Computational Prediction and Experimental Verification of New MAP Kinase Docking Sites and Substrates Including Gli Transcription Factors

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

Systematic discovery of linear binding motifs targeting an ancient protein interaction surface on MAP kinases

Mitogen-activated protein kinases (MAPK) are broadly used regulators of cellular signaling. However, how these enzymes can be involved in such a broad spectrum of physiological functions is not understood. Systematic discovery of MAPK networks both experimentally and in silico has been hindered because MAPKs bind to other proteins with low affinity and mostly in less-characterized disordered regions. We used a structurally consistent model on kinase-docking motif interactions to facilitate the discovery of short functional sites in the structurally flexible and functionally under-explored part of the human proteome and applied experimental tools specifically tailored to detect low-affinity protein-protein interactions for their validation in vitro and in cell-based assays. The combined computational and experimental approach enabled the identification of many novel MAPK-docking motifs that were elusive for other large-scale protein-protein interaction screens. The analysis produced an extensive list of independently evolved linear binding motifs from a functionally diverse set of proteins. These all target, with characteristic binding specificity, an ancient protein interaction surface on evolutionarily related but physiologically clearly distinct three MAPKs (JNK, ERK, and p38). This inventory of human protein kinase binding sites was compared with that of other organisms to examine how kinase-mediated partnerships evolved over time. The analysis suggests that most human MAPK-binding motifs are surprisingly new evolutionarily inventions and newly found links highlight (previously hidden) roles of MAPKs. We propose that short MAPK-binding stretches are created in disordered protein segments through a variety of ways and they represent a major resource for ancient signaling enzymes to acquire new regulatory roles

Bioinformatics Approaches for Predicting Kinase–Substrate Relationships

Protein phosphorylation, catalyzed by protein kinases, is the main posttranslational modification in eukaryotes, regulating essential aspects of cellular function. Using mass spectrometry techniques, a profound knowledge has been achieved in the localization of phosphorylated residues at proteomic scale. Although it is still largely unknown, the protein kinases are responsible for such modifications. To fill this gap, many computational algorithms have been developed, which are capable to predict kinase–substrate relationships. The greatest difficulty for these approaches is to model the complex nature that determines kinase–substrate specificity. The vast majority of predictors is based on the linear primary sequence pattern that surrounds phosphorylation sites. However, in the intracellular environment the protein kinase specificity is influenced by contextual factors, such as protein–protein interactions, substrates co-expression patterns, and subcellular localization. Only recently, the development of phosphorylation predictors has begun to incorporate these variables, significantly improving specificity of these methods. An accurate modeling of kinase–substrate relationships could be the greatest contribution of bioinformatics to understand physiological cell signaling and its pathological impairment

Proteome-wide Screening for Mitogen-Activated Protein Kinase Docking Motifs and Interactors

AbstractProteome-wide screening for mitogen-activated protein kinase docking motifs and interactors Guangda Shi 2021 Kinases catalyze the transfer of phosphate to substrates, a reaction critical for many cellular events. Mitogen-activated protein kinases (MAPKs), including ERK, p38, and JNK, phosphorylate hundreds of substrates, and each plays a pivotal role in distinct processes such as cell growth, survival, differentiation, and apoptosis. To correctly respond to external stimuli, MAPKs use several mechanisms to achieve a high degree of selectivity for their target substrates. A critical aspect of MAPK specificity comes from docking interactions occurring between sites distal from the site of catalysis and short linear sequence motifs located in MAPK interactors. These docking sequences conform to a general motif of ψ(1-3)-X(2-6)-ΦΦ-X-Φ (ψ: basic residue, X: any residue, Φ: hydrophobic residue). However, sites conforming to this motif can nonetheless bind specifically to any of the distinct MAPK subfamilies. MAPK preference for docking sites is therefore coded within sub-motifs falling within the consensus. Here I present yeast-based genetic screens to identify docking sequences selectively binding to either JNK or p38 MAPKs. First, I comprehensively characterized all possible amino acid substitutions with two known docking sites, revealing new information about amino acid residues critical for MAPK binding. Second, I screened for functional p38α and JNK1 binding sequences from the human proteome. I subsequently picked 36 peptide sequences selected in these screens and determined their binding affinity to both p38 and JNK. Over 90% of the peptides showed the predicted binding specificity, thus validating the screen results. I have also validated that hit sequences can serve to recruit MAPKs to phosphorylate protein substrates. Systematic analysis of sequences selected by each MAPK revealed key features conferring MAPK specificity. This work has provided unbiased insights into MAPK substrate specificity, and also suggests new biological processes regulated by MAPKs

Mechanisms acting on Hedgehog-GLI pathway and their therapeutic potential

Hedgehog signaling is crucial for diverse aspects of animal development, essential in regulating many cellular processes and is largely implicated in various forms of human cancer. However, many aspects of Hedgehog signaling are not completely understood. This thesis aims to contribute towards a better understanding of the mechanisms acting on Hedgehog-GLI signaling and explore their possible therapeutic potential. PAPER I. We demonstrate that the small molecule RITA, a p53 activator, downregulates Hedgehog signaling in human medulloblastoma and rhabdomyosarcoma cells via JNK kinase and irrespective of p53. In vitro RITA enhanced the anti-proliferative effects of the GLI antagonist GANT61. RITA was more potent than GANT61 in downregulating Hedgehog-GLI signaling in rhabdomyosarcoma subcutaneous xenograft tumors with the dual drug administration almost completely blocking the Hedgehog signaling response in vivo, suggesting a certain antagonism of the two drugs. Notably, RITA and GANT61 co-administration decreased cell proliferation and elicited a broader response of pathways involved in cancer cell growth, providing a plausible interpretation for tumor reduction in the absence of Hedgehog signaling downregulation. PAPER II. We address the possible therapeutic role of Hedgehog-GLI1 signaling for targeting and prognosis of ER-alpha positive breast cancer. We showed that expression of the Hedgehog signaling effector protein GLI1 is higher in tamoxifen resistant relative to tamoxifen sensitive cells. In both cell types GLI1 depletion mitigated cell proliferation and ER-alpha activity, irrespective of estrogen stimulation. Tamoxifen cytotoxicity was enhanced by GANT61 co-treatment, both in tamoxifen resistant and sensitive breast cancer cells, reflecting a crosstalk between ER-alpha and Hedgehog-GLI1 signaling. We have observed a positive correlation between GLI1 and ER-alpha/ER-alpha target gene expression, while high GLI1 expression was associated with poor distant metastasis-free survival in breast cancer patients. PAPER III. We identified a signature of GLI1 target genes via a combination of RNA-seq analyses of GLI1 overexpression and depletion datasets supplemented with in-depth validation in human cancer cell lines. Additionally, we found that RNA editing of GLI1 can modulate its effects on GLI1 target genes. Markedly, one of the highly upregulated targets, FOXS1, was found to engage in feedback mechanisms limiting the capacity of GLI1 to act as a proliferation factor in medulloblastoma and rhabdomyosarcoma cells. FOXS1 was both highly expressed and positively correlated with GLI1 in SHH medulloblastoma, further arguing for the existence of a FOXS1-GLI1 interplay in human tumors. PAPER IV (Manuscript). In this ongoing work we address the role of circRNAs in the context of Hedgehog signaling activation and Hedgehog-linked SHH medulloblastoma tumors. Via modified RNA-seq protocols we have determined the circRNA transcriptome of Daoy medulloblastoma and human embryonic palatal mesenchyme HEPM cells, following activation of Hedgehog pathway with SHH ligand or Smoothened agonist SAG. In total, 29 selected circRNAs were independently validated by Sanger sequencing and RT-PCR assays. Of these circRNAs, 10 were apparently regulated by Hedgehog signaling activation, however to a much lesser extent compared with known target genes of the pathway, e.g. GLI1 and HHIP. 7 circRNAs had reduced expression in human medulloblastoma tumors in comparison to normal cerebellum, while the linear mRNAs originating from the same genes did not exhibit a reduced expression. These findings highlight distinct regulatory mechanisms acting on the BACH1, CDYL, FKBP8, GLIS1, OGDH, SMARCA5 and ZKSCAN1 circRNAs and deserve further analysis for possible contribution to the development of medulloblastoma

The human Na⁺/H⁺ exchanger 1 is a membrane scaffold protein for extracellular signal-regulated kinase 2

Background Extracellular signal-regulated kinase 2 (ERK2) is an S/T kinase with more than 200 known substrates, and with critical roles in regulation of cell growth and differentiation and currently no membrane proteins have been linked to ERK2 scaffolding. Methods and results Here, we identify the human Na+/H+ exchanger 1 (hNHE1) as a membrane scaffold protein for ERK2 and show direct hNHE1-ERK1/2 interaction in cellular contexts. Using nuclear magnetic resonance (NMR) spectroscopy and immunofluorescence analysis we demonstrate that ERK2 scaffolding by hNHE1 occurs by one of three D-domains and by two non-canonical F-sites located in the disordered intracellular tail of hNHE1, mutation of which reduced cellular hNHE1-ERK1/2 co-localization, as well as reduced cellular ERK1/2 activation. Time-resolved NMR spectroscopy revealed that ERK2 phosphorylated the disordered tail of hNHE1 at six sites in vitro, in a distinct temporal order, with the phosphorylation rates at the individual sites being modulated by the docking sites in a distant dependent manner. Conclusions This work characterizes a new type of scaffolding complex, which we term a “shuffle complex”, between the disordered hNHE1-tail and ERK2, and provides a molecular mechanism for the important ERK2 scaffolding function of the membrane protein hNHE1, which regulates the phosphorylation of both hNHE1 and ERK2

Targeting the Hedgehog Pathway in Pediatric Medulloblastoma

Medulloblastoma (MB), a primitive neuroectomal tumor of the cerebellum, is the most common malignant pediatric brain tumor. The cause of MB is largely unknown, but aberrant activation of Hedgehog (Hh) pathway is responsible for ~30% of MB. Despite aggressive treatment with surgical resection, radiation and chemotherapy, 70%-80% of pediatric medulloblastoma cases can be controlled, but most treated patients suffer devastating side effects. Therefore, developing a new effective treatment strategy is urgently needed. Hh signaling controls transcription of target genes by regulating activities of the three Glioma-associated oncogene (Gli1-3) transcription factors. In this review, we will focus on current clinical treatment options of MB and discuss mechanisms of drug resistance. In addition, we will describe current known molecular pathways which crosstalk with the Hedgehog pathway both in the context of medulloblastoma and non-medulloblastoma cancer development. Finally, we will introduce post-translational modifications that modulate Gli1 activity and summarize the positive and negative regulations of the Hh/Gli1 pathway. Towards developing novel combination therapies for medulloblastoma treatment, current information on interacting pathways and direct regulation of Hh signaling should prove critical

Analysis of the protein-Ligand and protein-peptide interactions using a combined sequence- and structure-based approach

Proteins participate in most of the important processes in cells, and their ability to perform their function ultimately depends on their three-dimensional structure. They usually act in these processes through interactions with other molecules. Because of the importance of their role, proteins are also the common target for small molecule drugs that inhibit their activity, which may include targeting protein interactions. Understanding protein interactions and how they are affected by mutations is thus crucial for combating drug resistance and aiding drug design. This dissertation combines bioinformatics studies of protein interactions at both primary sequence and structural level. We analyse protein-protein interactions through linear motifs, as well as protein-small molecule interactions, and study how mutations affect them. This is done in the context of two systems. In the first study of drug resistance mutations in the protease of the human immunodeficiency virus type 1, we successfully apply molecular dynamics simulations to estimate the effects of known resistance-associated mutations on the free binding energy, also revealing molecular mechanisms of resistance. In the second study, we analyse consensus profiles of linear motifs that mediate the recognition by the mitogen-activated protein kinases of their target proteins. We thus gain insights into the cellular processes these proteins are involved in.Proteine sind an den meisten wichtigen Prozessen in Zellen beteiligt, und ihre Fähigkeit, ihre Funktion zu erfüllen, hängt letztlich von ihrer dreidimensionalen Struktur ab. In diesen Prozessen wirken sie normalerweise durch Wechselwirkungen mit anderen Molekülen. Aufgrund der Bedeutung ihrer Rolle sind Proteine auch die häufigsten Angriffspunkte für niedermolekulare Wirkstoffe, die ihre Aktivität hemmen. Dies kann das Targeting von Proteinwechselwirkungen umfassen. Um Wechselwirkungen mit Medikamenten zu bekämpfen und das Wirkstoffdesign zu unterstützen, ist es wichtig, die Wechselwirkungen zwischen Proteinen und deren Einfluss auf Mutationen zu verstehen. Diese Dissertation kombiniert bioinformatische Studien zu Proteinwechselwirkungen sowohl auf primärer als auch auf struktureller Ebene. Wir analysieren Protein-Protein-Wechselwirkungen anhand linearer Motive sowie Protein-Kleinmolekül-Wechselwirkungen und untersuchen, wie sich Mutationen auf sie auswirken. Dies wird untersucht im Kontext von zwei Systemen. In der ersten Studie zu Resistenzmutationen in der Protease des humanen Immundefizienzvirus Typ 1 haben wir molekulardynamische Simulationen erfolgreich eingesetzt, um die Auswirkungen bekannter Resistenz-assoziierter Mutationen auf die freie Bindungsenergie abzuschätzen und molekulare Resistenzmechanismen aufzuzeigen. In der zweiten Studie analysieren wir Konsensusprofile von linearen Motiven, die die Erkennung der Zielproteine durch die Mitogen-aktivierten Proteinkinasen vermitteln. So gewinnen wir Einblick in die zellulären Prozesse, an denen diese Proteine beteiligt sind

JNK signaling: Regulation and functions based on complex protein-protein partnerships

The c-Jun N-terminal kinases (JNKs), as members of the mitogenactivated protein kinase (MAPK) family, mediate eukaryotic cell responses to a wide range of abiotic and biotic stress insults. JNKs also regulate important physiological processes, including neuronal functions, immunological actions, and embryonic development, via their impact on gene expression, cytoskeletal protein dynamics, and cell death/survival pathways. Although the JNK pathway has been under study for -20 years, its complexity is still perplexing, with multiple protein partners of JNKs underlying the diversity of actions. Here we review the current knowledge of JNK structure and isoforms as well as the partnerships of JNKs with a range of intracellular proteins. Many of these proteins are direct substrates of the JNKs. We analyzed almost 100 of these target proteins in detail within a framework of their classification based on their regulation by JNKs. Examples of these JNK substrates include a diverse assortment of nuclear transcription factors (Jun, ATF2, Myc, Elk1), cytoplasmic proteins involved in cytoskeleton regulation (DCX, Tau, WDR62) or vesicular transport (JIP1, JIP3), cell membrane receptors (BMPR2), and mitochondrial proteins (Mcl1, Bim). In addition, because upstream signaling components impact JNK activity, we critically assessed the involvement of signaling scaffolds and the roles of feedback mechanisms in the JNK pathway. Despite a clarification of many regulatory events in JNK-dependent signaling during the past decade, many other structural and mechanistic insights are just beginning to be revealed. These advances open new opportunities to understand the role of JNK signaling in diverse physiological and pathophysiological states. Copyright © 2016, American Society for Microbiology. All Rights Reserved