Sphingosine kinases : emerging structure function insights

Sphingosine kinases (SK1 and SK2) catalyse the conversion of sphingosine into sphingosine 1-phosphate and control fundamental cellular processes, including cell survival, proliferation, differentiation, migration, and immune function. In this review, we highlight recent breakthroughs in the structural and functional characterisation of SK1 and these are contextualised by analysis of crystal structures for closely related prokaryotic lipid kinases. We identify a putative dimerisation interface and propose novel regulatory mechanisms governing structural plasticity induced by phosphorylation and interaction with phospholipids and proteins. Our analysis suggests that the catalytic function and regulation of the enzymes might be dependent on conformational mobility and it provides a roadmap for future interrogation of SK1 function and its role in physiology and disease

Structure-function analysis of lipid substrates and inhibitors of sphingosine kinases

The sphingosine kinases, SK1 and SK2, catalyse the formation of the bioactive signalling lipid, sphingosine 1-phosphate (S1P), from sphingosine. SK1 and SK2 differ in their subcellular localisation, trafficking and regulation, but the isoforms are also distinct in their selectivity toward naturally occurring and synthetic ligands as substrates and inhibitors. To date, only the structure of SK1 has been determined, and a structural basis for selectivity differences in substrate handling by SK2 has yet to be established. Here we present a structural rationale, based on homology modelling and ligand docking, to account for the capacity of SK2, but not SK1, to efficiently process the pharmacologically active substances, fingolimod (FTY720) and safingol, as substrates. We propose that two key residue differences in hSK2 (Ser305/Thr584 in place of Ala175/Ala339 in hSK1) facilitate conformational switching in the lipid head group anchor residue, Asp308 (corresponding to Asp178 in hSK1), to accommodate substrate diversity for SK2. Our analysis accounts for the contrasting behaviour of fingolimod and safingol as non-turnover inhibitors of SK1, but substrates for SK2, and the observed stereoselectivity for phosphorylation of the pro-S hydroxymethyl group of fingolimod to generate (S)-FTY720-P in vivo. We also rationalise why methylation of the pro-R hydroxymethyl of FTY720 switches the behaviour of the resulting compound, (R)-FTY720 methyl ether (ROMe), to SK2-selective inhibition. Whilst the pharmacological significance of (S)-FTY720-P is firmly established, as the active principle of fingolimod in treating relapsing-remitting multiple sclerosis, the potential importance of SK-mediated phosphorylation of other substrates, such as safingol and non-canonical naturally occuring substrates such as (4E,nZ)-sphingadienes, is less widely appreciated. Thus, the contribution of SK2-derived safingol 1-phosphate to the anti-cancer activity of safingol should be considered. Similarly, the biological role of sphingadiene 1-phosphates derived from plant-based dietary sphingadienes, which we also show here are substrates for both SK1 and SK2, merits investigation

Sphingosine kinases as druggable targets

There is substantial evidence that the enzymes, sphingosine kinase 1 and 2, which catalyse the formation of the bioactive lipid, sphingosine 1-phosphate are involved in physiological and pathophysiological processes. In this chapter, we appraise the evidence that both enzymes are druggable and describe how isoform-specific inhibitors can be developed based on the plasticity of the sphingosine-binding site. This is contextualised with the effect of sphingosine kinase inhibitors in cancer, pulmonary hypertension, neurodegeneration, inflammation and sickling

A Novel Selective Sphingosine Kinase 2 Inhibitor, HWG-35D, Ameliorates the Severity of Imiquimod-Induced Psoriasis Model by Blocking Th17 Differentiation of Naïve CD4 T Lymphocytes

Sphingosine kinases (SK) catalyze the phosphorylation of sphingosine to generate sphingosine-1-phosphate. Two isoforms of SK (SK1 and SK2) exist in mammals. Previously, we showed the beneficial effects of SK2 inhibition, using ABC294640, in a psoriasis mouse model. However, ABC294640 also induces the degradation of SK1 and dihydroceramide desaturase 1 (DES1). Considering these additional effects of ABC294640, we re-examined the efficacy of SK2 inhibition in an IMQ-induced psoriasis mouse model using a novel SK2 inhibitor, HWG-35D, which exhibits nM potency and 100-fold selectivity for SK2 over SK1. Topical application of HWG-35D ameliorated IMQ-induced skin lesions and normalized the serum interleukin-17A levels elevated by IMQ. Application of HWG-35D also decreased skin mRNA levels of interleukin-17A, K6 and K16 genes induced by IMQ. Consistent with the previous data using ABC294640, HWG-35D also blocked T helper type 17 differentiation of naive CD4+ T cells with concomitant reduction of SOCS1. Importantly, HWG-35D did not affect SK1 or DES1 expression levels. These results reaffirm an important role of SK2 in the T helper type 17 response and suggest that highly selective and potent SK2 inhibitors such as HWG-35D might be of therapeutic use for the treatment of psoriasis

Decision-making in structure solution using Bayesian estimates of map quality: the PHENIX AutoSol wizard.

Estimates of the quality of experimental maps are important in many stages of structure determination of macromolecules. Map quality is defined here as the correlation between a map and the corresponding map obtained using phases from the final refined model. Here, ten different measures of experimental map quality were examined using a set of 1359 maps calculated by re-analysis of 246 solved MAD, SAD and MIR data sets. A simple Bayesian approach to estimation of map quality from one or more measures is presented. It was found that a Bayesian estimator based on the skewness of the density values in an electron-density map is the most accurate of the ten individual Bayesian estimators of map quality examined, with a correlation between estimated and actual map quality of 0.90. A combination of the skewness of electron density with the local correlation of r.m.s. density gives a further improvement in estimating map quality, with an overall correlation coefficient of 0.92. The PHENIX AutoSol wizard carries out automated structure solution based on any combination of SAD, MAD, SIR or MIR data sets. The wizard is based on tools from the PHENIX package and uses the Bayesian estimates of map quality described here to choose the highest quality solutions after experimental phasing

Automating crystallographic structure solution and refinement of protein-ligand complexes.

High-throughput drug-discovery and mechanistic studies often require the determination of multiple related crystal structures that only differ in the bound ligands, point mutations in the protein sequence and minor conformational changes. If performed manually, solution and refinement requires extensive repetition of the same tasks for each structure. To accelerate this process and minimize manual effort, a pipeline encompassing all stages of ligand building and refinement, starting from integrated and scaled diffraction intensities, has been implemented in Phenix. The resulting system is able to successfully solve and refine large collections of structures in parallel without extensive user intervention prior to the final stages of model completion and validation

Iterative-build OMIT maps: map improvement by iterative model building and refinement without model bias.

A procedure for carrying out iterative model building, density modification and refinement is presented in which the density in an OMIT region is essentially unbiased by an atomic model. Density from a set of overlapping OMIT regions can be combined to create a composite 'iterative-build' OMIT map that is everywhere unbiased by an atomic model but also everywhere benefiting from the model-based information present elsewhere in the unit cell. The procedure may have applications in the validation of specific features in atomic models as well as in overall model validation. The procedure is demonstrated with a molecular-replacement structure and with an experimentally phased structure and a variation on the method is demonstrated by removing model bias from a structure from the Protein Data Bank

Interpretation of ensembles created by multiple iterative rebuilding of macromolecular models.

Automation of iterative model building, density modification and refinement in macromolecular crystallography has made it feasible to carry out this entire process multiple times. By using different random seeds in the process, a number of different models compatible with experimental data can be created. Sets of models were generated in this way using real data for ten protein structures from the Protein Data Bank and using synthetic data generated at various resolutions. Most of the heterogeneity among models produced in this way is in the side chains and loops on the protein surface. Possible interpretations of the variation among models created by repetitive rebuilding were investigated. Synthetic data were created in which a crystal structure was modelled as the average of a set of ;perfect' structures and the range of models obtained by rebuilding a single starting model was examined. The standard deviations of coordinates in models obtained by repetitive rebuilding at high resolution are small, while those obtained for the same synthetic crystal structure at low resolution are large, so that the diversity within a group of models cannot generally be a quantitative reflection of the actual structures in a crystal. Instead, the group of structures obtained by repetitive rebuilding reflects the precision of the models, and the standard deviation of coordinates of these structures is a lower bound estimate of the uncertainty in coordinates of the individual models

Use of knowledge-based restraints in phenix.refine to improve macromolecular refinement at low resolution

Recent developments in PHENIX are reported that allow the use of reference-model torsion restraints, secondary-structure hydrogen-bond restraints and Ramachandran restraints for improved macromolecular refinement in phenix.refine at low resolution

The sphingosine 1-phosphate receptor 2 is shed in exosomes from breast cancer cells and is N-terminally processed to a short constitutively active form that promotes extracellular signal regulated kinase activation and DNA synthesis in fibroblasts

We demonstrate here that the G protein-coupled receptor (GPCR), sphingosine 1-phosphate receptor 2 (S1P2, Mr = 40 kDa) is shed in hsp70+ and CD63+ containing exosomes from MDA-MB-231 breast cancer cells. The receptor is taken up by fibroblasts, where it is N-terminally processed to a shorter form (Mr = 36 kDa) that appears to be constitutively active and able to stimulate the extracellular signal regulated kinase-1/2 (ERK-1/2) pathway and DNA synthesis. An N-terminally truncated construct of S1P2, which may correspond to the processed form of the receptor generated in fibroblasts, was found to be constitutively active when over-expressed in HEK293 cells. Analysis based on the available crystal structure of the homologous S1P1 receptor suggests that, in the inactive-state, the N-terminus of S1P2 may tension TM1 so as to maintain a compressive action on TM7. This in turn may stabilise a closed basal state interface between the intracellular ends of TM7 and TM6. Cleavage and removal of the S1P2 N-terminal peptide is postulated to facilitate relaxation of TM1 and accompanying separation of TM6 and TM7. The latter transition is one of the key elements of G protein engagement and is required to open the intracellular coupling interface beneath the GPCR helix bundle. Therefore, removal at the N-terminus of S1P2 is likely to enhance G protein coupling. These findings provide the first evidence that S1P2 is released from breast cancer cells in exosomes and is processed by fibroblasts to promote ERK signaling and proliferation of these cells