NMR Characterization of Substituted Aromatic Poly (Ether Sulofone)s

Abstract

The synthesis of a variety of substituted bisphenol A polysulfones, including nitro, amino, aminomethyl, ethyl, and methyl derivatives, is described. Nuclear magnetic resonance (NMR) (both proton and carbon, and several 2-D experiments) data confirm conclusions on the substitution site based on arguments on inductive effects in the phenyl rings. The proton ortho to the oxygen in the bisphenol A (BPA) residue is replaced in electrophilic substitution reactions. The degree of substitution was also calculated from the NMR results. The ethyl and methyl derivatives were expected, from the starting reactants, to each have a BPA ring substituted. The NMR data showed that, on the average, this is true. The nitro derivative also has substitution in every BPA ring, while the amino and aminomethyl derivatives have only intermittent BPA rings substituted. Measured degrees of substitution (DS) varied from 0.11 to 2.25.     

Ethylene spacer-linked bis-acetamidopyridine for dicarboxylic acid recognition and polymeric new wave-like anti-perpendicular arrangement of a host–guest in the solid state

In this paper, 1,2-bis(2-acetamido-6-pyridyl)ethane, receptor 1, having an ethylene spacer is reported to recognise dicarboxylic acids. The binding study in the solution phase is carried out using ¹H NMR (1:1) and UV–vis experiments and in the solid phase by single-crystal X-ray analysis. In ¹H NMR, the downfield shifts of specific amide protons of receptor 1 in 1:1 complexes of receptor and guest diacids, and in the UV–vis experiment, the appearance of an isosbestic point as well as significant binding constants are observed, which thus unambiguously support the complexation of receptor 1 with dicarboxylic acids in solution. Receptor 2, simple 2-acetamido-6-methylpyridine, has lower binding constants than receptor 1 due to cooperative binding of two pyridine amide groups with two acid groups of diacids. In the solid phase, the ditopic receptor 1 shows a grid-like polymeric hydrogen-bonded network that changes to a polymeric wave-like 1:1 anti-perpendicular network instead of the syn–syn polymeric 1:1 (Goswami, S.; Dey, S.; Fun, H.-K.; Anjum, S.; Rahman, A.-U. Tetrahedron Lett. 2005 (a) Goswami, S., Ghosh, K. and Dasgupta, S. 2000. J. Org. Chem., 65: 1907–1914. (b) Goswami, S.; Ghosh, K.; Mukherjee, R. Tetrahedron2001, 57, 4987–4993. (c) Goswami, S.; Ghosh, K.; Halder, M. Tetrahedron Lett.1999, 40, 1735–1738. (d) Goswami, S.; Dey, S.; Fun, H.-K.; Anjum, S.; Rahman, A.-U. Tetrahedron Lett.2005, 46, 7187–7191. (e) Goswami, S.; Jana, S.; Dey, S.; Razak, I.A.; Fun, H.-K. Supramol. Chem.2006, 18, 571–574. (f) Goswami, S.; Jana, S.; Fun, H.-K. Cryst. Eng. Comm.2008, 10, 507–517. (g) Goswami, S.; Jana, S.; Dey, S.; Sen, D.; Fun, H.-K.; Chantrapromma, S. Tetrahedron2008,64, 6426–6433. (h) Goswami, S.; Dey, S.; Jana, S. Tetrahedron2008, 64, 6358–6363 [Google Scholar], 46, 7187–7191), anti–anti polymeric 1:1 (Goswami, S.; Jana, S.; Dey, S.; Razak, I.A.; Fun, H.-K. Supramol. Chem. 2006 (a) Goswami, S., Ghosh, K. and Dasgupta, S. 2000. J. Org. Chem., 65: 1907–1914. (b) Goswami, S.; Ghosh, K.; Mukherjee, R. Tetrahedron2001, 57, 4987–4993. (c) Goswami, S.; Ghosh, K.; Halder, M. Tetrahedron Lett.1999, 40, 1735–1738. (d) Goswami, S.; Dey, S.; Fun, H.-K.; Anjum, S.; Rahman, A.-U. Tetrahedron Lett.2005, 46, 7187–7191. (e) Goswami, S.; Jana, S.; Dey, S.; Razak, I.A.; Fun, H.-K. Supramol. Chem.2006, 18, 571–574. (f) Goswami, S.; Jana, S.; Fun, H.-K. Cryst. Eng. Comm.2008, 10, 507–517. (g) Goswami, S.; Jana, S.; Dey, S.; Sen, D.; Fun, H.-K.; Chantrapromma, S. Tetrahedron2008,64, 6426–6433. (h) Goswami, S.; Dey, S.; Jana, S. Tetrahedron2008, 64, 6358–6363 [Google Scholar], 18, 571–574; Goswami, S.; Jana, S.; Fun, H.-K. Cryst. Eng. Comm. 2008, 10, 507–517; Goswami, S.; Jana, S.; Dey, S.; Sen, D.; Fun, H.-K.; Chantrapromma, S. Tetrahedron 2008, 64, 6426–6433), syn–syn 2:2 (Karle, I.L.; Ranganathan, D.; Haridas, V. J. Am. Chem. Soc. 1997 (a) Garcia-Tellado, F., Goswami, S., Chang, S.K., Geib, S.J. and Hamilton, A.D. 1990. J. Am. Chem. Soc., 112: 7393–7394. (b) Geib, S.J.; Vicent, C.; Fan, E.; Hamilton, A.D. Angew. Chem. Int. Ed. Engl.1993, 32, 119–121. (c) Garcia-Tellado, F.; Geib, S.J.; Goswami, S.; Hamilton, A.D. J. Am. Chem. Soc.1991, 113, 9265–9269. (d) Karle, I.L.; Ranganathan, D.; Haridas, V. J. Am. Chem. Soc.1997, 119, 2777–2783. (e) Moore, G.; Papamicaël, C.; Levacher, V.; Bourguignon, J.; Dupas, G. Tetrahedron2004, 60, 4197–4204. (f) Korendovych, I.V.; Cho, M.; Makhlynets, O.V.; Butler, P.L.; Staples, R.J.; Rybak-Akimova, E.V. J. Org. Chem.2008, 73, 4771–4782. (g) Ghosh, K.; Masanta, G.; Fröhlich, R.; Petsalakis, I.D.; Theodorakopoulos, G. J. Phys. Chem. B2009, 113, 7800–7809 [Google Scholar], 119, 2777–2783) or top–bottom-bound 1:1 (Garcia-Tellado, F.; Goswami, S.; Chang, S.K.; Geib, S.J.; Hamilton, A.D. J. Am. Chem. Soc. 1990 (a) Goswami, S., Ghosh, K. and Dasgupta, S. 2000. J. Org. Chem., 65: 1907–1914. (b) Goswami, S.; Ghosh, K.; Mukherjee, R. Tetrahedron2001, 57, 4987–4993. (c) Goswami, S.; Ghosh, K.; Halder, M. Tetrahedron Lett.1999, 40, 1735–1738. (d) Goswami, S.; Dey, S.; Fun, H.-K.; Anjum, S.; Rahman, A.-U. Tetrahedron Lett.2005, 46, 7187–7191. (e) Goswami, S.; Jana, S.; Dey, S.; Razak, I.A.; Fun, H.-K. Supramol. Chem.2006, 18, 571–574. (f) Goswami, S.; Jana, S.; Fun, H.-K. Cryst. Eng. Comm.2008, 10, 507–517. (g) Goswami, S.; Jana, S.; Dey, S.; Sen, D.; Fun, H.-K.; Chantrapromma, S. Tetrahedron2008,64, 6426–6433. (h) Goswami, S.; Dey, S.; Jana, S. Tetrahedron2008, 64, 6358–6363 [Google Scholar], 112, 7393–7394) co-crystals.

     

Influence of amidoammonium calix[4]resorcinarenes on methyl orange protolytic equilibrium: supramolecular indicator systems

Here, we report on the study of cationic amidoammonium calix[4]resorcinarenes 1–5 of various lipophilicity capable of binding acid–base indicator methyl orange (MO). We identified the contributions of macrocycle aggregation and conformational mobility in the binding of MO. The effective pK_a values of bound MO systematically decrease as the size and the packing density of the aggregates increase with an increase in calixresorcinarene lipophilicity. Consideration of a series of macrocycles clearly shows that large aggregates form most stable complexes, binding guests not on individual level but as aggregates. It was found that the most stable MO complex with 5 is formed due to electrostatic binding with ammonium groups of the macrocycle and incapsulation of MO in a hydrophobic layer of the aggregates. We have shown that competitive binding of MO and cationic surfactants by aggregates of 5 is suitable for visual/spectrophotometric detection of colourless anionic substrates.     

Dimerisation and complexation of 6-(4′-t-butylphenylamino)naphthalene-2-sulphonate by β-cyclodextrin and linked β-cyclodextrin dimers

This study shows that stereochemical factors largely determine the extent to which 6-(4′-t-butylphenylamino)-naphthalene-2-sulphonate, BNS^?  and its dimer, (BNS^? )₂, are complexed by β-cyclodextrin, βCD, and a range of linked βCD dimers. Fluorescence and ¹H NMR studies, respectively, show that BNS^?  and (BNS^? )₂ form host–guest complexes with βCD of the stoichiometry βCD.BNS^?  (10^? 4 K ₁ = 4.67 dm³ mol^? 1) and βCD.BNS₂ ^2 ?  (10^? 2 K ₂′ = 2.31 dm³ mol^? 1), where the complexation constant K ₁ = [βCD.BNS^? ]/([βCD][BNS^? ]) and K ₂′ = [βCD. (BNS^? )₂]/([βCD.BNS^? ][BNS^? ]) in aqueous phosphate buffer at pH 7.0, I = 0.10 mol dm³ at 298.2 K. (The dimerisation of BNS^?  is characterised by 10^? 2 K _d = 2.65 dm³ mol^? 1.) For N,N-bis((2^AS,3^AS)-3^A-deoxy-3^A-β-cyclodextrin)succinamide, 33βCD₂su, N-((2^AS,3^AS)-3^A-deoxy-3^A-β-cyclodextrin)-N′-(6^A-deoxy-6^A-β-cyclodextrin)urea, 36βCD₂su, N,N-bis(6^A-deoxy-6^A-β-cyclodextrin)succinamide, 66βCD₂su, N-((2^AS,3^AS)-3^A-deoxy-3^A-β-cyclodextrin)-N′-(6^A-deoxy-6^A-β-cyclodextrin)urea, 36βCD₂ur, and N,N-bis(6^A-deoxy-6^A-β-cyclodextrin)urea, 66βCD₂ur, the analogous 10^? 4 K ₁ = 11.0, 101, 330, 29.6 and 435 dm³ mol^? 1 and 10^? 2 K ₂′ = 2.56, 2.31, 2.59, 1.82 and 1.72 dm³ mol^? 1, respectively. A similar variation occurs in K ₁ derived by UV–vis methods. The factors causing the variations in K ₁ and K ₂ are discussed in conjunction with ¹H ROESY NMR and molecular modelling studies.     

Synthesis and anion binding of 2-arylazo-meso-octamethylcalix[4]pyrroles

2-Arylazo-5,5,10,10,15,15,20,20-octamethylcalix[4]pyrroles (azo-OMCPs) have been synthesised by the reaction of calix[4]pyrrole with aryldiazonium chloride in 15–45% yields. The solution-state binding studies of the synthesised hosts were investigated by absorption spectroscopy and ¹H NMR in DMSO and CDCl₃, respectively. These receptors, appended with electron-donating and electron-withdrawing groups, displayed enhanced affinity and selectivity for fluoride anion. Well-defined colour change in the visible region of the spectrum was observed upon addition of fluoride ion in DMSO solution of azo-OMCPs. Detailed NMR studies in CDCl₃ revealed that azo-OMCPs with nitro and chloro groups have higher binding affinity for fluoride ion.

     

Interaction between tetramethylcucurbit[6]uril with α-furaldehyde-isonicotinyl-hydrazone hydrochloride

Interaction between tetramethylcucurbit[6]uril (TMeQ[6], host) and the hydrochloride salt of α-furaldehyde-isonicotinyl-hydrazone hydrochloride (FIHH⁺, guest) was investigated using X-ray crystallography and spectroscopic methods. X-ray crystallography showed that the π–π stacking effect and hydrogen bonding resulted in the formation of a dumbbell-shaped supramolecule which contained two FIHH⁺@TMeQ[6] host–guest inclusion complexes. The host–guest interaction provided identifiable changes in the vibrational frequencies in the IR spectra. ¹H NMR spectral analysis established a similar interaction model and revealed that TMeQ[6] preferred to include the furan moiety over the pyridine moiety of the FIHH⁺ guest molecule. Absorption spectrophotometric analysis suggested that the host and guest interact in a ratio of 1:1 with a stability constant K _s = (3.52 ± 0.74) × 10⁶ l mol^? 1.pH titration confirmed that the host–guest interaction led to a clear change in the protonation constant of the title guest. Quantum chemical calculations were used to determine the possible mechanism of formation of the dumbbell-shaped complex.     

Development of an information-intensive structure–activity relationship model and its application to human respiratory chemical sensitizers

Structure–activity relationship (SAR) models are recognized as powerful tools to predict the toxicologic potential of new or untested chemicals and also provide insight into possible mechanisms of toxicity. Models have been based on physicochemical attributes and structural features of chemicals. We describe herein the development of a new SAR modeling algorithm called cat-SAR that is capable of analyzing and predicting chemical activity from divergent biological response data. The cat-SAR program develops chemical fragment-based SAR models from categorical biological response data (e.g. toxicologically active and inactive compounds). The database selected for model development was a published set of chemicals documented to cause respiratory hypersensitivity in humans. Two models were generated that differed only in that one model included explicate hydrogen containing fragments. The predictive abilities of the models were tested using leave-one-out cross-validation tests. One model had a sensitivity of 0.94 and specificity of 0.87 yielding an overall correct prediction of 91%. The second model had a sensitivity of 0.89, specificity of 0.95 and overall correct prediction of 92%. The demonstrated predictive capabilities of the cat-SAR approach, together with its modeling flexibility and design transparency, suggest the potential for its widespread applicability to toxicity prediction and for deriving mechanistic insight into toxicologic effects.     

Theory of docking scores and its application to a customizable scoring function

In general, the docking scoring tends to have a size dependence related to the ranking of compounds. In this paper, we describe a novel method of parameter optimization for docking scores which reduce the size dependence and can efficiently discriminate active compounds from chemical databases. This method is based on a simplified theoretical model of docking scores which enables us to utilize large amounts of data of known active and inactive compounds for a particular target without requiring large computational resources or a complicated procedure. This method is useful for making scoring functions for the identification of novel scaffolds using the knowledge of active compounds for a particular target or a customized scoring function for an interesting family of drug targets.