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Computational prediction and experimental verification of new MAP kinase docking sites and substrates including Gli transcription factors.

ABSTRACT: In order to fully understand protein kinase networks, new methods are needed to identify regulators and substrates of kinases, especially for weakly expressed proteins. Here we have developed a hybrid computational search algorithm that combines machine learning and expert knowledge to identify kinase docking sites, and used this algorithm to search the human genome for novel MAP kinase substrates and regulators focused on the JNK family of MAP kinases. Predictions were tested by peptide array followed by rigorous biochemical verification with in vitro binding and kinase assays on wild-type and mutant proteins. Using this procedure, we found new 'D-site' class docking sites in previously known JNK substrates (hnRNP-K, PPM1J/PP2Czeta), as well as new JNK-interacting proteins (MLL4, NEIL1). Finally, we identified new D-site-dependent MAPK substrates, including the hedgehog-regulated transcription factors Gli1 and Gli3, suggesting that a direct connection between MAP kinase and hedgehog signaling may occur at the level of these key regulators. These results demonstrate that a genome-wide search for MAP kinase docking sites can be used to find new docking sites and substrates.

SUBMITTER: Whisenant TC

PROVIDER: S-EPMC2928751 | biostudies-literature | 2010 Aug

REPOSITORIES: biostudies-literature

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Computational prediction and experimental verification of new MAP kinase docking sites and substrates including Gli transcription factors.

Whisenant Thomas C TC Ho David T DT Benz Ryan W RW Rogers Jeffrey S JS Kaake Robyn M RM Gordon Elizabeth A EA Huang Lan L Baldi Pierre P Bardwell Lee L

PLoS computational biology 20100826 8

In order to fully understand protein kinase networks, new methods are needed to identify regulators and substrates of kinases, especially for weakly expressed proteins. Here we have developed a hybrid computational search algorithm that combines machine learning and expert knowledge to identify kinase docking sites, and used this algorithm to search the human genome for novel MAP kinase substrates and regulators focused on the JNK family of MAP kinases. Predictions were tested by peptide array f ...[more]

PMID: 20865152

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Project description:BackgroundOxidative stress (OS) is one of the major causes of ovarian aging and dysfunction. Indole-3-propionic acid (IPA) is an indole compound derived from tryptophan with free radical scavenging and antioxidant properties, and thus may have potential applications in protecting ovarian function, although the exact mechanisms are unknown. This study aims to preliminarily elucidate the potential mechanisms of IPA that benefit ovarian reserve function through network pharmacology, molecular docking, and experimental verification.MethodsThe related protein targets of IPA were searched on SwissTargetPrediction, TargetNet, BATMAN-TCM, and PharmMapper databases. The potential targets of diminished ovarian reserve (DOR) were identified from OMIM, GeneCards, DrugBank, and DisGeNET databases. The common targets were uploaded directly to the STRING database to construct PPI networks. We then performed GO and KEGG enrichment analysis on the targets. Subsequently, molecular docking and molecular dynamics simulation were used to validate the binding conformation of IPA to candidate targets. Furthermore, we carried out in vitro experiments to validate the prediction results of network pharmacology.ResultsWe identified a total of 61 potential targets for the interaction of IPA with DOR. The PPI network topological parameter analysis yielded 13 hub genes for DOR treatment. The GO biological process enrichment analysis identified 293 entries, mainly enriched in aging, signal transduction, response to hypoxia, negative regulation of apoptotic process, and positive regulation of cell proliferation. The KEGG enrichment analysis mainly included lipid and atherosclerosis, progesterone-mediated oocyte maturation, AGE-RAGE, relaxin, estrogen, and other signaling pathways. The molecular docking further revealed the direct binding of IPA with six hub proteins including NOS3, AKT1, EGFR, PPARA, SRC, and TNF. In vitro experiments showed that IPA pretreatment attenuated H2O2-induced cellular oxidative stress damage, while IPA exerted cytoprotective and antioxidant damage effects by regulating the six hub genes and antioxidant proteins.ConclusionWe systematically illustrated the potential protective effects of IPA against DOR through multiple targets and pathways using network pharmacology, and further verified the cytoprotective effect and antioxidant properties of IPA through in vitro experiments. These findings provide new insights into the targets and molecular mechanisms whereby IPA improves DOR.

Dataset Information

Computational prediction and experimental verification of new MAP kinase docking sites and substrates including Gli transcription factors.

Publications

Computational prediction and experimental verification of new MAP kinase docking sites and substrates including Gli transcription factors.

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