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Comprehensive characterization of (S)GTP-binding proteins by orthogonal quantitative (S)GTP-affinity profiling and (S)GTP/GTP competition assays.

ABSTRACT: Thiopurine drugs are widely used as antileukemic drugs and immunosuppressive agents, and 6-thioguanosine triphosphate ((S)GTP) is a major metabolite for these drugs. Recent studies have suggested that thiopurine drugs may exert their cytotoxic effects partly through binding of (S)GTP to a GTP-binding protein, Rac1. However, it remains unclear whether (S)GTP can also bind to other cellular proteins. Here, we introduced an orthogonal approach, encompassing nucleotide-affinity profiling and nucleotide-binding competition assays, to characterize comprehensively (S)GTP-binding proteins along with the specific binding sites from the entire human proteome. With the simultaneous use of (S)GTP and GTP affinity probes, we identified 165 (S)GTP-binding proteins that are involved in several different biological processes. We also examined the binding selectivities of these proteins toward (S)GTP and GTP, which allowed for the revelation of the relative binding affinities of the two nucleotides toward the nucleotide-binding motif sequence of proteins. Our results suggest that (S)GTP mainly targets GTPases, with strong binding affinities observed for multiple heterotrimeric G proteins. We also demonstrated that (S)GTP binds to several cyclin-dependent kinases (CDKs), which may perturb the CDK-mediated phosphorylation and cell cycle progression. Together, this represents the first comprehensive characterization of (S)GTP-binding property for the entire human proteome. We reason that a similar strategy can be generally employed for the future characterization of the interaction of other modified nucleotides with the global proteome.

SUBMITTER: Xiao Y

PROVIDER: S-EPMC4014148 | biostudies-other | 2014 May

REPOSITORIES: biostudies-other

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Comprehensive characterization of (S)GTP-binding proteins by orthogonal quantitative (S)GTP-affinity profiling and (S)GTP/GTP competition assays.

Xiao Yongsheng Y Ji Debin D Guo Lei L Wang Yinsheng Y

Analytical chemistry 20140411 9

Thiopurine drugs are widely used as antileukemic drugs and immunosuppressive agents, and 6-thioguanosine triphosphate ((S)GTP) is a major metabolite for these drugs. Recent studies have suggested that thiopurine drugs may exert their cytotoxic effects partly through binding of (S)GTP to a GTP-binding protein, Rac1. However, it remains unclear whether (S)GTP can also bind to other cellular proteins. Here, we introduced an orthogonal approach, encompassing nucleotide-affinity profiling and nucleot ...[more]

PMID: 24689502

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Project description:MotivationRNA binding proteins (RBPs) play important roles in post-transcriptional control of gene expression, including splicing, transport, polyadenylation and RNA stability. To model protein-RNA interactions by considering all available sources of information, it is necessary to integrate the rapidly growing RBP experimental data with the latest genome annotation, gene function, RNA sequence and structure. Such integration is possible by matrix factorization, where current approaches have an undesired tendency to identify only a small number of the strongest patterns with overlapping features. Because protein-RNA interactions are orchestrated by multiple factors, methods that identify discriminative patterns of varying strengths are needed.ResultsWe have developed an integrative orthogonality-regularized nonnegative matrix factorization (iONMF) to integrate multiple data sources and discover non-overlapping, class-specific RNA binding patterns of varying strengths. The orthogonality constraint halves the effective size of the factor model and outperforms other NMF models in predicting RBP interaction sites on RNA. We have integrated the largest data compendium to date, which includes 31 CLIP experiments on 19 RBPs involved in splicing (such as hnRNPs, U2AF2, ELAVL1, TDP-43 and FUS) and processing of 3'UTR (Ago, IGF2BP). We show that the integration of multiple data sources improves the predictive accuracy of retrieval of RNA binding sites. In our study the key predictive factors of protein-RNA interactions were the position of RNA structure and sequence motifs, RBP co-binding and gene region type. We report on a number of protein-specific patterns, many of which are consistent with experimentally determined properties of RBPs.Availability and implementationThe iONMF implementation and example datasets are available at https://github.com/mstrazar/ionmfContact: tomaz.curk@fri.uni-lj.siSupplementary informationSupplementary data are available at Bioinformatics online.

Dataset Information

Comprehensive characterization of (S)GTP-binding proteins by orthogonal quantitative (S)GTP-affinity profiling and (S)GTP/GTP competition assays.

Publications

Comprehensive characterization of (S)GTP-binding proteins by orthogonal quantitative (S)GTP-affinity profiling and (S)GTP/GTP competition assays.

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