Model pharmaceutical co-crystallization: Guest-directed assembly of caffeine and aromatic tri-hydroxy and dicarboxylic acids into different heteromolecular hydrogen bonding networks in solid state

Three model pharmaceutical caffeine-containing co-crystals of 1,3,5-trihydroxybenzene (phloroglucinol), isophthalic acid and 5-hydroxyisophthalic acid were synthesized and characterized via single-crystal X-ray diffraction. The three crystalline forms reported are an anhydrous co-crystal and other two are co-crystal hydrates. Also their binding properties were studied by UV-vis analysis. In each of these structures, an organised intermolecular hydrogen bonding motif was observed. A comparison of hydrogen bonding motifs in the crystal sheets was presented.     

Discrete spatial symmetries: Redundant coordinates and search for stationary points in reduced spaces

Given the invariance of an N-body system under discrete operations of reflection, inversion, a rotation by 2π/n, and the corresponding relations among the derivatives of energy, we have constructed through an invertible transformation a set of active and redundant coordinates. Movement along the active coordinates preserves all symmetry relations. We show that algorithms for locating stationary points or for calculating reaction paths are exactly separable in these active and redundant coordinates. We further show that this formalism is equally applicable when equations of constraints among coordinates are specified for the movement of particles. This includes geometrical constraints on bond lengths, angles, substituent group internal rotations, etc. This formalism enhances the efficiency since (laborious) cartesian derivatives need to be calculated only for the active variables and that the problem is reduced in term of m(?3N) variables. We apply this procedure to obtain the equilibrium geometry of H₂O molecule within the subspace of C_2v symmetry configurations ab initio derivatives.     

Mixed-pole terms in the anisotrophy of the long-range interaction coefficients for H2He and H2H2

It is shown that mixed-pole terms can make significant, and even dominant, contributions to the anisotropy of the long-range interaction C₈ coefficients for H₂He and H₂H₂.     

Interatomic forces and Compton profiles

The virial theorem is used to derive rigorous relationships between the nuclear framework dependence of the impulse approximation Compton profile of a polyatomic molecule and its Born–Oppenheimer potential energy surface along a uniform scaling path. The interatomic energy- and force-related difference Compton profiles for H₂ are examined as an illustration.     

Medium effects on the reactions of coordination complexes: Base hydrolysisof(αβS)(p-hydroxybenzoato)(tetraethylenepentamine) cobalt(III) in iso-propanol–water,tert-butanol–water and dimethyl sulfoxide–water media

The base hydrolysis of (S)(p-hydroxybenzoato)-(tetraethylenepentamine)cobalt(III) has been investigated in aqueous–organic solvent media using i-PrOH, t-BuOH and dimethyl sulfoxide (DMSO) as cosolvents at 20.0 T (°C) 40.0 (I=0.02 mol dm ^-3) with 80% (v/v) of cosolvents. Only the base-catalysed path (k_obs=k_OH[OH^-]) is observed. The relative second order rate constant k _OH ^os /k _OH ^ow at I=0 increases nonlinearly with increasing mol fraction (x_O.S.) of the cosolvents, the rate acceleration in alcoholic cosolvents being greater than in DMSO. The destabilization of ^-OH in mixed solvent media alone does not explain the observed rate acceleration. The solvent composition dependence, log k _OH ^os = log k _OH ^ow + a_ix _os ⁱ [i=1,2,k _OH ⁰ denotes k_OH at I=0 in mixed solvent(s) and water (w)] indicates specific solute–solvent interactions. The values of the relative transfer free-energy data [_TG(t.s.) - _TG^o (i.s.)](sw)(25 °C)(G), where t.s. and i.s. denote the transition state and initial state of the substrates respectively, are positive for all substrates at all compositions, indicating a greater destabilizing effect of the mixed solvent on the transition state than on the initial state. The G values also correlate with G^E(G = ax_O.S. + cG^E) for all solvents, supporting the fact that solvent structural effects mediate the rates and energetics of the reaction. However, the solvent effects on the solvation components of H and S are mutually compensating, thus indicating that there is no change in the mechanism.     

A Predictive Approach Using Fractal Analysis for Analyte-Receptor Binding and Dissociation Kinetics for Surface Plasmon Resonance Biosensor Applications

A predictive approach using fractal analysis is presented for analyte-receptor binding and dissociation kinetics for biosensor applications. Data taken from the literature may be modeled, in the case of binding using a single-fractal analysis or a dual-fractal analysis. The dual-fractal analysis represents a change in the binding mechanism as the reaction progresses on the surface. A single-fractal analysis is adequate to model the dissociation kinetics in the examples presented. Predictive relationships developed for the binding and the affinity (k(diss)/k(bind)) as a function of the analyte concentration are of particular value since they provide a means by which the binding and the affinity rate coefficients may be manipulated. Relationships are also presented for the binding and the dissociation rate coefficients and for the affinity as a function of their corresponding fractal dimension, D(f), or the degree of heterogeneity that exists on the surface. When analyte-receptor binding or dissociation is involved, an increase in the heterogeneity on the surface (increase in D(f)) leads to an increase in the binding and in the dissociation rate coefficient. It is suggested that an increase in the degree of heterogeneity on the surface leads to an increase in the turbulence on the surface owing to the irregularities on the surface. This turbulence promotes mixing, minimizes diffusional limitations, and leads subsequently to an increase in the binding and in the dissociation rate coefficient. The binding and the dissociation rate coefficients are rather sensitive to the degree of heterogeneity, D(f,bind) (or D(f1)) and D(f,diss), respectively, that exists on the biosensor surface. For example, the order of dependence on D(f,bind) (or D(f1)) and D(f2) is 6.69 and 6.96 for k(bind,1) (or k(1)) and k(2), respectively, for the binding of 0.085 to 0.339 μM Fab fragment 48G7(L)48G7(H) in solution to p-nitrophenyl phosphonate (PNP) transition state analogue immobilized on a surface plasmon resonance (SPR) biosensor. The order of dependence on D(f,diss) (or D(f,d)) is 3.26 for the dissociation rate coefficient, k(diss), for the dissociation of the 48G7(L)48G7(H)-PNP complex from the SPR surface to the solution. The predictive relationships presented for the binding and the affinity as a function of the analyte concentration in solution provide further physical insights into the reactions on the surface and should assist in enhancing SPR biosensor performance. In general, the technique is applicable to other reactions occurring on different types of biosensor surfaces and other surfaces such as cell-surface reactions. Copyright 2000 Academic Press.     

A fractal analysis of analyte-estrogen receptor binding and dissociation kinetics using biosensors: environmental effects

A fractal analysis is used to model the binding and dissociation kinetics between analytes in solution and estrogen receptors (ER) immobilized on a sensor chip of a surface plasmon resonance (SPR) biosensor. Both cases are analyzed: unliganded as well as liganded. The influence of different ligands is also analyzed. A better understanding of the kinetics provides physical insights into the interactions and suggests means by which appropriate interactions (to promote correct signaling) and inappropriate interactions such as with xenoestrogens (to minimize inappropriate signaling and signaling deleterious to health) may be better controlled. The fractal approach is applied to analyte-ER interaction data available in the literature. Numerical values obtained for the binding and the dissociation rate coefficients are linked to the degree of roughness or heterogeneity (fractal dimension, D(f)) present on the biosensor chip surface. In general, the binding and the dissociation rate coefficients are very sensitive to the degree of heterogeneity on the surface. For example, the binding rate coefficient, k, exhibits a 4.60 order of dependence on the fractal dimension, D(f), for the binding of unliganded and liganded VDR mixed with GST-RXR in solution to Spp-1 VDRE (1,25-dihydroxyvitamin D(3) receptor element) DNA immobilized on a sensor chip surface (Cheskis and Freedman, Biochemistry 35 (1996) 3300-3318). A single-fractal analysis is adequate in some cases. In others (that exhibit complexities in the binding or the dissociation curves) a dual-fractal analysis is required to obtain a better fit. A predictive relationship is also presented for the ratio K(A)(=k/k(d)) as a function of the ratio of the fractal dimensions (D(f)/D(fd)). This has biomedical and environmental implications in that the dissociation and binding rate coefficients may be used to alleviate deleterious effects or enhance beneficial effects by selective modulation of the surface. The K(A) exhibits a 112-order dependence on the ratio of the fractal dimensions for the ligand effects on VDR-RXR interaction with specific DNA.     

Analyte-receptor binding kinetics for biosensor applications

The diffusion-limited binding kinetics of antigen (analyte), in solution with antibody (receptor) immobilized on a biosensor surface, is analyzed within a fractal framework. Most of the data presented is adequately described by a single-fractal analysis. This was indicated by the regression analysis provided by Sigmaplot. A single example of a dual-fractal analysis is also presented. It is of interest to note that the binding-rate coefficient (k) and the fractal dimension (D_f) both exhibit changes in the same and in the reverse direction for the antigen-antibody systems analyzed. Binding-rate coefficient expressions, as a function of the D_f developed for the antigen-antibody binding systems, indicate the high sensitivity of thek on the D_f when both a single- and a dual-fractal analysis are used. For example, for a single-fractal analysis, and for the binding of antibody Mab 0.5β in solution to gpl20 peptide immobilized on a BIAcore biosensor, the order of dependence on the D_f was 4.0926. For a dual-fractal analysis, and for the binding of 25-100 ng/mL TRITC-LPS (lipopolysaccharide) in solution with polymyxin B immobilized on a fiberoptic biosensor, the order of dependence of the binding-rate coefficients, k₁ and k₂ on the fractal dimensions, D_f1 and D_f2, were 7.6335 and-11.55, respectively. The fractional order of dependence of thek(s) on the D_f(s) further reinforces the fractal nature of the system. Thek(s) expressions developed as a function of the D_f(s) are of particular value, since they provide a means to better control biosensor performance, by linking it to the heterogeneity on the surface, and further emphasize, in a quantitative sense, the importance of the nature of the surface in biosensor performance.     

A beta-cyclodextrin based fiber-optic chemical sensor: a fractal analysis

A fractal analysis is presented for the binding of pyrene in solution to beta-cyclodextrin attached to a fiber-optic chemical sensor. The specific (k(l)) and non-specific binding rate coefficients and the fractal dimension (D(f)) (specific binding case only) both tend to increase as the pyrene concentration in solution increases from 12.4 to 124 ng ml(-1). Predictive relations for the binding rate coefficient (specific as well as non-specific binding) and for D(f) (specific binding case only) as a function of pyrene concentration are provided. These relations fit the calculated k(l) and D(f) values in the pyrene concentration range reasonably well. Fractal analysis data seem to indicate that an increase in the pyrene concentration in solution increases the "ruggedness" or inhomogeneity on the fiber-optic biosensor surface. The fractal analysis provides novel physical insights into the reactions occuring on the fiber-optic chemical surface and should assist in the design of fiber-optic chemical sensors.