Gas chromatography-stable isotope ratio mass spectrometry prior solid phase microextraction and gas chromatography-tandem mass spectrometry: development and optimization of analytical methods to analyse garlic (Allium sativum L.) volatile fraction

Garlic (Allium sativum L.) is not only appreciated for its flavour and taste, but it is also recognized for various health properties. The European Commission, through the attribution of the Protected Designation of Origin (PDO) certification mark, has officially recognized some specific varieties of garlic. To protect not only the commercial value but also the reputation of this appreciated product, effective tools are therefore required. For the first time, a new compound specific isotope analysis method based on carbon stable isotopic ratio measurement of the three major volatile garlic compounds allyl alcohol (AA), diallyl disulphide (DD) and diallyl trisulphide (DT) through head-space solid phase microextraction (HS-SPME) followed by gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS) was developed. A within-day standard deviation (Srwithin-day) of 0.3 ‰, 0.4 ‰ and 0.2 ‰ for δ(13C) and a between-day standard deviation (Srbetween-day) of 0.8 ‰, 1.0 ‰ and 0.6 ‰ of AA, DT and DD was estimated. For the first time, the ranges of isotopic variability for the three volatile compounds of red garlic from two neighbouring Italian regions (Abruzzo and Lazio) were defined analysing 30 samples. The same dataset was also considered in analysing the percentage composition of the previously mentioned three volatile compounds through HS-SPME followed by gas chromatography-tandem mass spectrometry (GC-MS/MS). The two analytical approaches were combined in this explorative study, aiming to provide potential parameters to discriminate garlic samples based on their geographical origin.

Characterization of the Volatile Profiles of Insect Flours by (HS)-SPME/GC-MS: A Preliminary Study

The growing world population, combined with scarcities of agricultural land, water, forest, fisheries, and biodiversity resources, makes it necessary to search for alternative sources of nutrients. For this reason, in recent years, edible insects have been introduced into the diet, even in areas where entomophagy is not traditional. In light of this, the present study aims at characterizing the aromatic profile of three edible insects flours: cricket (Acheta domesticus, CP), buffalo worm (Alphitobius diaperinus, BW), and mealworm (Tenebrio molitor, MW). This goal has been achieved by means of an (HS)-SPME/GC-MS strategy. 67 compounds have been tentatively identified; of these, 27 are present only in the CP and BW flours, while 10 are common in all three flours. The compound with the highest peak's relative area in gas chromatograms of CP and BW flours is hexadecanoic acid, while in MW it is 1-heptylpyrrolidin-2-one. In general, we have observed that CP and BW flours have 37 compounds in common, and their volatile compositions along with their profiles are more similar to each other than to MW profile.

Synthesis of hydrophilic carbon nanotube sponge via post-growth thermal treatment

Clean water is vital for healthy ecosystems, for human life and, in a broader sense, it is directly linked to our socio-economic development. Nevertheless, climate change, pollution and increasing world population will likely make clean water scarcer in the near future. Consequently, it becomes imperative to develop novel materials and more efficient ways of treating waste and contaminated water. Carbon nanotube (CNT) sponges, for example, are excellent in removing oleophilic contaminants; however, due to their super-hydrophobic nature, they are not as efficient when it comes to absorbing water-soluble substances. Here, by means of a scalable method consisting of simply treating CNT sponges at mild temperatures in air, we attach oxygen-containing functional groups to the CNT surface. The functionalized sponge becomes hydrophilic while preserving its micro- and macro-structure and can therefore be used to successfully remove toxic contaminants, such as pesticides, that are dissolved in water. This discovery expands the current range of applications of CNT sponges to those fields in which a hydrophilic character of the sponge is more suitable.

Transfer of gas chromatographic retention data among poly(siloxane) columns by quantitative structure-retention relationships based on molecular descriptors of both solutes and stationary phases

In the present study, computational molecular descriptors of 90 saturated esters and seven poly(siloxane) stationary phases with different polarity (SE-30, OV-7, DC-710, OV-25, XE-60, OV-225 and Silar-5CP) were combined into quantitative structure-retention relationship (QSRR) models aimed at predicting the Kováts retention indices (RIs) of the solutes. The molecular descriptors (174) of the stationary phases included in the models were computed using Dragon software from poly(siloxane) oligomers made of 20 siloxane units reflecting the nominal composition of the stationary phase, whereas 439 molecular descriptors were adopted to represent the esters. Different QSRR models were generated by means of Partial Least Squares (PLS) regression to assess the accuracy of this approach in predicting the RIs of unexplored solutes both in known and external stationary phases. After calibration of each PLS model, the descriptors were selected/discarded according to their relevance, evaluated by Covariance Selection (CovSel), and the PLS models were re-built, which resulted in a noticeable improvement of their predictive ability. Firstly, all the available data were equally divided into a training and a test set; the model built on the calibration set was used to predict the RIs of the validation observations. Successively, seven diverse PLS models were created following a "leave-one-column-out" fashion procedure, each one finalized to the estimation of the RIs of the 90 esters associated with a single stationary phase, whereas the calibration model was calculated on the remaining data. All the estimated models provided successful results on the external stationary phase, and predictive performance further increased after variable selection based on CovSel analysis. The final models provided a Root Mean Square Error in Cross Validation (RMSECV) in the range 12-20, a Root Mean Square Error in Prediction (RMSEP) in the range 11-26, and Mean Absolute Percentage Errors in Prediction (MAMEPs) in the range 0.7-1.5, revealing accurate cross-column prediction. Eventually, to test the robustness of the proposed approach, the 90 solutes were equally partitioned into a calibration and a test set and two further QSSR strategies were applied. The first PLS model was calibrated on all the seven stationary phases and the RIs of the 45 external solutes in the same seven columns were simultaneously predicted. The last QSRR approach followed a "leave-one-column-out" scheme and RI of 45 test solutes on an external stationary phase was predicted by a PLS model calibrated with the data of the 45 remaining solutes and the six left stationary phases. After selection of the significant molecular descriptors, PLS regression provided RMSECV values in the range 6-19, RMSEPs in the range 10-14, and MAPEPs in the range 0.9-2.4, revealing the suitability of the approach to deduce the RI of unknown solutes in uncharted stationary phases.

Stable isotope ratio analysis combined with inductively coupled plasma-mass spectrometry for geographical discrimination between Italian and foreign saffron

Seventy-six samples of saffron were analysed through inductively coupled plasma-mass spectrometry (ICP-MS) and stable isotope ratio analysis. The dataset was formed by 67 samples harvested in different areas of Italy, Morocco and Iran, and nine samples purchased in the Italian market. For the first time, 42 elements and five stable isotopes (δ¹³ C, δ¹⁵ N, δ³⁴ S, δ² H and δ¹⁸ O) were considered to carry out the discrimination of the samples on the basis of their geographical origin. Combined ICP-MS and isotopic composition data turned out to be a useful tool for the geographical discrimination of saffron among predefined cultivation sites. K, Cr, Mn, Ni, Zn, Rb, Sr, Mo, Cs, Nd, Eu, Pb, δ¹³ C, δ¹⁵ N, δ³⁴ S and δ² H were identified as the significant variables in geographical discrimination. Moreover, the class models generated for saffron cultivated in two specific areas of Central Italy exhibited 100% specificity for Moroccan, Iranian and commercial samples and a high specificity (83% and 84%) for the saffron samples cultivated in other, although close, Italian sites.

Multivariate optimization of an analytical method for the analysis of Abruzzo white wines by ICP OES

An inductively coupled plasma-optical emission spectrometry (ICP OES) method was optimized and applied for determining the concentration of 14 elements (Ba, Ca, Co, Cu, Fe, K, Li, Mg, Mn, Na, Ni, Sr, V, and Zn) in three representative white wines of the Abruzzo region (Italy). In order to optimise an ICP OES method a three level factorial design for three variables was used. The intensity of the emission lines for analytes was simultaneously maximised by using Derringer's desirability function. Using this approach, the optimal experimental conditions for wine analysis of 0.48 L min-1, 1.8 mL min-1 and 0.5 L min-1 for the nebulizer gas flow rate, sample uptake rate and auxiliary gas flow rate respectively were achieved. A total of 46 white wine samples of the three varieties were analysed by using the optimised experimental conditions. Linear Discriminant Analysis (LDA) and Partial Least Squares Linear Discriminant Analysis (PLS LDA) allowed an acceptable classification of the three varietal samples.

Geographical Classification of Italian Saffron (Crocus sativus L.) by Multi-Block Treatments of UV-Vis and IR Spectroscopic Data

One-hundred and fourteen samples of saffron harvested in four different Italian areas (three in Central Italy and one in the South) were investigated by IR and UV-Vis spectroscopies. Two different multi-block strategies, Sequential and Orthogonalized Partial Least Squares Linear Discriminant Analysis (SO-PLS-LDA) and Sequential and Orthogonalized Covariance Selection Linear Discriminant Analysis (SO-CovSel-LDA), were used to simultaneously handle the two data blocks and classify samples according to their geographical origin. Both multi-block approaches provided very satisfying results. Each model was investigated in order to understand which spectral variables contribute the most to the discrimination of samples, i.e., to the characterization of saffron harvested in the four different areas. The most accurate solution was provided by SO-PLS-LDA, which only misclassified three test samples over 31 (in external validation).

Analysis of intraspecific seed diversity in Astragalus aquilanus (Fabaceae), an endemic species of Central Apennine

This work aims to study seeds of the endemic species Astragalus aquilanus from four different populations of central Italy. We investigated seed morpho-colorimetric features (shape and size) and chemical differences (through infrared spectroscopy) among populations and between dark and light seeds. Seed morpho-colorimetric quantitative variables, describing shape, size and colour traits, were measured using image analysis techniques. Fourier transform infrared (FT-IR) spectroscopy was used to attempt seed chemical characterisation. The measured data were analysed by step-wise linear discriminant analysis (LDA). Moreover, we analysed the correlation between the four most important traits and six climatic variables extracted from WorldClim 2.0. The LDA on seeds traits shows clear differentiation of the four populations, which can be attributed to different chemical composition, as confirmed by Wilk's lambda test (P < 0.001). A strong correlation between morphometric traits and temperature (annual mean temperature, mean temperature of the warmest and coolest quarter), colorimetric traits and precipitation (annual precipitation, precipitation of wettest and driest quarter) was observed. The characterisation of A. aquilanus seeds shows large intraspecific plasticity both in morpho-colorimetric and chemical composition. These results confirm the strong relationship between the type of seed produced and the climatic variables.

UHPLC Analysis of Saffron (Crocus sativus L.): Optimization of Separation Using Chemometrics and Detection of Minor Crocetin Esters

Ultra-high performance liquid chromatography (UHPLC) coupled with diode array detection (DAD) was applied to improve separation and detection of mono- and bis-glucosyl esters of crocetin (crocins), the main red-colored constituents of saffron (Crocus sativus L.), and other polar components. Response surface methodology (RSM) was used to optimise the chromatographic resolution on the Kinetex C18 (Phenomenex) column taking into account of the combined effect of the column temperature, the eluent flow rate and the slope of a linear eluent concentration gradient. A three-level full-factorial design of experiments was adopted to identify suitable combinations of the above factors. The influence of the separation conditions on the resolutions of 22 adjacent peaks was simultaneously modelled by a multi-layer artificial neural network (ANN) in which a bit string representation was used to identify the target analytes. The chromatogram collected under the optimal separation conditions revealed a higher number of crocetin esters than those already characterised by means of mass-spectrometry data and usually detected by HPLC. Ultra-high performance liquid chromatography analyses carried out on the novel Luna Omega Polar C18 (Phenomenex) column confirmed the large number of crocetin derivatives. Further work is in progress to acquire mass-spectrometry data and to clarify the chemical structure to the newly found saffron components.

Adsorption of triazine herbicides from aqueous solution by functionalized multiwall carbon nanotubes grown on silicon substrate

Multi-walled carbon nanotubes (MWCNTs), because of their small size and large available surface area, are potentially efficient sorbents for the extraction of water solutes. Dispersion of MWCNTs in aqueous medium is suitable to adsorb organic contaminants from small sample volumes, but, the recovery of the suspended sorbent for successive re-use represents a critical step, which makes this method inapplicable in large-scale water-treatment technologies. To overcome this problem, we proposed here MWCNTs grown on silicon supports and investigated on a small-volume scale their adsorption properties towards triazine herbicides dissolved in water. The adsorption efficiency of the supported MWCNTs has been tested on seven triazine herbicides, which are emerging water contaminants in Europe and USA, because of their massive use, persistence in soils and potential risks for the aquatic organisms and human health. The investigated compounds, in spite of their common molecular skeleton, cover a relatively large property range in terms of both solubility in water and hydrophilicity/hydrophobicity. The functionalisation of MWCNTs carried out by acidic oxidation, apart from increasing wettability of the material, results in a better adsorption performance. Increasing of functionalisation time between 17 and 60 h progressively increases the extraction of all seven pesticides and produces a moderate increment of selectivity.

Geographical identification of saffron (Crocus sativus L.) by linear discriminant analysis applied to the UV-visible spectra of aqueous extracts

We attempted geographical classification of saffron using UV-visible spectroscopy, conventionally adopted for quality grading according to the ISO Normative 3632. We investigated 81 saffron samples produced in L'Aquila, Città della Pieve, Cascia, and Sardinia (Italy) and commercial products purchased in various supermarkets. Exploratory principal component analysis applied to the UV-vis spectra of saffron aqueous extracts revealed a clear differentiation of the samples belonging to different quality categories, but a poor separation according to the geographical origin of the spices. On the other hand, linear discriminant analysis based on 8 selected absorbance values, concentrated near 279, 305 and 328nm, allowed a good distinction of the spices coming from different sites. Under severe validation conditions (30% and 50% of saffron samples in the evaluation set), correct predictions were 85 and 83%, respectively.

Geographical classification of Italian saffron (Crocus sativus L.) based on chemical constituents determined by high-performance liquid-chromatography and by using linear discriminant analysis

One hundred and forty-four Italian saffron samples produced in the years from 2009 to 2015 in five distinct areas located in four different regions, Abruzzo (L'Aquila), Tuscany (Florence), Umbria (Cascia and Città della Pieve) and Sardinia, have been analysed by high-performance liquid chromatography with diode array detection. Intensities of the chromatographic peaks attributed to crocins, safranal, picrocrocin and its derivatives and flavonoids were considered as variables in linear discriminant analysis to attempt geographical classification. The results revealed that spices produced at different sites of the Italian territory can be discriminated with good accuracy. The differentiation of saffron cultivated in Sardinia from those produced in Central Italy was mainly attributed to different contents of the most abundant crocins. Good differentiation of spices produced in close sites of Central Italy was also observed, 88% of validation samples being correctly classified; some minor crocins are responsible for such discrimination.

HPLC with diode-array detection for the simultaneous determination of di(2-ethylhexyl)phthalate and mono(2-ethylhexyl)phthalate in seminal plasma

A high-performance liquid chromatographic method for the simultaneous determination of di(2-ethylhexyl)phthalate (DEHP) and its major metabolite mono(2-ethylhexyl)phthalate (MEHP) in seminal plasma was developed and validated. The method involves liquid-liquid extraction followed by isocratic reversed-phase chromatography with diode-array detection. The recovery, selectivity, linearity, precision and accuracy of the method were evaluated from the analysis of spiked seminal plasma samples. The effect of mobile-phase composition and pH on the retention of the target analytes was investigated. The limits of detection were 0.010 and 0.015 microg/mL, for DEHP and MEHP, respectively. This method was used to analyze real samples in support of clinical studies on these potential endocrine disruptors.

Investigation of retention behaviour of non-steroidal anti-inflammatory drugs in high-performance liquid chromatography by using quantitative structure–retention relationships

In this paper, a quantitative structure-retention relationship (QSRR) method is employed to model the retention behaviour in reversed-phase high-performance liquid chromatography of arylpropionic acid derivatives, largely used non-steroidal anti-inflammatory drugs (NSAIDs). Computed molecular descriptors and the organic modifier content in the mobile phase are associated into a comprehensive model to describe the effect of both solute structure and eluent composition on the isocratic retention of these drugs in water-acetonitrile mobile phases. Multilinear regression (MLR) combined with genetic algorithm (GA) variable selection is used to extract from a large set of computed 3D descriptors an optimal subset. Based on GA-MLR analysis, a five-dimensional QSRR model is identified. All the four selected molecular descriptors belong to the category of GEometry, Topology, and Atom-Weights AssemblY (GETAWAY) descriptors. The related multilinear model exhibits a quite good fitting and predictive performance. This model is further improved using an artificial neural network (ANN) learned by error back-propagation. Finally, the ANN-based model displays a remarkably better performance as compared with the MLR counterpart and, based on external validation, is able to predict with good accuracy the behaviour of unknown arylpropionic NSAIDs in the range of mobile phase composition of analytical interest (between 35 and 75% acetonitrile (v/v)).

Modelling of retention of pesticides in reversed-phase high-performance liquid chromatography: Quantitative structure-retention relationships based on solute quantum-chemical descriptors and experimental (solvatochromic and spin-probe) mobile phase descriptors

A quantitative structure-retention relationship (QSRR) analysis based on multilinear regression (MLR) and artificial neural networks (ANNs) is carried out to model the combined effect of solute structure and eluent composition on the retention behaviour of pesticides in isocratic reversed-phase high-performance liquid chromatography (RP-HPLC). The octanol-water partition coefficient and four quantum chemical descriptors (the total dipole moment, the mean polarizability, the anisotropy of the polarizability and a descriptor of hydrogen-bonding based on the atomic charges on acidic and basic chemical functionalities) are considered as solute descriptors. In order to identify suitable mobile phase descriptors, encoding composition-dependent properties of both methanol- and acetonitrile-containing mobile phases, the Kamlet-Taft solvatochromic parameters (polarity-dipolarity, hydrogen-bond acidity and hydrogen-bond basicity, pi*, alpha and beta, respectively) and the 14N hyperfine-splitting constant (aN) of a spin-probe dissolved in the eluent are examined. A satisfactory description of mobile phase properties influencing the solute retention is provided by aN and beta or alternatively pi* and beta. The two seven-parameter models resulting from combination of aN and beta, or pi* and beta, with the solute descriptors were tested on a set of 26 pesticides representative of 10 different chemical classes in a wide range of mobile phase composition (30-60% (v/v) water-methanol and 30-70% (v/v) water-acetonitrile). Within the explored experimental range, the acidity of the eluent, as quantified by alpha, is almost constant, and this parameter is in fact irrelevant. The results reveal that aN and pi*, that can be considered as interchangeable mobile phase descriptors, are the most influent variables in the respective models. The predictive ability of the proposed models, as tested on an external data set, is quite good (Q2 close to 0.94) when a MLR approach is used, but the modelling capability can be further improved using an artificial neural network.

Quantitative structure-retention relationships of pesticides in reversed-phase high-performance liquid chromatography

In this paper, a quantitative structure-retention relationships (QSRR) method is employed to predict the retention behaviour of pesticides in reversed-phase high-performance liquid chromatography (HPLC). A six-parameter nonlinear model is developed by means of a feed-forward artificial neural network (ANN) with back-propagation learning rule. Accurate description of the retention factors of 26 compounds including commonly used insecticides, herbicides and fungicides and some metabolites is successfully achieved. In addition to the acetonitrile content, included to describe composition of the water-acetonitrile mobile phase, the octanol-water partition coefficient (from literature) and four quantum chemical descriptors are considered to account for the effect of solute structure on the retention. These are: the total dipole moment, the mean polarizability, the anisotropy of polarizability and a descriptor of hydrogen bonding ability based on the atomic charges on hydrogen bond donor and acceptor chemical functionalities. The proposed nonlinear QSRR model exhibits a high degree of correlation between observed and computed retention factors and a good predictive performance in wide range of mobile phase composition (40-65%, v/v acetonitrile) that supports its application for the prediction of the chromatographic behaviour of unknown pesticides. A multilinear regression model based on the same six descriptors shows a significantly worse predictive capability.

Gel-type polyacrylic resins cross-linked with trimethylolpropanetrimethacrylate: the issue of their nanostructure and molecular accessibility unveiled with a combination of inverse steric exclusion chromatography (ISEC), and ESR and CP-MAS 13C NMR spectroscopy

Six gel-type functional resins, that is, three poly-DMAA-co-TMPTP (DMAA = N,N-dimethylacrylamide, TMPTP = trimethylolpropyltrimethacrylate) samples with different degrees of cross-linking (0.6, 1.2, 1.7 % mol) and three poly-DMAA-co-MA-co-TMPTP (MA = methacrylic acid, ca. 5.5 % mol) samples with 1.7, 3.5, and 7 % mol cross-linking were investigated with ISEC (inverse steric exclusion chromatography), and ESR and CP-MAS (cross polarization magic angle spinning) 13C NMR spectroscopy after swelling in water and other solvents. This unprecedented combination of conceptually independent physicochemical techniques provides a thorough overall consistent picture of the morphology of the resins on the nanometer scale and of the molecular accessibility of the swollen polymer framework to the paramagnetic probe TEMPONE (2,2,6,6-tetramethyl-4-oxo-1-oxypiperidine) and to selected solvents.

Application of artificial neural networks for prediction of retention factors of triazine herbicides in reversed-phase liquid chromatography

In this paper a quantitative structure-retention relationship (QSRR) method is used to model reversed-phase high-performance liquid chromatography (HPLC) behaviour of a series of triazine herbicides and their metabolites. Accurate description of the retention factors in terms of four descriptors related to the analytes and to the mobile phase is achieved by means of an artificial neural network (ANN). For comparison, a QSRR model is derived by multilinear regression (MLR). Validation of the two models shows a better ability in prediction of the ANN as compared with the MLR method. A solid-phase extraction (SPE) procedure allowing the simultaneous determination of the five triazinic compounds in groundwater analysis is also presented. The observed recoveries from water samples range between 85 and 100% for ng/ml concentration levels of all analytes.

On the growth and shape of sodium taurodeoxycholate micellar aggregates: A spin-label and quasielastic light scattering investigation

Electron spin resonance (ESR) and quasielastic laser scattering (QELS) measurements have been carried out on sodium taurodeoxycholate (NaTDC) micellar aqueous solutions. Computer simulation of the ESR line shape has been used to quantitatively analyze the rotational dynamics of the cholestan-spin label (CSL) dissolved by the NaTDC micellar aggregates as a function of temperature and NaCl concentration. The local reorientation of CSL has been accounted for motionally-averaged g- and A-tensors assuming fast oscillation around the spin-probe long molecular axis. The overall Brownian tumbling of CSL-micelle complexes has been modeled by an axially symmetric rotational tensor. Good agreement with experimental spectra is obtained. Best-fit rotational parameters and QELS data suggest that, in the circumstance of large aggregation, NaTDC micelles have cylindrical shape and micellar growth occurs along the cylinder axis.

Polybenzimidazole as a promising support for metal catalysis: morphology and molecular accessibility in the dry and swollen state

Polybenzimidazole (PBI) in beaded form (250-500 microm) has been characterized in the dry state by scanning electron microscopy (SEM), BET, and nitrogen porosimetry. In the swollen state, it has been characterized by inverse steric exclusion chromatography (ISEC) in tetrahydrofuran, toluene, and water, by ESR of TEMPONE (2,2,6,6-tetramethyl-4-oxo-1-oxypiperidine), and pulse field gradient spin echo (PGSE) NMR spectroscopy, toluene, in tetrahydrofuran, ethanol and water. The dry-state results are in good agreement with the ISEC results obtained in tetrahydrofuran, toluene, and water with regard to the 40-80 nm macroporosity. The swelling-dependent surface area and pore volume detected by ISEC in toluene and water reveal the amphiphilic nature of PBI.

Conformational changes at the active site of pantetheine hydrolase during denaturation by guanidine hydrochloride

Conformational changes at the active site of pantetheine hydrolase (EC3.5.1.-) during guanidine hydrochloride (GndHCl) denaturation were investigated by UV and circular dichroism spectroscopy and by electron spin resonance spectroscopy, following the spectral behaviour of the nitroxide radicals (N-(1-oxyl-2,2,5,5,-tetramethyl-3-pyrrolidinyl) iodacetamide) covalently linked to the two active site cysteine residues. At low denaturant concentrations (0.2 M) no conformational changes may be observed, whereas the catalytic activity, is strongly affected. The results indicate that the active site of pantetheine hydrolase is labile and unfolds under conditions in which no global tertiary structure modifications can be observed.

On the interaction of polypeptides with bile salts or bilirubin-IX alpha

Aqueous solutions formed by polypeptides, simple models of proteins, and bile salts (sodium cholate and deoxycholate, NaC and NaDC, respectively) or bilirubin-IX alpha (BR) have been studied by CD measurements. They could mimic more complicated biliary systems, thus supplying a possible interpretation of the behavior of some amino acid residues in the biliary proteins. The aggregation of NaDC and NaC in water can be monitored by CD measurements. Bile salts, in submicellar and micellar form, stabilize poly(L-Lys) (PLL) in alpha-helical conformation. The alpha-helix content increases with increasing bile salt concentration and ionic strength. NaDC seems to be a slightly better stabilizing agent of the alpha-helix conformation than NaC. Models characterized by hydrogen bonds between bile salts and PLL are proposed, also resorting to previous data available on the systems formed by NaDC and poly(L-Leu-L-Leu-L-Lys) (PLLL) or poly(L-Leu-L-Leu-L-Asp) (PLLA). Binding of BR to PLL, poly(D-Lys), poly(L-Glu), PLLL, and PLLA in water has been investigated by CD spectra in order to clarify the nature of the association complexes and the mechanism of the BR enantioselective complexation. Potential energy calculations provide binding models capable of explaining the enantioselective ability of the PLL and PLLL alpha-helices toward the left- and right-handed enantiomer of BR, respectively. BR is bound to -NH2 groups of PLL and PLLL lying on a right- and left-handed spiral, respectively. These results, together with those formerly obtained for some bile salts-BR systems, indicate that the selectivity originates from a binding that involves large regions of the BR molecule and gives rise, very probably, to moderate conformational changes from the "ridge tile" structure observed in the crystals. In some cases van der Waals forces can play a crucial role in the chiral recognition of bilirubin. Moreover, possible interaction models of BR with human serum albumin are proposed on the basis of a recent x-ray crystal structure of the protein.