Pressurized capillary electrochromatography in a screening for possible antioxidant molecules in Mallotus fingerprints: challenges, potentials and prospects.

Because of its eminent high resolution potential and minimal solvent consumption, pressurized capillary electrochromatography (pCEC) may offer an interesting alternative to HPLC for screening applications that need to resolve complex samples. In this paper, its potential was assessed in a screening of plant extracts from Mallotus species to indicate compounds with possible antioxidant activities by means of a PLS model built from their pCEC fingerprints. The main aim of this research was to find out whether pCEC can have an added value for this application. To get a complete overview of the techniques potential for this application, it was also assessed whether the technique can meet the requirements in terms of precision, sensitivity and column robustness. Encountered benefits and downsides were reported. Fingerprints with satisfactory sensitivity and precision could be obtained by concentrating the sample 5-fold and using optimized rinsing procedures, respectively. From the generated pCEC fingerprints of 39 Mallotus samples and their respective DPPH radical scavenging activity test results, a three-component PLS model was being built. The model proved good predictive abilities and easily allowed the indication of possible antioxidant compounds in the fingerprints. Despite its much higher peak capacity, the performance of pCEC to fingerprint the majority of the Mallotus extracts did not surpass that of a custom HPLC method. This was also reflected in its comparable power to indicate possible antioxidant compounds in the fingerprints after modeling. Because of its low detection sensitivity and modest column robustness, the benefit of the lower solvent consumption was partly paid-off by the current need for more system maintenance, also limiting the sample throughput. For the considered screening application, pCEC may suit as a viable but no preferred alternative technique.

Advanced QSRR modeling of peptides behavior in RPLC.

In QSRR the retention is modeled as a function of structural or molecular descriptors. Since the structural datasets can be very large a selection of informative variables is often required. But beside the question which subset of variables (descriptors) produces optimum predictions one should answer the question: can good prediction be used in the QSRR community even if the physical meaning of applied descriptors is hard to interpret? The main focus in this paper is put on different modeling methodologies applied and molecular descriptors used in the QSRR approaches. Besides the widely used multiple linear regression (MLR), these methodologies include partial least squares (PLS), uninformative variable elimination partial least squares (UVE-PLS), genetic algorithms (GA) prior to MLR or PLS. The comparison will focus on the predictive performance but also on the descriptors found to be most important for the chromatographic retention prediction of peptides. The results of this study showed that stepwise-MLR and UVE-PLS are producing better predictions than the rest of the studied methodologies. From the variables selected by various methodologies one can see that the important information for the retention mechanism of RPLC was given by 2D-, 3D-descriptors and descriptors from the empirical QSRR equations, which bring the information about hydrogen-bonding properties, molecular size, and complexity. Overall, for the considered data set the empirical QSRR models were predicting the peptides retention best.

The molecular descriptor logSumAA and its alternatives in QSRR models to predict the retention of peptides.

The use of the experimental molecular descriptor logSum(AA) and some possible alternatives were evaluated in the QSRR analysis of peptides. To quantitatively characterize the structure of analytes in a previously proposed QSRR the following three structural descriptors were applied: the logarithm of the sum of gradient retention times of the amino acids composing the individual peptide, logSum(AA); the logarithm of the peptide's van der Waals volume, logVDW(Vol); and the logarithm of its theoretically calculated n-octanol-water partition coefficient, clogP. Taking into consideration that most amino acids were hardly retained in the different RP-HPLC systems on which the peptides retention was measured, the contribution of most amino acids to the logSum(AA) descriptor is rather constant. Therefore, to enlarge the variability of the descriptor and the amino acids contributions for a given series of peptides, in a first instance, it was evaluated whether, by changing the chromatographic conditions, the retention differences between the amino acids could be increased, while maintaining their mutual selectivity. It was not evident to find such conditions. Secondly, it was also investigated whether the experimental descriptor logSum(AA) can be replaced by a theoretical, either based on a simple or on a weighted counting of the amino acids composing the peptide. The weighting factor for the retained amino acids was determined by their experimental gradient retention times measured on different systems. The predictive abilities of the new QSRR models (applying the alternative descriptors) were assessed using the leave-one-out cross-validation procedure and compared to that of the initial model. Finally, a descriptor was defined for which the retention measurement of only a limited number of amino acids is required. It resulted in QSRR models with similar predictive properties as those with logSum(AA), but with a reduced workload.

Homogeneous assay based on 52 primer sets to scan for mutations of the ABCA1 gene and its application in genetic analysis of a new patient with familial high-density lipoprotein deficiency syndrome.

Familial high-density lipoprotein (HDL)-deficiency syndromes are caused by mutations of the ABCA1 gene, coding for the ATP-binding cassette transporter 1. We have developed a homogeneous assay based on 52 primer sets to amplify all 50 ABCA1 exons and approximately 1 kb of its promoter. The assay allows for convenient amplification of the gene from genomic DNA and easy mutational analysis through automatic sequencing. It obviates the need to use mRNA preparations, which were difficult to handle and posed a risk to miss splice junction or promoter mutations. The application of the test to the molecular analysis of a new patient with familial HDL-deficiency (Tangier disease) led to a discovery of two novel ABCA1 mutations: C2665del and C4457T.