes in DA were 128 reflected at the organism level. A link between changes at these two levels was therefore 129 established. The EvoProDom model was implemented with and tested on EvoProDomDB 130 (see Materials and Methods). In total, 5,548 translocation events, involving 94 protein 131 super families, excluding an "unknown" super family, were found ( Table 2). This result 132 indicates the existence of multiple evolutionary translocation events as defined by the 133 model. 134Mapping of genes to proteins and alternative splicing 135 EvoProDom combined genomic information (genes) with proteins, and in turn, proteins 136 with Pfam doma...

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“…The availability of complete genome sequences for many organisms, coupled with a vast increase in the number of proteomic and protein-interaction data sets, have facilitated a broader perspective on modular binding domains and their role in signalling; the field has transitioned from 'discovery mode' to an appreciation of the full range and scope of the interactions that are mediated by modular domains 82 . We know roughly how many of each class of domain are present in various organisms and in how many different proteins they are found (see the figure, part a, for key examples).…”

Section: Box 1 | Domainomicsmentioning

confidence: 99%

The discovery of modular binding domains: building blocks of cell signalling

Mayer

2015

Nat Rev Mol Cell Biol

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Cell signalling - the ability of a cell to process information from the environment and change its behaviour in response - is a central property of life. Signalling depends on proteins that are assembled from a toolkit of modular domains, each of which confers a specific activity or function. The discovery of modular protein- and lipid-binding domains was a crucial turning point in understanding the logic and evolution of signalling mechanisms.

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The application of modular protein domains in proteomics

Cited by 39 publications

References 163 publications

Phosphotyrosine recognition domains: the typical, the atypical and the versatile

Phosphotyrosine recognition domains: the typical, the atypical and the versatile

EvoProDom: Evolutionary model of protein families by means of translocations of protein domains

The discovery of modular binding domains: building blocks of cell signalling

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