Collagen immobilised on silica derivatives as a new stationary phase for HPLC

Comparison of supercritical fluid chromatographic methods to predict the skin permeability of pharmaceutical and cosmetic compounds

Supercritical fluid chromatography (SFC) was explored as an alternative for liquid chromatography to predict the skin permeability of pharmaceutical and cosmetic compounds. Nine dissimilar stationary phases were applied to screen a test set of 58 compounds. The experimental retention factors (log k), in addition to two sets of theoretical molecular descriptors, were applied to model the skin permeability coefficient. Different modelling approaches, i.e. multiple linear regression (MLR) and partial least squares (PLS) regression, were used. In general, the MLR models performed better than the PLS models for a given descriptor set. The results obtained on a cyanopropyl (CN) column provided the best correlation with the skin permeability data. The retention factors obtained on this column were included in a simple MLR model, together with the octanol-water partition coefficient and the number of atoms (r² = 0.81, RMSEC = 0.537 or 20.5% and RMSECV = 0.580 or 22.1%). The overall best MLR model included the chromatographic descriptor from a phenyl column and 18 descriptors (r² = 0.98, RMSEC = 0.167 or 6.2% and RMSECV = 0.238 or 8.9%). This model showed a good fit, on top of very good predictive features. However, stepwise MLR models with a reduced complexity could also be determined, with the best performance parameters obtained with the CN-column based retention and eight descriptors (r² = 0.95, RMSEC = 0.282 or 10.7% and RMSECV = 0.353 or 13.4%). SFC thus provides a suitable alternative to the liquid chromatographic techniques previously applied to model the skin permeability.

Evaluating micellar liquid chromatographic methods on octadecyl particle-based and monolithic columns to predict the skin permeation of drug and cosmetic molecules

A micellar liquid chromatographic method was developed to assist in the modeling of the skin permeability of pharmaceutical and cosmetic compounds. The composition of the mobile phase was determined by means of a two-factor central composite design, after which it was tested on both a particle-based and monolithic column. The latter provided the opportunity to increase the flow rate from 1 to 8 mL/min without reaching too high backpressures. The micellar conditions allowed analyzing a large test set of compounds with diverse characteristics with just one mobile-phase composition. The obtained experimental chromatographic descriptors besides two sets of theoretical molecular descriptors were used to model the skin permeability coefficient log K_p, applying multiple linear regression and partial least squares regression approaches. The micellar method on the monolithic column provided useful models with similar or even slightly better performance parameters than the method on the particle-based column. Furthermore, a much faster analysis can be achieved when applying a flow rate of 8 mL/min, making the micellar monolithic method ideal to estimate skin permeability.

Comparison of in-silico modelling and reversed-phase liquid chromatographic retention on an octadecyl silica column to predict skin permeability of pharmaceutical and cosmetic compounds

This study focuses on the in-silico modelling of the skin permeability using a test set of pharmaceutical and cosmetic compounds. Two sets of theoretical molecular descriptors, obtained from the E-Dragon and Vega ZZ software programs, were used in the models. Different linear regression methods, i.e. Multiple Linear Regression (MLR) and Partial Least Squares (PLS) regression, were applied for modelling and estimating the skin permeability. The best model was obtained using a stepwise MLR approach on the E-Dragon descriptor set. In a second step, the retention of the test set compounds was measured on a C18 column at two pH levels: pH 5.5 and pH 7. Different organic-modifier fractions were applied in the mobile phase to be able to extrapolate the retention factors to a log k_w value, with k_w the estimated retention factor in an aqueous mobile phase without organic modifier. Thereafter it was examined whether combining this chromatographic descriptor with the theoretical descriptors could improve the modelling of the skin permeability. The chromatographic descriptor often did not show an added value compared to the models containing only theoretical descriptors. Therefore, the in-silico models were preferred, and these models could be useful to predict the skin permeability of pharmaceutical and cosmetic compounds.

Emerging or Underestimated Silica-Based Stationary Phases in Liquid Chromatography

Several newly synthesized or forgotten silica-based stationary phases proposed for liquid chromatography are described, including non-endcapped, short-chain alkyl phases; hydrophilic and polar-endcapped stationary phases; polar-embedded alkyl phases; long-chain alkyl phases. Stationary phases with aromatic, cyanopropyl, diol and aminopropyl functionalities are also reviewed. Stationary phases of particular interest are biomolecular materials - based on immobilized cholesterol, aminoacids, peptides, proteins or lipoproteins. Packing materials involving macrocyclic chemistry (crown ethers; calixarenes; aza-macrocycles; oligo-and polysaccharides including these of marine origin - chitin- or chitosan-based; macrocyclic antibiotics) are discussed. Since many stationary phases developed for one type of applications (e.g. chiral separation) have been found useful in solving other analytical problems (e.g. drug's plasma protein binding ability), it seemed reasonable to discuss particular chemistries behind the stationary phases presented in this review rather than specific types of interactions or chromatographic modes.

Quantitative structure-retention relationships in affinity high-performance liquid chromatography

In this report the affinity high-performance liquid chromatography data, which were determined on silica-based human serum albumin, alpha1-acid glycoprotein, keratin, collagen, melanin, amylose tris(3,5-dimethylphenylcarbamate), and basic fatty acid binding protein columns, are discussed. Using a quantitative structure-retention relationship (QSRR) approach the affinity data were interpreted in terms of structural requirements of specific binding sites on biomacromolecules. The unique chromatographic properties of immobilized artificial membrane and cholesterol stationary phases were also analyzed from the point of view of mimicking biological processes. It has been demonstrated that chemometric processing of appropriately designed sets of chromatographic data derived in systems comprising biomolecules provides information of relevance for molecular pharmacology and rational drug design.

High-performance affinity chromatography: a powerful tool for studying serum protein binding

High-performance affinity chromatography (HPAC) is a method in which a biologically-related ligand is used as a stationary phase in an HPLC system. This approach is a powerful means for selectively isolating or quantitating agents in complex samples, but it can also be employed to study the interactions of biological systems. In recent years there have been numerous reports in which HPAC has been used to examine the interactions of drugs, hormones and other substances with serum proteins. This review discusses how HPAC has been used in such work. Particular attention is given to the techniques of zonal elution and frontal analysis. Various applications are provided for these techniques, along with a list of factors that need to be considered in their optimization and use. New approaches based on band-broadening studies and rapid immunoextraction are also discussed.

Quantitative structure/retention relationships in affinity chromatography

Affinity chromatography (AC) followed by quantitative structure/retention relationships (QSRR) analysis provides information on both the analytes and the macromolecules forming the stationary phases. QSRR equations derived for test series of analytes (often drugs) are interpreted in terms of structural requirements of the specific binding sites on macromolecules. Chromatographically demonstrated differences in analyte/macromolecule interactions may be relevant to molecular pharmacology and rational drug design. Multiple regression analysis of appropriately designed sets of affinity-chromatographic data may help increase the speed and efficiency of search as for new drugs and reduce the need for in vivo screening. Specific high-performance affinity-chromatographic separations can be optimized by rational selection of chiral columns, the characteristics of which are provided by QSRR.

Applications of immobilized stationary-phase liquid chromatography: a potential in vitro technique

Immobilized artificial-membrane chromatography is a potential in vitro technique for determining lipophilicity and studying drug transport and membrane interactions. It is reproducible, efficient and simple. Several other and newer applications of immobilized stationary-phase liquid chromatography have been reported, including the purification of membrane proteins, the synthesis of biomolecules and the simultaneous determination of enzyme activity and enantioselectivity. This article describes the immobilized artificial-membrane concept and provides an overview of the applications, advantages and limitations, in general, of immobilized stationary-phase chromatography.

Connection between chromatographic data and biological data

There are no previous references to the direct use of GLC data in the correlation of biological processes, but we show that GLC retention data can be used in the correlation of several such processes involving gaseous solutes. There are a number of reports of RP-HPLC and MEKC data being used in the correlation of biological processes, but they are mostly restricted as to the number and type of solute studied. We show that if chromatographic data are used to obtain solvation descriptors for solutes, and if these descriptors are then used in the correlation of biological processes, that this indirect connection is a much more powerful and generally applicable method than is the direct connection between chromatographic data and biological data.

Retention data from affinity high-performance liquid chromatography in view of chemometrics

A combination of affinity chromatography and chemometrics is demonstrated to provide information on drug analytes and on biomacromolecules forming stationary phases, which is of relevance to molecular pharmacology and to rational drug design. The approach can also be applied to elucidate the molecular mechanism of enantioseparation on natural biopolymer stationary phases. Affinity high-performance liquid chromatographic data, which were determined on silica-based human serum albumin, alpha1-acid glycoprotein, keratin, collagen, melanin and amylose tris(3,5-dimethylphenylcarbamate) stationary phases, are discussed. Quantitative structure-retention relationships (QSRRs) derived for test series of drug analytes are interpreted in terms of structural requirements of specific binding sites on biomacromolecules. A means to quantify the differences in drug-biomacromolecule binding among the members of analyte families is demonstrated based on hydrophobicity and structural descriptors from molecular modeling. Chemometric processing of appropriately designed sets of affinity chromatographic data may increase the speed and efficiency of a search for new drugs, providing at the same time a chance to reduce the number of in vivo screenings. It can also be of help in rational selection of chiral columns for specific analytical separations.