Fragment-Based Discovery of a Series of Allosteric-Binding Site Modulators of ß-Glucocerebrosidase.

ß-Glucocerebrosidase (GBA/GCase) mutations leading to misfolded protein cause Gaucher's disease and are a major genetic risk factor for Parkinson's disease and dementia with Lewy bodies. The identification of small molecule pharmacological chaperones that can stabilize the misfolded protein and increase delivery of degradation-prone mutant GCase to the lysosome is a strategy under active investigation. Here, we describe the first use of fragment-based drug discovery (FBDD) to identify pharmacological chaperones of GCase. The fragment hits were identified by using X-ray crystallography and biophysical techniques. This work led to the discovery of a series of compounds that bind GCase with nM potency and positively modulate GCase activity in cells.

Application of Native ESI-MS to Characterize Interactions between Compounds Derived from Fragment-Based Discovery Campaigns and Two Pharmaceutically Relevant Proteins.

Native electrospray ionization mass spectrometry (ESI-MS) was applied to analyze the binding of compounds generated during fragment-based drug discovery (FBDD) campaigns against two functionally distinct proteins, the X-linked inhibitor of apoptosis protein (XIAP) and cyclin-dependent kinase 2 (CDK2). Compounds of different molecular weights and a wide range of binding affinities obtained from the hits to leads and lead optimization stages of FBDD campaigns were studied, and their dissociation constants (Kd) were measured by native ESI-MS. We demonstrate that native ESI-MS has the potential to be applied to the stages of an FBDD campaign downstream of primary screening for the detection and quantification of protein-ligand binding. Native ESI-MS was used to derive Kd values for compounds binding to XIAP, and the dissociation of the complex between XIAP and a peptide derived from the second mitochondria-derived activator of caspases (SMAC) protein induced by one of the test compounds was also investigated. Affinities of compounds binding to CDK2 gave Kd values in the low nanomolar to low millimolar range, and Kd values generated by MS and isothermal titration calorimetry (ITC) followed the same trend for both proteins. Practical considerations for the application of native ESI-MS are discussed in detail.

Native Mass Spectrometry Gives Insight into the Allosteric Binding Mechanism of M2 Pyruvate Kinase to Fructose-1,6-Bisphosphate.

The various oligomeric states of the M2 isoform of pyruvate kinase (PKM2) were distinguished using native mass spectrometry. The effect of PKM2 concentration on its dimer-tetramer equilibrium was monitored, and a value for the dissociation constant ( Kd) of the two species was estimated to be 0.95 µM. Results of binding of fructose-1,6-bisphosphate (FBP) to PKM2 are shown and provide insight into the allosteric mechanism and changes in the oligomerization status of PKM2. The average Kd for binding of FBP to the PKM2 tetramer was estimated to be 7.5 µM. It is concluded that four molecules of FBP bind to the active PKM2 tetramer whereas binding of FBP to the PKM2 dimer was not observed. It is suggested that either FBP potentiates rapid tetramer formation after binding to apo PKM2 dimers or FBP binds to PKM2 apo tetramers, thus driving the dimer-tetramer equilibrium in the direction of fully FBP-bound tetramer. The binding occurs in a highly positively cooperative manner with a Hill coefficient ( n) of 3.

Structure of the Epigenetic Oncogene MMSET and Inhibition by N-Alkyl Sinefungin Derivatives.

The members of the NSD subfamily of lysine methyl transferases are compelling oncology targets due to the recent characterization of gain-of-function mutations and translocations in several hematological cancers. To date, these proteins have proven intractable to small molecule inhibition. Here, we present initial efforts to identify inhibitors of MMSET (aka NSD2 or WHSC1) using solution phase and crystal structural methods. On the basis of 2D NMR experiments comparing NSD1 and MMSET structural mobility, we designed an MMSET construct with five point mutations in the N-terminal helix of its SET domain for crystallization experiments and elucidated the structure of the mutant MMSET SET domain at 2.1 Å resolution. Both NSD1 and MMSET crystal systems proved resistant to soaking or cocrystallography with inhibitors. However, use of the close homologue SETD2 as a structural surrogate supported the design and characterization of N-alkyl sinefungin derivatives, which showed low micromolar inhibition against both SETD2 and MMSET.

In-gel activity-based protein profiling of a clickable covalent ERK1/2 inhibitor.

In-gel activity-based protein profiling (ABPP) offers rapid assessment of the proteome-wide selectivity and target engagement of a chemical tool. Here we demonstrate the use of the inverse electron demand Diels Alder (IEDDA) click reaction for in-gel ABPP by evaluating the selectivity profile and target engagement of a covalent ERK1/2 probe tagged with a trans-cyclooctene group. The chemical probe was shown to bind covalently to Cys166 of ERK2 using protein MS and X-ray crystallography, and displayed submicromolar GI50s in A375 and HCT116 cells. In both cell lines, the probe demonstrated target engagement and a good selectivity profile at low concentrations, which was lost at higher concentrations. The IEDDA cycloaddition enabled fast and quantitative fluorescent tagging for readout with a high background-to-noise ratio and thereby provides a promising alternative to the commonly used copper catalysed alkyne-azide cycloaddition.

Exploitation of a Novel Binding Pocket in Human Lipoprotein-Associated Phospholipase A2 (Lp-PLA2) Discovered through X-ray Fragment Screening.

Elevated levels of human lipoprotein-associated phospholipase A2 (Lp-PLA2) are associated with cardiovascular disease and dementia. A fragment screen was conducted against Lp-PLA2 in order to identify novel inhibitors. Multiple fragment hits were observed in different regions of the active site, including some hits that bound in a pocket created by movement of a protein side chain (approximately 13 Å from the catalytic residue Ser273). Using structure guided design, we optimized a fragment that bound in this pocket to generate a novel low nanomolar chemotype, which did not interact with the catalytic residues.

Serine is a natural ligand and allosteric activator of pyruvate kinase M2.

Cancer cells exhibit several unique metabolic phenotypes that are critical for cell growth and proliferation. Specifically, they overexpress the M2 isoform of the tightly regulated enzyme pyruvate kinase (PKM2), which controls glycolytic flux, and are highly dependent on de novo biosynthesis of serine and glycine. Here we describe a new rheostat-like mechanistic relationship between PKM2 activity and serine biosynthesis. We show that serine can bind to and activate human PKM2, and that PKM2 activity in cells is reduced in response to serine deprivation. This reduction in PKM2 activity shifts cells to a fuel-efficient mode in which more pyruvate is diverted to the mitochondria and more glucose-derived carbon is channelled into serine biosynthesis to support cell proliferation.

Crystal structure of human CDK4 in complex with a D-type cyclin.

The cyclin D1-cyclin-dependent kinase 4 (CDK4) complex is a key regulator of the transition through the G(1) phase of the cell cycle. Among the cyclin/CDKs, CDK4 and cyclin D1 are the most frequently activated by somatic genetic alterations in multiple tumor types. Thus, aberrant regulation of the CDK4/cyclin D1 pathway plays an essential role in oncogenesis; hence, CDK4 is a genetically validated therapeutic target. Although X-ray crystallographic structures have been determined for various CDK/cyclin complexes, CDK4/cyclin D1 has remained highly refractory to structure determination. Here, we report the crystal structure of CDK4 in complex with cyclin D1 at a resolution of 2.3 A. Although CDK4 is bound to cyclin D1 and has a phosphorylated T-loop, CDK4 is in an inactive conformation and the conformation of the heterodimer diverges from the previously known CDK/cyclin binary complexes, which suggests a unique mechanism for the process of CDK4 regulation and activation.

A prototype methodology combining surface-enhanced laser desorption/ionization protein chip technology and artificial neural network algorithms to predict the chemoresponsiveness of breast cancer cell lines exposed to Paclitaxel and Doxorubicin under in vitro conditions.

An ability to predict the likelihood of cellular response towards particular chemotherapeutic agents based upon protein expression patterns could facilitate the identification of biological molecules with previously undefined roles in the process of chemoresistance/chemosensitivity, and if robust enough these patterns might also be exploited towards the development of novel predictive assays. To ascertain whether proteomic based molecular profiling in conjunction with artificial neural network (ANN) algorithms could be applied towards the specific recognition of phenotypic patterns between either control or drug treated and chemosensitive or chemoresistant cellular populations, a combined approach involving MALDI-TOF matrix-assisted laser desorption/ionization-time of flight mass spectrometry, Ciphergen protein chip technology and ANN algorithms have been applied to specifically identify proteomic 'fingerprints' indicative of treatment regimen for chemosensitive (MCF-7, T47D) and chemoresistant (MCF-7/ADR) breast cancer cell lines following exposure to Doxorubicin or Paclitaxel. The results indicate that proteomic patterns can be identified by ANN algorithms to correctly assign 'class' for treatment regimen (e.g. control/drug treated or chemosensitive/chemoresistant) with a high degree of accuracy using boot-strap statistical validation techniques and that biomarker ion patterns indicative of response/non-response phenotypes are associated with MCF-7 and MCF-7/ADR cells exposed to Doxorubicin. We have also examined the predictive capability of this approach towards MCF-7 and T47D cells to ascertain whether prediction could be made based upon treatment regimen irrespective of cell lineage. Models were identified that could correctly assign class (control or Paclitaxel treatment) for 35/38 samples of an independent dataset. A similar level of predictive capability was also found (> 92%; n = 28) when proteomic patterns derived from the drug resistant cell line MCF-7/ADR were compared against those derived from MCF-7 and T47D as a model system of drug resistant and drug sensitive phenotypes. This approach might offer a potential methodology for predicting the biological behaviour of cancer cells towards particular chemotherapeutics and through protein isolation and sequence identification could result in the identification of biological molecules associated with chemosensitive/chemoresistance tumour phenotypes.