Prediction of pH-dependent aqueous solubility of Histone Deacetylase (HDAC) inhibitors1

Recently we developed a model for prediction of pH-dependent aqueous solubility of drugs and drug like molecules. In the present work, the model was applied on a series of novel Histone Deacetylases (HDAC) inhibitors discovered at TopoTarget. The applicability of our model was evaluated on the series of HDAC inhibitors by use of Self-Organizing Maps (SOM) and 2D-projection of the HDAC inhibitors on the chemical space of the training data set of the artificial neural network (ANN) module. The model was refined for the particular chemical space of interest, which led to two modifications in the training data set of the ANN. The performance of the original and the two modified versions of the model were evaluated against the commercial software from Simulations-plus and pH-dependent solubility measurements for representative compounds of the series. The results of the evaluation indicate that one can develop models that are more accurate in predicting differences in the solubility of structurally very similar compounds than models that have been trained on structurally unbiased, diverse data sets. Such ‘tailor-made’ models have the potential to become trustworthy enough to replace time-consuming and expensive medium- and high-throughput solubility experiments by providing results of similar or even better quality.     

Prediction of pH-dependent aqueous solubility of druglike molecules

In the present work, the Henderson-Hasselbalch (HH) equation has been employed for the development of a tool for the prediction of pH-dependent aqueous solubility of drugs and drug candidates. A new prediction method for the intrinsic solubility was developed, based on artificial neural networks that have been trained on a druglike PHYSPROP subset of 4548 compounds. For the prediction of acid/base dissociation coefficients, the commercial tool Marvin has been used, following validation on a data set of 467 molecules from the PHYSPROP database. The best performing network for intrinsic solubility predictions has a cross-validated root mean square error (RMSE) of 0.70 log S-units, while the Marvin pKa plug-in has an RMSE of 0.71 pH-units. A data set of 27 drugs with experimentally determined pH-solubility curves was assembled from the literature for the validation of the combined pH-dependent model, giving a mean RMSE of 0.79 log S-units. Finally, the combined model has been applied on profiling the solubility space at low pH of five large vendor libraries.     

Light‐Controlled Histone Deacetylase (HDAC) Inhibitors: Towards Photopharmacological Chemotherapy

Cancer treatment suffers from limitations that have a major impact on the patient’s quality of life and survival. In the case of chemotherapy, the systemic distribution of cytotoxic drugs reduces their efficacy and causes severe side effects due to nonselective toxicity. Photopharmacology allows a novel approach to address these problems because it employs external, local activation of chemotherapeutic agents by using light. The development of photoswitchable histone deacetylase (HDAC) inhibitors as potential antitumor agents is reported herein. Analogues of the clinically used chemotherapeutic agents vorinostat, panobinostat, and belinostat were designed with a photoswitchable azobenzene moiety incorporated into their structure. The most promising compound exhibits high inhibitory potency in the thermodynamically less stable cis form and a significantly lower activity for the trans form, both in terms of HDAC activity and proliferation of HeLa cells. This approach offers a clear prospect towards local photoactivation of HDAC inhibition to avoid severe side effects in chemotherapy.     

Prediction of aqueous solubility of organic compounds by the general solubility equation (GSE)

The revised general solubility equation (GSE) is used along with four different methods including Huuskonen's artificial neural network (ANN) and three multiple linear regression (MLR) methods to estimate the aqueous solubility of a test set of the 21 pharmaceutically and environmentally interesting compounds. For the selected test sets, it is clear that the GSE and ANN predictions are more accurate than MLR methods. The GSE has the advantages of being simple and thermodynamically sound. The only two inputs used in the GSE are the Celsius melting point (MP) and the octanol water partition coefficient (K(ow)). No fitted parameters and no training data are used in the GSE, whereas other methods utilize a large number of parameters and require a training set. The GSE is also applied to a test set of 413 organic nonelectrolytes that were studied by Huuskonen. Although the GSE uses only two parameters and no training set, its average absolute errors is only 0.1 log units larger than that of the ANN, which requires many parameters and a large training set. The average absolute error AAE is 0.54 log units using the GSE and 0.43 log units using Huuskonen's ANN modeling. This study provides evidence for the GSE being a convenient and reliable method to predict aqueous solubilities of organic compounds.     

Docking,Binding Free Energy Calculations and In Vitro Characterization of Pyrazine Linked 2-Aminobenzamides as Novel Class I Histone Deacetylase (HDAC) Inhibitors

Class I histone deacetylases, HDAC1, HDAC2, and HDAC3, represent potential targets for cancer treatment. However, the development of isoform-selective drugs for these enzymes remains challenging due to their high sequence and structural similarity. In the current study, we applied a computational approach to predict the selectivity profile of developed inhibitors. Molecular docking followed by MD simulation and calculation of binding free energy was performed for a dataset of 2-aminobenzamides comprising 30 previously developed inhibitors. For each HDAC isoform, a significant correlation was found between the binding free energy values and in vitro inhibitory activities. The predictive accuracy and reliability of the best preforming models were assessed on an external test set of newly designed and synthesized inhibitors. The developed binding free-energy models are cost-effective methods and help to reduce the time required to prioritize compounds for further studies.     

Design,Synthesis and Biological Evaluation of Novel Selective Thiol-based Histone Deacetylase(HDAC) VI InhibitorsBearing Indeno[1,2-c]pyrazole or Benzoindazole Scaffold

A series of thiol-based indeno[1,2-c]pyrazoles and benzoindazole compounds was designed and synthesized according to the structural specificity of histone deacetylase VI(HDAC6) and the structural characteristics of HDAC inhibitors. The inhibitory activities of the target compounds against HDAC6 and HDAC1 were screened by fluorescence analysis. Most of the target compounds showed moderate inhibitory activity against HDAC6(IC₅₀=44—598 nmol/L). Among them, compound A-4 displayed the highest selectivity against HDAC6 and similar inhibitory activity(IC₅₀=44 nmol/L) to that of the positive drug SAHA(IC₅₀=41 nmol/L) against HDAC6.     

Identification of Histone deacetylase (HDAC)-Associated Proteins with DNA-Programmed Affinity Labeling

Histone deacetylase (HDAC) is a major class of deacetylation enzymes. Many HDACs exist in large protein complexes in cells and their functions strongly depend on the complex composition. The identification of HDAC-associated proteins is highly important in understanding their molecular mechanisms. Although affinity probes have been developed to study HDACs, they were mostly targeting the direct binder HDAC, while other proteins in the complex remain underexplored. We report a DNA-based affinity labeling method capable of presenting different probe configurations without the need for preparing multiple probes. Using one binding probe, 9 probe configurations were created to profile HDAC complexes. Notably, this method identified indirect HDAC binders that may be inaccessible to traditional affinity probes, and it also revealed new biological implications for HDAC-associated proteins. This study provided a simple and broadly applicable method for characterizing protein-protein interactions.     

Prediction of drug solubility by the general solubility equation (GSE)

The revised general solubility equation (GSE) proposed by Jain and Yalkowsky is used to estimate the aqueous solubility of a set of organic nonelectrolytes studied by Jorgensen and Duffy. The only inputs used in the GSE are the Celsius melting point (MP) and the octanol water partition coefficient (K(ow)). These are generally known, easily measured, or easily calculated. The GSE does not utilize any fitted parameters. The average absolute error for the 150 compounds is 0.43 compared to 0.56 with Jorgensen and Duffy's computational method, which utilitizes five fitted parameters. Thus, the revised GSE is simpler and provides a more accurate estimation of aqueous solubility of the same set of organic compounds. It is also more accurate than the original version of the GSE.     

Prediction of aqueous solubility of drugs and pesticides with COSMO-RS

The COSMO-RS method, originally developed for the prediction of liquid-liquid and liquid-vapor equilibrium constants based on quantum chemical calculations, has been extended to solid compounds by addition of a heuristic expression for the Gibbs free energy of fusion. By this addition, COSMO-RS is now capable of a priori prediction of aqueous solubilities of a wide range of typical neutral drug and pesticide compounds. Only three parameters in the heuristic expression have been fitted on a data set of 150 drug-like compounds. On these data an rms deviation of 0.66 log-units was achieved. Later, the model was tested on a set of 107 pesticides, which have been critically selected based on two experimental data sources and by a crosscheck with an independent HQSAR model. On this data set an rms of 0.61 log-units was achieved, without any adjustments to the structurally extremely diverse pesticides. This result verifies the ability of this extended COSMO-RS to predict aqueous solubilities of drugs and pesticides of almost arbitrary structural classes. The new method is COSMO-RSol.     

Novel Sulfonamide Derivatives as Inhibitors of Histone Deacetylase

Inhibition of the enzyme histone deacetylase (HDAC) is emerging as a novel approach to the treatment of cancer. A series of novel sulfonamide derivatives were synthesized and evaluated for their ability to inhibit human HDAC. Compounds were identified which are potent enzyme inhibitors, with IC₅₀ values in the low nanomolar range against enzyme obtained from HeLa cell extracts, and with antiproliferative effects in cell culture. Extensive characterization of the structure–activity relationships of this series identified key requirements for activity. These include the direction of the sulfonamide bond and substitution patterns on the central phenyl ring. The alkyl spacer between the aromatic head group and the sulfonamide functionality also influenced the HDAC inhibitory activity. One of these compounds, m 11.1 , also designated PXD101, has entered clinical trials for solid tumors and haematological malignancies.     

新型苯甲酰胺类HDAC抑制剂的合成及其抗肿瘤活性

以MS-275为先导化合物,设计并合成了7个新型苯甲酰胺类化合物（6a~6c, 14a, 14b, 15a和18）,其结构经¹H NMR和ESI-MS表征。采用MTT法测定了6a~6c, 14a, 14b, 15a和18对人急性白血病细胞(HL60)和人乳腺癌细胞(MCF-7)的体外抗肿瘤细胞增殖活性。结果表明：N-(2-氨基苯)-3-［4-(吡啶-3-基)嘧啶-2-氨基］己酰胺（6a）, N-(2-氨基苯)-4-【3-{4-［(二乙胺基)甲基］苯基}丙烯酰】苯甲酰胺（14a）和N-(2-氨基苯)-4-［3-(吡啶-3-基)丙烯酰］丙酰胺(18）的抑制活性较好,其GI₅₀依次为5.72 μmol·L^-1, 6.91 μmol·L^-1, 7.11 μmol·L^-1和3.46 μmol·L^-1, 4.12 μmol·L^-1, 3.97 μmol·L^-1,优于MS-275(7.88 μmol·L^-1和4.49 μmol·L^-1)。     

The solubility of (14)C-labelled barium carbonate in aqueous systems

The solubility of (14)C-labelled barium carbonate has been determined in basic aqueous solutions with and without added Ba(2+) present and in aqueous solutions containing no added Ba(2+) or OH(-) ions. By use of activity coefficients from the literature, K(sp) has been determined to be 4.0 x 10(-10) +/- 0.5 x 10(-10) at 25 degrees .     

Conformal prediction of HDAC inhibitors

The growing interest in epigenetic probes and drug discovery, as revealed by several epigenetic drugs in clinical use or in the lineup of the drug development pipeline, is boosting the generation of screening data. In order to maximize the use of structure–activity relationships there is a clear need to develop robust and accurate models to understand the underlying structure–activity relationship. Similarly, accurate models should be able to guide the rational screening of compound libraries. Herein we introduce a novel approach for epigenetic quantitative structure–activity relationship (QSAR) modelling using conformal prediction. As a case study, we discuss the development of models for 11 sets of inhibitors of histone deacetylases (HDACs), which are one of the major epigenetic target families that have been screened. It was found that all derived models, for every HDAC endpoint and all three significance levels, are valid with respect to predictions for the external test sets as well as the internal validation of the corresponding training sets. Furthermore, the efficiencies for the predictions are above 80% for most data sets and above 90% for four data sets at different significant levels. The findings of this work encourage prospective applications of conformal prediction for other epigenetic target data sets.     

pH-dependent chiral vesicles from enantiomeric sodium 2,3-bis(decyloxy) succinate in aqueous solution

Enantiomeric, twin-tailed, twin-chiral, sodium (2R,3R)-(+)-bis(decyloxy)succinate and sodium (2S,3S)-(-)-bis(decyloxy)succinate have been synthesized and characterized. Surface tension, conductivity, and steady-state fluorescence spectroscopic measurements confirmed the presence of two aggregation concentrations, namely, the critical micellar concentration (CMC) and the critical vesicle concentration (CVC). The compounds behaved as true surfactants, with a CMC of 0.05 mM, and formed vesicles spontaneously in aqueous solution at a CVC of 0.14 mM. The compounds formed myelin figures in contact experiments, suggesting the formation of bilayers in aqueous solution culminating into individual vesicles. The vesicles were of 500-800 nm size and formed egg shells, porous spheres, and multivesicular vesicles, confirmed from transmission electron microscopy and optical microscopic techniques. The vesicles were found to be pH sensitive, were stable in the pH range 6-8, and formed the insoluble diacid at acidic pH due to protonation of the carboxylate head groups.     

pH-dependent self-assembly of polystyrene-block-poly((sulfamate-carboxylate)isoprene) copolymer in aqueous media

The amphiphilic polystyrene- block-poly((sulfamate-carboxylate)isoprene) (PS-PISC) diblock copolymer was synthesized from the precursor diblock copolymer polystyrene- block-isoprene by reaction with chlorosulfonyl isocyanate. The structure and behavior of self-assembled PS-PISC nanoparticles was studied in alkaline and acidic aqueous solutions by a combination of static and dynamic light scattering, analytical ultracentrifugation, atomic force and cryogenic transmission electron microscopies, NMR spectroscopy, potentiometric titration, and fluorometry using pyrene as a polarity-sensitive fluorescent probe. It was found that PS-PISC exists in aqueous solutions in the form of micellar aggregates. The aggregation tendency increases with decreasing effective charge density in the shell, that is, with decreasing pH of the solution, and aggregates found in alkaline aqueous media have much smaller molar masses than those formed in acidic media. The latter are dense, collapsed structures with immobile PISC domains in which most of the COOH and NH 2 (+)SO 3 (-) groups are buried inside of the nanoparticles. The swelling of PISC domains and disentanglement of PISC chains after addition of a base are slow processes occurring on the time scale of days.     

Identification of Histone deacetylase (HDAC)‐Associated Proteins with DNA‐Programmed Affinity Labeling

Histone deacetylase (HDAC) is a major class of deacetylation enzymes. Many HDACs exist in large protein complexes in cells and their functions strongly depend on the complex composition. The identification of HDAC‐associated proteins is highly important in understanding their molecular mechanisms. Although affinity probes have been developed to study HDACs, they were mostly targeting the direct binder HDAC, while other proteins in the complex remain underexplored. We report a DNA‐based affinity labeling method capable of presenting different probe configurations without the need for preparing multiple probes. Using one binding probe, 9 probe configurations were created to profile HDAC complexes. Notably, this method identified indirect HDAC binders that may be inaccessible to traditional affinity probes, and it also revealed new biological implications for HDAC‐associated proteins. This study provided a simple and broadly applicable method for characterizing protein‐protein interactions.     

Osmium(ii) tethered half-sandwich complexes: pH-dependent aqueous speciation and transfer hydrogenation in cells

Aquation is often acknowledged as a necessary step for metallodrug activity inside the cell. Hemilabile ligands can be used for reversible metallodrug activation. We report a new family of osmium(ii) arene complexes of formula [Os(η⁶-C₆H₅(CH₂)₃OH)(XY)Cl]^+/0 (1–13) bearing the hemilabile η⁶-bound arene 3-phenylpropanol, where XY is a neutral N,N or an anionic N,O⁻ bidentate chelating ligand. Os–Cl bond cleavage in water leads to the formation of the hydroxido/aqua adduct, Os–OH(H). In spite of being considered inert, the hydroxido adduct unexpectedly triggers rapid tether ring formation by attachment of the pendant alcohol–oxygen to the osmium centre, resulting in the alkoxy tethered complex [Os(η⁶-arene-O-κ¹)(XY)]ⁿ⁺. Complexes 1C–13C of formula [Os(η⁶:κ¹-C₆H₅(CH₂)₃OH/O)(XY)]⁺ are fully characterised, including the X-ray structure of cation 3C. Tether-ring formation is reversible and pH dependent. Osmium complexes bearing picolinate N,O-chelates (9–12) catalyse the hydrogenation of pyruvate to lactate. Intracellular lactate production upon co-incubation of complex 11 (XY = 4-Me-picolinate) with formate has been quantified inside MDA-MB-231 and MCF7 breast cancer cells. The tether Os–arene complexes presented here can be exploited for the intracellular conversion of metabolites that are essential in the intricate metabolism of the cancer cell.

New Os(ii) half-sandwich complexes bearing a pendant alcohol prompt reversible tether-ring formation upon aquation, protecting Os against deactivation. Excitingly, these complexes mediate hydrogenation of pyruvate to lactate inside cancer cells.     

pH-dependent x-ray absorption spectra of aqueous boron oxides

Near edge x-ray absorption fine structure (NEXAFS) spectra at the boron K-edge were measured for aqueous boric acid, borate, and polyborate ions, using liquid microjet technology, and compared with simulated spectra calculated from first principles density functional theory in the excited electron and core hole (XCH) approximation. Thermal motion in both hydrated and isolated molecules was incorporated into the calculations by sampling trajectories from quantum mechanics∕molecular mechanics simulations at the experimental temperature. The boron oxide molecules exhibit little spectral change upon hydration, relative to mineral samples. Simulations reveal that water is arranged nearly isotropically around boric acid and sodium borate, but the calculations also indicate that the boron K-edge NEXAFS spectra are insensitive to hydrogen bonding, molecular environment, or salt interactions.