Allosteric regulation of glycogen synthase kinase 3β: a theoretical study

Estrogen Enhances FDFT1 Expression in Theca Cells of Chicken Hierarchical Ovarian Follicles by Increasing LSD1Ser54p Level Through GSK3β Phosphorylation at 216th Tyrosine

The development of chicken ovarian follicles involves two key stages of primordial follicle recruitment and follicle selection that are tightly regulated by multiple reproductive hormones and cytokines. Our previous study revealed an estrogen-stimulated increase in the phosphorylation level of serine at position 54 of lysine demethylase 1A (LSD1Ser54p) in the theca cells of chicken hierarchical ovarian follicles (Post-TCs). In this study, we further found that the upregulation of LSD1Ser54p by estrogen was performed by glycogen synthase kinase 3 beta (GSK3β) and that GSK3β promoted LSD1Ser54p levels by directly binding to the SWIRM and AOL1 domains of LSD1. Upon estrogen stimulation, the phosphorylation level of tyrosine at position 216 of GSK3β (GSK3βTyr216p) increased, which enhanced the binding between LSD1 and GSK3β. The subsequent transcriptome sequencing on chicken Post-TCs treated with estrogen and CUT&RUN sequencing against the LSD1Ser54p protein revealed that the expression of the farnesyl-diphosphate farnesyltransferase 1 (FDFT1) gene was simultaneously upregulated by estrogen, GSK3β, and LSD1Ser54p. Moreover, the overexpression of FDFT1 further promoted cholesterol biosynthesis in chicken Post-TCs. In short, the findings of this study suggest that estrogen-induced tyrosine phosphorylation at position 216 of GSK3β can upregulate the level of LSD1Ser54p, leading to the activation of FDFT1 expression and subsequently promoting cholesterol biosynthesis in chicken Post-TCs, which may in turn enhance estrogen synthesis.

Identifying Potential Ligand Binding Sites on Glycogen Synthase Kinase 3 Using Atomistic Cosolvent Simulations

Glycogen synthase kinase 3 β (GSK3β) is a serine/threonine kinase that phosphorylates several protein substrates in crucial cell signaling pathways. Owing to its therapeutic importance, there is a need to develop GSK3β inhibitors with high specificity and potency. One approach is to find small molecules that can allosterically bind to the GSK3β protein surface. We have employed fully atomistic mixed-solvent molecular dynamics (MixMD) simulations to identify three plausible allosteric sites on GSK3β that can facilitate the search for allosteric inhibitors. Our MixMD simulations narrow down the allosteric sites to precise regions on the GSK3β surface, thereby improving upon the previous predictions of the locations of these sites.

Targeting glycogen synthase kinase-3β for Alzheimer's disease: Recent advances and future Prospects

Senile plaques induced by β-amyloid (Aβ) abnormal aggregation and neurofibrillary tangles (NFT) caused by tau hyperphosphorylation are important pathological manifestations of Alzheimer's disease (AD). Glycogen synthase kinase-3 (GSK-3) is a conserved kinase; one member GSK-3β is highly expressed in the AD brain and involved in the formation of NFT. Hence, pharmacologically inhibiting GSK-3β activity and expression is a good approach to treat AD. As summarized in this article, multiple GSK-3β inhibitors has been comprehensively summarized over recent five years. However, only lithium carbonate and Tideglusib have been studied in clinical trials of AD. Besides ATP-competitive and non-ATP-competitive inhibitors, peptide inhibitors, allosteric inhibitors and other types of inhibitors have gradually attracted more interest. Moreover, considering the close relationship between GSK-3β and other targets involved in cholinergic hypothesis, Aβ aggregation hypothesis, tau hyperphosphorylation hypothesis, oxidative stress hypothesis, neuro-inflammation hypothesis, etc., diverse multifunctional molecules and multi-target directed ligands (MTDLs) have also been disclosed. We hope that these recent advances and critical perspectives will facilitate the discovery of safe and effective GSK-3β inhibitors for AD treatment.

Rational Design of Dual Inhibitors for Alzheimer's Disease: Insights from Computational Screening of BACE1 and GSK-3β

BACKGROUND

Alzheimer's disease (AD) is one of the most concerned neurodegenerative disorders across the world characterized by amyloid-beta (Aβ) plaques and neurofibrillary tangles (NFTs), leading to cognitive decline and memory loss. Targeting key pathways involved in AD like Aβ and NFT pathways, are crucial for the development of effective therapeutic strategies. In this study, we aimed to identify and establish promising dual inhibitors targeting BACE1 and GSK-3β, two proteins implicated in Aβ and NFT formation respectively.

METHODS

We have used molecular docking, ADME property analysis, and MMGBSA calculations for the identification of hit molecules and further evaluation of binding affinity, drug-like properties, and stability against BACE1 and GSK-3β.

RESULTS

Our results demonstrated strong binding affinities of ZINC000034853956 towards the active sites of both proteins, with favorable interactions involving key residues crucial for inhibitory activity. Additionally, ZINC000034853956 exhibited favorable drug-like properties. MD simulations revealed the stable binding of ZINC000034853956 to both BACE1 and GSK-3β over a 50 ns period, with consistent ligand-protein interactions, such as hydrogen bonding and hydrophobic contacts. These findings highlight the potential of ZINC000034853956 as a promising candidate for AD treatment, acting as a dual inhibitor targeting both BACE1 and GSK-3β. Overall, our study provides valuable insights into the potential of ZINC000034853956 as a dual inhibitor for AD. The strong binding affinity, favorable drug-like properties, and stability observed in MD simulations support its suitability for further optimization and preclinical studies.

CONCLUSION

Further investigations are warranted to elucidate the precise molecular mechanisms and therapeutic benefits of ZINC000034853956. Our findings offer hope for the development of novel therapeutic interventions targeting crucial pathways involved in AD neurodegeneration.

The role of glycogen synthase kinase 3 beta in multiple sclerosis

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS) that leads to progressive neurological disability due to axonal deterioration. Although MS presents profound heterogeneity in the clinical course, its underlying central mechanism is active demyelination and neurodegeneration associated with inflammation. Multiple autoimmune and neuroinflammatory pathways are involved in the demyelination process of MS. Analysis of MS lesions has shown that inflammatory genes are upregulated. Glycogen synthase kinase-3 (GSK-3) is part of the mitogen-activated protein kinase (MAPK) family and has important roles in many signaling cascades. GSK-3 is a highly conserved serine/threonine protein kinase expressed in both the central and the peripheral nervous systems. GSK-3 modulates several biological processes through phosphorylation of protein kinases, including cell signaling, neuronal growth, apoptosis and production of pro-inflammatory cytokines and interleukins, allowing adaptive changes in events such as cellular proliferation, migration, inflammation, and immunity. GSK-3 occurs in mammals in two isoforms GSK-3α and GSK-3β, both of which are common in the brain, although GSK-3α is found particularly in the cerebral cortex, cerebellum, striated hippocampus and Purkinje cells, while GSK-3β is found in all brain regions. In patients with chronic progressive MS, expression of GSK-3β is elevated in several brain regions such as the corpus callosum and cerebral cortex. GSK-3β inhibition may play a role in glial cell activation, reducing pathological pain induced by nerve injury by formalin injection. According to the role of GSK-3β in pathological conditions, the aim of this article is review of the role of GSK-3β in multiple sclerosis and inflammation of neurons.

Crosstalk between GSK-3β-actuated molecular cascades and myocardial physiology

The finding of "glycogen synthase kinase-3" (GSK-3) was initially identified as a protein kinase that phosphorylate and inhibited glycogen synthase. However, it was soon discovered that GSK-3 also has significant impact in regulation of truly astonishing number of critical intracellular signaling pathways ranging from regulation of cell growth, neurology, heart failure, diabetes, aging, inflammation, and cancer. Recent studies have validated the feasibility of targeting GSK-3 for its vital therapeutic potential to maintain normal myocardial homeostasis, conversely, its loss is incompatible with life as it can abrupt cell cycle and endorse fatal cardiomyopathy. The current study focuses on its expanding therapeutic action in myocardial tissue, concentrating primarily on its role in diabetes-associated cardiac complication, apoptosis and metabolism, heart failure, cardiac hypertrophy, and myocardial infarction. The current report also includes the finding of our previous investigation that has shown the impact of GSK-3β inhibitor against diabetes-associated myocardial injury and experimentally induced myocardial infarction. We have also discussed some recent identified GSK-3β inhibitors for their cardio-protective potential. The crosstalk of various underlying mechanisms that highlight the significant role of GSK-3β in myocardial pathophysiology have been discussed in the present report. For these literatures, we will rely profoundly on our previous studies and those of others to reconcile some of the deceptive contradictions in the literature.

The structural basis of the autoinhibition mechanism of glycogen synthase kinase 3β (GSK3β): molecular modeling and molecular dynamics simulation studies

The autoinhibition phenomenon has been frequently observed in enzymes and represents an important regulatory strategy to fine-tune enzyme activity. Evolution has exploited this mechanism to reduce enzymatic activity. Glycogen synthase kinase 3β (GSK3β) undergoes autoinhibition via the phosphorylation of Ser9 at the N-terminus of the kinase, which, acting as a pseudosubstrate, occupies the catalytic domain of GSK3β and subsequently blocks primed substrates from having access to the catalytic domain. The detailed structural basis of the autoinhibition mechanism of GSK3β by the pseudosubstrate, however, has not yet been fully resolved. Here, a three-dimensional model of the binary GSK3β-pseudosubstrate complex was built via the molecular modeling method. Based on the constructed model, extensive molecular dynamics (MD) simulations and subsequent molecular mechanics generalized Born/surface area (MM_GBSA) calculations were performed on the wild-type GSK3β-pseudosubstrate complex and three mutated systems (R4A, R6A, and S9A). Analyses of MD simulations and binding free energies revealed that the phosphorylation of Ser9 is the prerequisite for the autoinhibition of GSK3β, and both mutations of Arg4 and Arg6 to alanine markedly reduced the binding affinities of the mutated pseudosubstrate to the GSK3β catalytic domain, thereby disrupting the autoinhibition of the kinase. This study highlights the importance of Ser9, Arg6, and Arg4 in modulating the autoinhibition mechanism of GSK3β, contributing to a deeper understanding of GSK3β biology.Communicated by Ramaswamy H. Sarma.

Regulation of platelet-activating factor-induced interleukin-8 expression by protein tyrosine phosphatase 1B

Background

Platelet-activating factor (PAF) is a potent lipid mediator whose involvement in the onset and progression of atherosclerosis is mediated by, among others, the modulation of cytokine expression patterns. The presence of multiple potential protein-tyrosine phosphatase (PTP) 1B substrates in PAF receptor signaling pathways brought us to investigate its involvement in PAF-induced cytokine expression in monocyte-derived dendritic cells (Mo-DCs) and to study the pathways involved in this modulation.

Methods

We used in-vitro-matured human dendritic cells and the HEK-293 cell line in our studies. PTP1B inhibition was though siRNAs and a selective inhibitor. Cytokine expression was studied with RT-PCR, luciferase assays and ELISA. Phosphorylation status of kinases and transcription factors was studied with western blotting.

Results

Here, we report that PTP1B was involved in the modulation of cytokine expression in PAF-stimulated Mo-DCs. A study of the down-regulation of PAF-induced IL-8 expression, by PTP1B, showed modulation of PAF-induced transactivation of the IL-8 promoter which was dependent on the presence of the C/EBPß -binding site. Results also suggested that PTP1B decreased PAF-induced IL-8 production by a glycogen synthase kinase (GSK)-3-dependent pathway via activation of the Src family kinases (SFK). These kinases activated an unidentified pathway at early stimulation times and the PI3K/Akt signaling pathway in a later phase. This change in GSK-3 activity decreased the C/EBPß phosphorylation levels of the threonine 235, a residue whose phosphorylation is known to increase C/EBPß transactivation potential, and consequently modified IL-8 expression.

Conclusion

The negative regulation of GSK-3 activity by PTP1B and the consequent decrease in phosphorylation of the C/EBPß transactivation domain could be an important negative feedback loop by which cells control their cytokine production after PAF stimulation.

Electronic supplementary material

The online version of this article (10.1186/s12964-019-0334-6) contains supplementary material, which is available to authorized users.

Kinase-loaded magnetic beads for sequentialin vitrophosphorylation of peptides and proteins

Kinases ERK2 and GSK-3β loaded magnetic beads for sequentialin vitrophosphorylation of peptides and proteins.

Investigation of naphthofuran moiety as potential dual inhibitor against BACE-1 and GSK-3β: molecular dynamics simulations, binding energy, and network analysis to identify first-in-class dual inhibitors against Alzheimer's disease

BACE-1 and GSK-3β are potential therapeutic drug targets for Alzheimer's disease. Recently, both the targets received attention for designing dual inhibitors for Alzheimer's disease. Until now, only two-scaffold triazinone and curcumin have been reported as BACE-1 and GSK-3β dual inhibitors. Docking, molecular dynamics, clustering, binding energy, and network analysis of triazinone derivatives with BACE-1 and GSK-3β was performed to get molecular insight into the first reported dual inhibitor. Further, we designed and evaluated a naphthofuran series for its ability to inhibit BACE-1 and GSK-3β with the computational approaches. Docking study of naphthofuran series showed a good binding affinity towards both the targets. Molecular dynamics, binding energy, and network analysis were performed to compare their binding with the targets and amino acids responsible for binding. Naphthofuran series derivatives showed good interaction within the active site residues of both of the targets. Hydrogen bond occupancy and binding energy suggested strong binding with the targets. Dual-inhibitor binding was mostly governed by the hydrophobic interactions for both of the targets. Per residue energy decomposition and network analysis identified the key residues involved in the binding and inhibiting BACE-1 and GSK-3β. The results indicated that naphthofuran series derivative 11 may be a promising first-in-class dual inhibitor against BACE-1 and GSK-3β. This naphthofuran series may be further explored to design better dual inhibitors. Graphical abstract Naphthofuran derivative as a dual inhibitor for BACE-1 and GSK-3β.

Modeling Peptide-Protein Structure and Binding Using Monte Carlo Sampling Approaches: Rosetta FlexPepDock and FlexPepBind

Many signaling and regulatory processes involve peptide-mediated protein interactions, i.e., the binding of a short stretch in one protein to a domain in its partner. Computational tools that generate accurate models of peptide-receptor structures and binding improve characterization and manipulation of known interactions, help to discover yet unknown peptide-protein interactions and networks, and bring into reach the design of peptide-based drugs for targeting specific systems of medical interest.Here, we present a concise overview of the Rosetta FlexPepDock protocol and its derivatives that we have developed for the structure-based characterization of peptide-protein binding. Rosetta FlexPepDock was built to generate precise models of protein-peptide complex structures, by effectively addressing the challenge of the considerable conformational flexibility of the peptide. Rosetta FlexPepBind is an extension of this protocol that allows characterizing peptide-binding affinities and specificities of various biological systems, based on the structural models generated by Rosetta FlexPepDock. We provide detailed descriptions and guidelines for the usage of these protocols, and on a specific example, we highlight the variety of different challenges that can be met and the questions that can be answered with Rosetta FlexPepDock.

Identification of lead small molecule inhibitors of glycogen synthase kinase-3 beta using a fragment-linking strategy

Glycogen synthase kinase-3 beta (GSK3β) kinase serves as a promising therapeutic target for the treatment of various human diseases, such as diabetes, obesity, and Alzheimer's disease. In this study, we report lead GSK3β inhibitors identified using a fragment-linking strategy. Through the systematic exploration, a six-atom chain unit bearing the rigid double bond was found to be a suitable linker connecting two fragments, which enables favorable contacts with backbone groups of residues in the pockets. As a consequence, potent GSK3β inhibitor 9i was found with IC₅₀ values of 19nM. The binding mode analysis indicates that the activities of the inhibitors appear to be achieved by the establishment of multiple hydrogen bonds and hydrophobic interactions in the ATP-binding site of GSK3β. The good biochemical potencies and structural uniqueness of the inhibitors support consideration in the further study to optimize the biological activity.

Molecular dynamics simulation studies of GSK-3β ATP competitive inhibitors: understanding the factors contributing to selectivity

Glycogen synthase kinase-3 is a constitutively acting, multifunctional serine threonine kinase, the role of which has been implicated in several physiological pathways and has emerged as a promising target for the treatment of type-II diabetes and Alzheimer's disease. In order to provide a detailed understanding of the origin of selectivity determinants of ATP competitive inhibitors, molecular dynamics simulations in combination with MM-PBSA binding energy calculations were performed using crystal structures of GSK-3β and CDK-2 in complex with 12 ATP competitive inhibitors. Analysis of energy contributions indicate that electrostatic interaction energy dictates the selectivity of ATP competitive inhibitors against CDK-2. Key interactions as well as residues that potentially make a major contribution to the binding free energy were identified at the ATP binding site. This analysis stresses the need for the inhibitors to interact with Lys85, Thr138, and Arg141 in the binding site of GSK-3β to show selectivity. The residue-wise energy decomposition analysis further suggested the additional role of Gln185 in determining the selectivity of maleimides. The results obtained in this study can be utilized to design new selective GSK-3 ATP competitive inhibitors.

HDAC inhibition through valproic acid modulates the methylation profiles in human embryonic kidney cells

Post-translational modifications on the tails of core and linker histones dictate transcription and have vital roles in disease and development. Acetylation and deacetylation events enabled by histone acetyl transferases and histone deacetylases (HDACs) on the chromatin milieu are intricately involved in gene regulation. Inhibition of HDACs is emerging as a powerful strategy in regenerative therapy, transplantation, development and in nuclear reprogramming events. Valproic acid (VPA), belonging to the short-chain fatty acid group of HDAC inhibitors, modulates the epigenome altering gene expression profiles across cell lines. This work attempts to explore the methylation profiles triggered by VPA treatment on human embryonic kidney cells (HEK 293) through a biochemical and computational approach. VPA treatment (for 48 h) has been observed to hypermethylate lysine 4 on the core histone H3 and confers a hypomethylation status of H3 lysine 27 in HEK 293 cells leaving the nuclear area and nuclear contour unaltered. Our structural docking and Binding Free Energy (BFE) calculations establish an active role for VPA in inhibiting the demethylase JARID1A (Jumonji, AT Rich Interactive Domain 1A) and the methyl-transferase EZH2 (Enhancer of Zeste Homologue 2). This work has also proven that VPA can inhibit the activity of proteins like GSK3β and PKCβII involved in developmental disorders. This work establishes a dynamic correlation between histone methylation events and HDAC inhibition and may define newer epigenetic strategies for treating neurodevelopmental and oncological disorders.

Cancer-related networks: a help to understand, predict and change malignant transformation

Cancer is increasingly described as a systems-level, network phenomenon. Genetic methods, such as next generation sequencing and RNA interference uncovered the complexity tumor-specific mutation-induced effects and the identification of multiple target sets. Network analysis of cancer-specific metabolic and signaling pathways highlighted the structural features of cancer-related proteins and their complexes to develop next-generation protein kinase inhibitors, as well as the modulation of inflammatory and autophagic pathways in anti-cancer therapies. Importantly, malignant transformation can be described as a two-phase process, where an initial increase of system plasticity is followed by a decrease of plasticity at late stages of tumor development. Late-stage tumors should be attacked by an indirect network influence strategy. On the contrary, the attack of early-stage tumors may target central network nodes. Cancer stem cells need special diagnosis and targeting, since they potentially have an extremely high ability to change the rigidity/plasticity of their networks. The early warning signals of the activation of fast growing tumor cell clones are important in personalized diagnosis and therapy. Multi-target attacks are needed to perturb cancer-specific networks to exit from cancer attractors and re-enter a normal attractor. However, the dynamic non-genetic heterogeneity of cancer cell population induces the replenishment of the cancer attractor with surviving, non-responsive cells from neighboring abnormal attractors. The development of drug resistance is further complicated by interactions of tumor clones and their microenvironment. Network analysis of intercellular cooperation using game theory approaches may open new areas of understanding tumor complexity. In conclusion, the above applications of the network approach open up new, and highly promising avenues in anti-cancer drug design.

Glycogen synthase kinase-3β (GSK-3β) and its dysregulation in glioblastoma multiforme

Glioblastoma multiforme (GBM) is the most frequently occurring and devastating human brain malignancy, retaining almost universal mortality and a median survival of only 14 months, even with recent advances in multimodal treatments. Gliomas are characterised as being both highly resistant to chemo- and radiotherapy and highly invasive, rendering conventional interventions palliative. The continual dismal prognosis for GBM patients identifies an urgent need for the evolutionary development of new treatment modalities. This includes molecular targeted therapies as many signaling molecules and associated pathways have been implicated in the development and survival of malignant gliomas including the protein kinase, glycogen synthase kinase 3 beta (GSK-3β). Here we review the activity and function of GSK-3β in a number of signaling pathways and its role in gliomagenesis.

How calcium inhibits the magnesium-dependent kinase gsk3β: a molecular simulation study

Glycogen synthase kinase 3β (GSK3β) is a ubiquitous serine/threonine kinase that plays a pivotal role in many biological processes. GSK3β catalyzes the transfer of γ-phosphate of ATP to the unique substrate Ser/Thr residues with the assistance of two natural activating cofactors Mg(2+). Interestingly, the biological observation reveals that a non-native Ca(2+) ion can inhibit the GSK3β catalytic activity. Here, the inhibitory mechanism of GSK3β by the displacement of native Mg(2+) at site 1 by Ca(2+) was investigated by means of 80 ns comparative molecular dynamics (MD) simulations of the GSK3β···Mg(2+)-2/ATP/Mg(2+) -1 and GSK3β···Mg(2+)-2/ATP/Ca(2+)-1 systems. MD simulation results revealed that using the AMBER point charge model force field for Mg(2+) was more appropriate in the reproduction of the active site architectural characteristics of GSK3β than using the magnesium-cationic dummy atom model force field. Compared with the native Mg(2+) bound system, the misalignment of the critical triphosphate moiety of ATP, the erroneous coordination environments around the Mg(2+) ion at site 2, and the rupture of the key hydrogen bond between the invariant Lys85 and the ATP O(β2) atom in the Ca(2+) substituted system were observed in the MD simulation due to the Ca(2+) ion in active site in order to achieve its preferred sevenfold coordination geometry, which adequately abolish the enzymatic activity. The obtained results are valuable in understanding the possible mechanism by why Ca(2+) inhibits the GSK3β activity and also provide insights into the mechanism of Ca(2+) inhibition in other structurally related protein kinases.

Rosetta FlexPepDock web server--high resolution modeling of peptide-protein interactions

Peptide–protein interactions are among the most prevalent and important interactions in the cell, but a large fraction of those interactions lack detailed structural characterization. The Rosetta FlexPepDock web server (http://flexpepdock.furmanlab.cs.huji.ac.il/) provides an interface to a high-resolution peptide docking (refinement) protocol for the modeling of peptide–protein complexes, implemented within the Rosetta framework. Given a protein receptor structure and an approximate, possibly inaccurate model of the peptide within the receptor binding site, the FlexPepDock server refines the peptide to high resolution, allowing full flexibility to the peptide backbone and to all side chains. This protocol was extensively tested and benchmarked on a wide array of non-redundant peptide–protein complexes, and was proven effective when applied to peptide starting conformations within 5.5 Å backbone root mean square deviation from the native conformation. FlexPepDock has been applied to several systems that are mediated and regulated by peptide–protein interactions. This easy to use and general web server interface allows non-expert users to accurately model their specific peptide–protein interaction of interest.

Rosetta FlexPepDock ab-initio: simultaneous folding, docking and refinement of peptides onto their receptors

Flexible peptides that fold upon binding to another protein molecule mediate a large number of regulatory interactions in the living cell and may provide highly specific recognition modules. We present Rosetta FlexPepDock ab-initio, a protocol for simultaneous docking and de-novo folding of peptides, starting from an approximate specification of the peptide binding site. Using the Rosetta fragments library and a coarse-grained structural representation of the peptide and the receptor, FlexPepDock ab-initio samples efficiently and simultaneously the space of possible peptide backbone conformations and rigid-body orientations over the receptor surface of a given binding site. The subsequent all-atom refinement of the coarse-grained models includes full side-chain modeling of both the receptor and the peptide, resulting in high-resolution models in which key side-chain interactions are recapitulated. The protocol was applied to a benchmark in which peptides were modeled over receptors in either their bound backbone conformations or in their free, unbound form. Near-native peptide conformations were identified in 18/26 of the bound cases and 7/14 of the unbound cases. The protocol performs well on peptides from various classes of secondary structures, including coiled peptides with unusual turns and kinks. The results presented here significantly extend the scope of state-of-the-art methods for high-resolution peptide modeling, which can now be applied to a wide variety of peptide-protein interactions where no prior information about the peptide backbone conformation is available, enabling detailed structure-based studies and manipulation of those interactions.

Deconstructing GSK-3: The Fine Regulation of Its Activity

Glycogen synthase kinase-3 (GSK-3) unique position in modulating the function of a diverse series of proteins in combination with its association with a wide variety of human disorders has attracted significant attention to the protein both as a therapeutic target and as a means to understand the molecular basis of these disorders. GSK-3 is ubiquitously expressed and, unusually, constitutively active in resting, unstimulated cells. In mammals, GSK-3α and β are each expressed widely at both the RNA and protein levels although some tissues show preferential levels of some of the two proteins. Neither gene appears to be acutely regulated at the transcriptional level, whereas the proteins are controlled posttranslationally, largely through protein-protein interactions or by posttranslational regulation. Control of GSK-3 activity thus occurs by complex mechanisms that are each dependent upon specific signalling pathways. Furthermore, GSK-3 appears to be a cellular nexus, integrating several signalling systems, including several second messengers and a wide selection of cellular stimulants. This paper will focus on the different ways to control GSK-3 activity (phosphorylation, protein complex formation, truncation, subcellular localization, etc.), the main signalling pathways involved in its control, and its pathological deregulation.

Modeling peptide-protein interactions

Peptide-protein interactions are prevalent in the living cell and form a key component of the overall protein-protein interaction network. These interactions are drawing increasing interest due to their part in signaling and regulation, and are thus attractive targets for computational structural modeling. Here we report an overview of current techniques for the high resolution modeling of peptide-protein complexes. We dissect this complicated challenge into several smaller subproblems, namely: modeling the receptor protein, predicting the peptide binding site, sampling an initial peptide backbone conformation and the final refinement of the peptide within the receptor binding site. For each of these conceptual stages, we present available tools, approaches, and their reported performance. We summarize with an illustrative example of this process, highlighting the success and current challenges still facing the automated blind modeling of peptide-protein interactions. We believe that the upcoming years will see considerable progress in our ability to create accurate models of peptide-protein interactions, with applications in binding-specificity prediction, rational design of peptide-mediated interactions and the usage of peptides as therapeutic agents.