Liquid Chromatography Retention Times Research Articles

Quantitative structure-(chromatographic) retention relationship models for dissociating compounds

The aim of this work was to develop mathematical models relating the hydrophobicity and dissociation constant of an analyte with its structure, which would be useful in predicting analyte retention times in reversed-phase liquid chromatography. For that purpose a large and diverse group of 115 drugs was used to build three QSRR models combining retention-related parameters (logkw—chromatographic measure of hydrophobicity, S—slope factor from Snyder-Soczewinski equation, and pKa) with structural descriptors calculated by means of molecular modeling for both dissociated and nondissociated forms of analytes. Lasso, Stepwise and PLS regressions were used to build statistical models. Moreover a simple QSRR equations based on lipophilicity and dissociation constant parameters calculated in the ACD/Labs software were proposed and compared with quantum chemistry-based QSRR equations. The obtained relationships were further used to predict chromatographic retention times. The predictive performances of the obtained models were assessed using 10-fold cross-validation and external validation. The QSRR equations developed were simple and were characterized by satisfactory predictive performance. Application of quantum chemistry-based and ACD-based descriptors leads to similar accuracy of retention times’ prediction.

Prediction of retention time in reversed-phase liquid chromatography as a tool for steroid identification

The untargeted profiling of steroids constitutes a growing research field because of their importance as biomarkers of endocrine disruption. New technologies in analytical chemistry, such as ultra high-pressure liquid chromatography coupled with mass spectrometry (MS), offer the possibility of a fast and sensitive analysis. Nevertheless, difficulties regarding steroid identification are encountered when considering isotopomeric steroids. Thus, the use of retention times is of great help for the unambiguous identification of steroids. In this context, starting from the linear solvent strength (LSS) theory, quantitative structure retention relationship (QSRR) models, based on a dataset composed of 91 endogenous steroids and VolSurf + descriptors combined with a new dedicated molecular fingerprint, were developed to predict retention times of steroid structures in any gradient mode conditions. Satisfactory performance was obtained during nested cross-validation with a predictive ability (Q2) of 0.92. The generalisation ability of the model was further confirmed by an average error of 4.4% in external prediction. This allowed the list of candidates associated with identical monoisotopic masses to be strongly reduced, facilitating definitive steroid identification.

RePLiCal: A QconCAT Protein for Retention Time Standardization in Proteomics Studies.

This study introduces a new reversed-phase liquid chromatography retention time (RT) standard, RePLiCal (Reversed-phase liquid chromatography calibrant), produced using QconCAT technology. The synthetic protein contains 27 lysine-terminating calibrant peptides, meaning that the same complement of standards can be generated using either Lys-C or trypsin-based digestion protocols. RePLiCal was designed such that each constituent peptide is unique with respect to all eukaryotic proteomes, thereby enabling integration into a wide range of proteomic analyses. RePLiCal has been benchmarked against three commercially available peptide RT standard kits and outperforms all in terms of LC gradient coverage. RePLiCal also provides a higher number of calibrant points for chromatographic retention time standardization and normalization. The standard provides stable RTs over long analysis times and can be readily transferred between different LC gradients and nUHPLC instruments. Moreover, RePLiCal can be used to predict RTs for other peptides in a timely manner. Furthermore, it is shown that RePLiCal can be used effectively to evaluate trapping column performance for nUHPLC instruments using trap-elute configurations, to optimize gradients to maximize peptide and protein identification rates, and to recalibrate the m/z scale of mass spectrometry data post-acquisition.

Efficiency of a solvatic sorption model for the prediction of retention times in linear gradient reversed-phase liquid chromatography working with different stationary phases

Efficiency of a solvatic sorption model for the prediction of retention times in linear gradient reversed-phase liquid chromatography working with different stationary phases

Microwave-Assisted Extraction and Purification of Arctiin and Arctigenin from Fructus Arctii by High-Speed Countercurrent Chromatography.

An efficient method for the rapid extraction, separation and purification of bioactive lignans, arctiin and arctigenin, from Fructus arctii by microwave-assisted extraction coupled with high-speed countercurrent chromatography was developed. The optimal extraction conditions of arctiin and arctigenin were evaluated by orthogonal array. Arctigenin could be converted from arctiin by hydrochloric acid hydrolysis. The separations were performed at a preparative scale with two-phase solvents composed of ethyl acetate-ethanol-water (5 : 1 : 5, v/v/v) for arctiin, and n-hexane-ethyl acetate-ethanol-water (4 : 4 : 3 : 4, v/v/v/v) for arctigenin. From 500 mg of crude extract sample, 122.3 mg of arctiin and 45.7 mg of arctigenin were obtained with the purity of 98.46 and 96.57%, and the recovery of 94.3 and 81.6%, respectively. Their structures were determined by comparison with the high-performance liquid chromatography retention time of standard substance as well as UV, FT-IR, electrospray ion source (ESI)-MS, (1)H-NMR and (13)C-NMR spectrum. According to the antioxidant activity assay, arctigenin had stronger 1,1-diphenyl-2-picrylhydrazyl free radicals scavenging activity.

Performance comparison of partial least squares-related variable selection methods for quantitative structure retention relationships modelling of retention times in reversed-phase liquid chromatography

The relative performance of six multivariate data analysis methods derived from or combined with partial least squares (PLS) has been compared in the context of quantitative structure–retention relationships (QSRR). These methods include, GA (genetic algorithm)-PLS, Monte Carlo uninformative variable elimination (MC-UVE), competitive adaptive reweighted sampling (CARS), iteratively retaining informative variables (IRIV), variable iterative space shrinkage approach (VISSA) and PLS with automated backward selection of predictors (autoPLS). A set of 825 molecular descriptors was computed for 86 suspected sports doping compounds and used for predicting their gradient retention times in reversed-phase liquid chromatography (RPLC). The correlation between molecular descriptors selected by each technique and the retention time was established using the PLS method. All models derived from a selected subset of descriptors outperformed the reference PLS model derived from all descriptors, with very small demands of computational time and effort. A performance comparison indicated great diversity of these methods in selecting the most relevant molecular descriptors, ranging from 28 for CARS to 263 for MC-UVE. While VISSA provided the lowest degree of over-fitting for the training set, CARS demonstrated the best compromise between the prediction accuracy and the number of selected descriptors, with the prediction error of as low as 46s for the external test set. Only ten descriptors were found to be common for all models, with the characteristics of these descriptors being representative of the retention mechanism in RPLC.

Gradient liquid chromatographic retention time prediction for suspect screening applications: A critical assessment of a generalised artificial neural network-based approach across 10 multi-residue reversed-phase analytical methods

For the first time, the performance of a generalised artificial neural network (ANN) approach for the prediction of 2492 chromatographic retention times (tR) is presented for a total of 1117 chemically diverse compounds present in a range of complex matrices and across 10 gradient reversed-phase liquid chromatography-(high resolution) mass spectrometry methods. Probabilistic, generalised regression, radial basis function as well as 2- and 3-layer multilayer perceptron-type neural networks were investigated to determine the most robust and accurate model for this purpose. Multi-layer perceptrons most frequently yielded the best correlations in 8 out of 10 methods. Averaged correlations of predicted versus measured tR across all methods were R2=0.918, 0.924 and 0.898 for the training, verification and test sets respectively. Predictions of blind test compounds (n=8–84 cases) resulted in an average absolute accuracy of 1.02±0.54min for all methods. Within this variation, absolute accuracy was observed to marginally improve for shorter runtimes, but was found to be relatively consistent with respect to analyte retention ranges (~5%). Finally, optimised and replicated network dependency on molecular descriptor data is presented and critically discussed across all methods. Overall, ANNs were considered especially suitable for suspects screening applications and could potentially be utilised in bracketed-type analyses in combination with high resolution mass spectrometry.

Retention projection enables accurate calculation of liquid chromatographic retention times across labs and methods

Identification of small molecules by liquid chromatography–mass spectrometry (LC–MS) can be greatly improved if the chromatographic retention information is used along with mass spectral information to narrow down the lists of candidates. Linear retention indexing remains the standard for sharing retention data across labs, but it is unreliable because it cannot properly account for differences in the experimental conditions used by various labs, even when the differences are relatively small and unintentional. On the other hand, an approach called “retention projection” properly accounts for many intentional differences in experimental conditions, and when combined with a “back-calculation” methodology described recently, it also accounts for unintentional differences. In this study, the accuracy of this methodology is compared with linear retention indexing across eight different labs. When each lab ran a test mixture under a range of multi-segment gradients and flow rates they selected independently, retention projections averaged 22-fold more accurate for uncharged compounds because they properly accounted for these intentional differences, which were more pronounced in steep gradients. When each lab ran the test mixture under nominally the same conditions, which is the ideal situation to reproduce linear retention indices, retention projections still averaged 2-fold more accurate because they properly accounted for many unintentional differences between the LC systems. To the best of our knowledge, this is the most successful study to date aiming to calculate (or even just to reproduce) LC gradient retention across labs, and it is the only study in which retention was reliably calculated under various multi-segment gradients and flow rates chosen independently by labs.

Abstract 4619: DNA adductome analyses at multiple sites of human gastric mucosa, resected for gastric cancer

Abstract DNA adducts are recognized as an initiative step of mutagenesis, but the measurement of them is still a technical challenge. So-called adductome approach, based on LC-MS/MS, is a popular procedure to identify multiple DNA adducts in various tissues at a single experiments. Recently we reported 7 lipid peroxidation-induced DNA adducts in human gastric mucosa resected for gastric cancer in two countries for the first time, and showed the profile of these DNA adducts could indicate geo-pathological background of gastric mucosa (Matsuda 2013). Though DNA adductome approach posesses the high throghput potential in terms of finding numerous specis of DNA adducts having different molecular weights, there are still challenges to overcome. First of all, the numbers of the standards of DNA adducts molecules available are less than the species with identified molecular weight. This implies there are much more DNA modifications in human tissues than previously characterized. The other challaenge is that the absolute quantifications of these adducts requires isotopic standard chemicals. In this study, we strengthened DNA adductome method by including as many as known adducts in the assay system. Mass/Charge value and liquid chromatography retention time of known 254 DNA addcuts were collected and incoporated into LC-MS/MS machine (4000-QTRAP; Thermo). By this procedure we could measure the 254 DNA adducts at one time in MRM mode. Using this system, we measured 254 DNA adducts in the following human gastric mucosa. Written informed consents were obtained from the patients who took gastrectomy for gastric cancer. Under the hypothesis of field cancerization of gastric mucosa, in order to analyze the spatial influence of the exposure of the potential carcinogens toward cancer site, muocsal tissue at multiple sites with different distance to cancer, (10cm and more distant from the tumor site in the stomach to the site adjacent to the tumor) were taken. Three to 10 sites/case were investigated for DNA adducts measurements. Totally 11 cases and 77 sites are analyzed. Considerable numbers of known DNA adducts were present in human gastric mucosa in different quantities. Among them, tobacco-related and lipid-peroxidation-induced DNA adducts were noted. We also did the same measurements in proximal, middle, and distal gastric mucosa from autospy cases without gastric cancer and compared them to those of the cancer cases. Among them, etheno-dA was able to be quantitatively measured using isotopic standard. The mean level of etheno dA in the gastric mucosa of autopsy cases without gastric cancer was 8.02/107 nucleotides, while that of gastric cancer patients mucosae was 4.80/107 nucleotides. These comprehensive identifications in adducts in human gastric mucosa will provide the basic information for dosimetry and risk assessment of environmental chemicals toward gastric cancer. Citation Format: Nobuya Kurabe, Ippei Ohnishi, Masako Suzuki, Yusuke Inoue, Tomoaki Kahyo, Moriya Iwaizumi, Yoshitaka Matsushima, Yukari Totsuka, Hitoshi Nakagama, Masako Kasami, Hideto Ochiai, Keigo Matsumoto, Shioto Suzuki, Fumihiko Tanioka, Haruhiko Sugimura. DNA adductome analyses at multiple sites of human gastric mucosa, resected for gastric cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4619. doi:10.1158/1538-7445.AM2015-4619

Qualitative and quantitative characterization of monomers of uncured bulk-fill and conventional resin-composites using liquid chromatography/mass spectrometry

ObjectivesThe aim of this study was to assess the resin matrix monomer composition of selected bulk-fill and conventional resin-composite materials using reverse phase liquid chromatography coupled with electron spray ionization mass spectrometry. Material and methodsSix bulk-fill (SureFil SDR, Venus Bulk Fill, X-tra base, Filtek Bulk Fill flowable, Sonic Fill, and Tetric EvoCeram Bulk Fill) and eight conventional resin-composites (Grandioso Flow, Venus Diamond Flow, X-Flow, Filtek Supreme XTE, Grandioso, Venus Diamond, TPH Spectrum, and Filtek Z250) were tested. For assessment of resin composition and relative monomer amounts, uncured resin-composites were analysed with reverse phase liquid chromatography/electron spray ionization mass spectrometry. logP values (a measure of hydrophobicity) of detected compounds were calculated and their correlation to reverse phase liquid chromatography retention time was explored. Data were analysed with one-way ANOVA, Tukey post hoc test, Pearson correlation and regression analyses at α=0.05. ResultsThe main monomers detected were BisGMA, UDMA, TEGDMA, and BisEMA. Monomers were detected at variable combinations in different materials with significantly different relative amounts. Other monomers were detected including HDDMA, DEGDMA, TCD-DI-HEA, and SDR-UDMA in Grandioso flow, X-flow, Venus Diamond, and SureFil SDR respectively. A positive correlation between logP and reverse phase liquid chromatography retention time was detected (r2=0.62, p=0.004). ConclusionsResin composition of bulk-fill resin-composites is comparable to that of conventional materials with the exception of SureFil SDR. The relative hydrophobicity of dental monomers can be determined by their reverse phase liquid chromatography retention time.

Hydrophobic Blocks Facilitate Lipid Compatibility and Translocon Recognition of Transmembrane Protein Sequences

Biophysical hydrophobicity scales suggest that partitioning of a protein segment from an aqueous phase into a membrane is governed by its perceived segmental hydrophobicity but do not establish specifically (i) how the segment is identified in vivo for translocon-mediated insertion or (ii) whether the destination lipid bilayer is biochemically receptive to the inserted sequence. To examine the congruence between these dual requirements, we designed and synthesized a library of Lys-tagged peptides of a core length sufficient to span a bilayer but with varying patterns of sequence, each composed of nine Leu residues, nine Ser residues, and one (central) Trp residue. We found that peptides containing contiguous Leu residues (Leu-block peptides, e.g., LLLLLLLLLWSSSSSSSSS), in comparison to those containing discontinuous stretches of Leu residues (non-Leu-block peptides, e.g., SLSLLSLSSWSLLSLSLLS), displayed greater helicity (circular dichroism spectroscopy), traveled slower during sodium dodecyl sulfate–polyacrylamide gel electrophoresis, had longer reverse phase high-performance liquid chromatography retention times on a C-18 column, and were helical when reconstituted into 1-palmitoyl-2-oleoylglycero-3-phosphocholine liposomes, each observation indicating superior lipid compatibility when a Leu-block is present. These parameters were largely paralleled in a biological membrane insertion assay using microsomal membranes from dog pancreas endoplasmic reticulum, where we found only the Leu-block sequences successfully inserted; intriguingly, an amphipathic peptide (SLLSSLLSSWLLSSLLSSL; Leu face, Ser face) with biophysical properties similar to those of Leu-block peptides failed to insert. Our overall results identify local sequence lipid compatibility rather than average hydrophobicity as a principal determinant of transmembrane segment potential, while demonstrating that further subtleties of hydrophobic and helical patterning, such as circumferential hydrophobicity in Leu-block segments, promote translocon-mediated insertion.

Artificial neural network prediction of multilinear gradient retention in reversed-phase HPLC: comprehensive QSRR-based models combining categorical or structural solute descriptors and gradient profile parameters.

A multilayer artificial neural network (ANN) is used to model the reversed-phase liquid chromatography retention times of 16 selected compounds, including purines, pyrimidines and nucleosides. The analysed data, taken from literature, were collected in acetonitrile-water eluents under the application of 16 different multilinear gradients. The parameters describing the gradient profile together with solute descriptors are considered as the independent variables of an ANN-based model providing the retention time as response. Categorical variables or, alternatively, a selected set of molecular descriptors of computational origin are adopted to represent the solutes. Network training, validation and testing are performed preliminarily using data of 12, 2 and 4 gradients, respectively and successively, to investigate model performance under more severe calibration conditions, with data of 9, 2 and 7 gradients. The proposed approach allows a quite accurate prediction of retention times of the target analytes in external multilinear gradients. Categorical variables can successfully represent the target solutes when the model is called to transfer retention data from calibration to external gradients. In particular, using a five-dimensional bit string to represent the analytes, mean errors on retention times are 2 and 3% under the most and less favourable calibration conditions, respectively. A comparable performance is observed if the categorical variables are replaced by five molecular descriptors, selected by a genetic algorithm within a large set of structural variables of computational origin.

Compound “J” in Late Cretaceous/Tertiary terrigenous oils revisited: Structure elucidation of a rearranged oleanane coeluting on GC with 18β(H)-oleanane

A C30 pentacyclic triterpane eluting slightly after 18α(H)-oleanane in the m/z 191 mass chromatograms of Late Cretaceous/Tertiary terrigenous oils (peak “J” in the early literature) has been isolated from a Niger Delta oil and identified using NMR spectroscopy as 3β-methyl-24-nor-18α(H)-oleanane. The previous assignment as 18β(H)-oleanane is therefore partly erroneous. 3β-Methyl-24-nor-18α(H)-oleanane affords a larger m/z 412→356 response than the oleananes and the relative contribution of 3β-methyl-24-nor-18α(H)-oleanane to the 412→191 “oleanane peak” can be roughly estimated from comparison of the 412→356/412→191 ratio from the oleanane peak with that of the pure compounds. 3β-Methyl-24-nor-18α(H)-oleanane can be as abundant as 18α(H)-oleanane in oils having a high concentration of early eluting rearranged oleananes. 3β-Methyl-24-nor-19α(H)-taraxastane was also tentatively assigned in the oils on the basis of its mass spectrum as well as its gas chromatography and high performance liquid chromatography retention times. 3β-Methyl-24-nor-gammacerane was tentatively assigned in a similar way in an oil containing gammacerane. All 3β-methyl-24-nor-triterpanes could be formed via dehydration, rearrangement and hydrogenation of triterpenoids having an OH group at C-3.

Physicochemical and biochemical properties for the dialkyl phthalates

Abraham descriptors for 40 phthalate esters have been calculated from a variety of experimental data, including water–solvent partition coefficients, high performance liquid chromatographic and gas chromatographic retention times. These descriptors can then be used to calculate a large number of physicochemical and biochemical properties of the esters; values are given for dinonyl phthalate as an example. Once the Abraham descriptors have been obtained for a given phthalate ester, no more than simple arithmetic is needed to calculate values of a huge range of properties. The ‘three solubility method’ yields data that are consistent for a particular physicochemical property, but not necessarily correct data. Previous literature values for air–water partition coefficients for the higher phthalates are likely to be incorrect by several orders of magnitude.

Reproducibility of retention time and peak area in comprehensive two-dimensional liquid chromatography.

Comprehensive two-dimensional liquid chromatography is used to separate anionic, nonionic, and amphoteric surfactants by substance class, alkyl chain distribution, and degree of ethoxylation. A nearly orthogonal system with a hydrophilic interaction chromatography (HILIC) phase in the first and a reversed-phase material in the second dimension is applied to generate a separation with maximum peak capacity. The potential of the developed method is demonstrated by the reproducibility of retention time and peak area, which shows standard deviations less than 5% and the analysis of real samples. An external calibration and the standard addition method were applied to determine unknown concentrations for the alkyl chain homologues of a betaine and for one ethoxylate (EO) homologue of a fatty alcohol ethoxylate in a sample mixture.

Metabolic pathway for degradation of anthracene by halophilic Martelella sp. AD-3

Anthracene (40 mg l−1) was completely depleted by Martelella sp. strain AD-3 under 3% salinity and a pH of 9.0 after 6 days of incubation. The metabolites were extracted and identified by high-performance liquid chromatography (HPLC) retention times, mass spectrometry, 1H and 13C nuclear magnetic resonance spectrometry, and comparison to authentic compounds or literature data. On the basis of the identified metabolites, enzyme activities and the utilization of probable intermediates, anthracene degradation by strain AD-3 is proposed via two distinct routes. In route I, metabolism of anthracene is initiated by the dioxygenation at C-1,2, then proceeds through 6,7-benzocoumarin, 3-hydroxy-2-naphthoic acid, salicylic acid and gentisic acid. In route II, anthracene is metabolized to 9,10-anthraquinone. The results suggest that strain AD-3 possesses efficient anthracene biodegradability in high salinity. To our knowledge, this work presents the first report of anthracene degradation by a halophilic PAH-degrading strain via two routes. The strain AD-3 may be a useful candidate for PAH-contaminated saline-alkali soil bioremediation.

Novel Method To Identify the Optimal Antimicrobial Peptide in a Combination Matrix, Using Anoplin as an Example

Microbial resistance is an increasing health concern and a true danger to human well-being. A worldwide search for new compounds is ongoing, and antimicrobial peptides are promising lead candidates for tomorrow's antibiotics. The decapeptide anoplin (GLLKRIKTLL-NH2) is an especially interesting candidate because of its small size as well as its antimicrobial and nonhemolytic properties. Optimization of the properties of an antimicrobial peptide such as anoplin requires multidimensional searching in a complex chemical space. Typically, such optimization is performed by labor-intensive and costly trial-and-error methods. In this study, we show the benefit of fractional factorial design for identification of the optimal antimicrobial peptide in a combination matrix. We synthesized and analyzed a training set of 12 anoplin analogs, representative of 64 analogs in total. Using MIC, hemolysis, and high-performance liquid chromatography retention time data, we constructed analysis-of-variance models that describe the relationship between these properties and the structural characteristics of the analogs. We show that the mathematical models derived from the training set data can be used to predict the properties of other analogs in the chemical space. Hence, this method provides an efficient means of identification of the optimal peptide in the searched chemical space.

Identification of a novel flavonoid glycoside sulfotransferase in Arabidopsis thaliana

The discovery of sulfated flavonoids in plants suggests that sulfation may play a regulatory role in the physiological functions of flavonoids. Sulfation of flavonoids is mediated by cytosolic sulfotransferases (SULTs), which utilize 3'-phosphoadenosine 5'-phosphosulfate (PAPS) as the sulfate donor. A novel SULT from Arabidopsis thaliana, designated AtSULT202B7 (AGI code: At1g13420), was cloned and expressed in Escherichia coli. Using various compounds as potential substrates, we demonstrated, for the first time, that AtSULT202B7 displayed sulfating activity specific for flavonoids. Intriguingly, the recombinant enzyme preferred flavonoid glycosides (e.g. kaempferol-3-glucoside and quercetin-3-glucoside) rather than their aglycone counterparts. Among a series of hydroxyflavones tested, AtSULT202B7 showed the enzymatic activity only for 7-hydroxyflavone. pH-dependency study showed that the optimum pH was relatively low (pH 5.5) compared with those (pH 6.0-8.5) previously reported for other isoforms. Based on the comparison of high performance (pressure) liquid chromatography (HPLC) retention times between sulfated kaempferol and the deglycosylated product of sulfated kaempferol-3-glucoside, the sulfation site in sulfated kaempferol-3-glucoside appeared to be the hydroxyl group of the flavonoid skeleton. In addition, by using direct infusion mass spectrometry, it was found that the sulfated product had one sulfonate group within the molecule. These results indicated that AtSULT202B7 functions as a flavonoid glycoside 7-sulfotransferase.

Unifying Expression Scale for Peptide Hydrophobicity in Proteomic Reversed Phase High-Pressure Liquid Chromatography Experiments

As an initial step in our efforts to unify the expression of peptide retention times in proteomic liquid chromatography-mass spectrometry (LC-MS) experiments, we aligned the chromatographic properties of a number of peptide retention standards against a collection of peptides commonly observed in proteomic experiments. The standard peptide mixtures and tryptic digests of samples of different origins were separated under the identical chromatographic condition most commonly employed in proteomics: 100 Å C18 sorbent with 0.1% formic acid as an ion-pairing modifier. Following our original approach (Krokhin, O. V.; Spicer, V. Anal. Chem. 2009, 81, 9522-9530) the retention characteristics of these standards and collection of tryptic peptides were mapped into hydrophobicity index (HI) or acetonitrile percentage units. This scale allows for direct visualization of the chromatographic outcome of LC-MS acquisitions, monitors the performance of the gradient LC system, and simplifies method development and interlaboratory data alignment. Wide adoption of this approach would significantly aid understanding the basic principles of gradient peptide RP-HPLC and solidify our collective efforts in acquiring confident peptide retention libraries, a key component in the development of targeted proteomic approaches.

Comprehensive profiling of flavonoids inScutellaria incanaL. using LC-Q-TOF-MS

Summary Scutellaria L. is a diverse genus of the Lamiaceae (Labiatae) family of over 300 herbaceous plants commonly known as skullcaps. Various species of Scutellaria are used as ethnobotanical herbs for the treatment of ailments like cancer, jaundice, cirrhosis, anxiety, and nervous disorders. Scutellaria incana L., commonly known as the Hoary skullcap, is a traditional medicinal plant used by native Americans as a sedative for nervousness or anxiety. S. incana metabolites were identified by comparing their high-performance liquid chromatography (HPLC) retention times and mass spectra with those of the corresponding authentic standards. Where standards were unavailable, the structures were characterized on the basis of their tandem mass spectrometry (MS/MS) spectra following collision-induced dissociation (CID) and the accurate masses of the corresponding deprotonated molecules [M-H]− (mass accuracy ± 5 ppm). A total of 40 flavonoids, including two phenolic glycosides, were identified from leaves, stems, and roots of S. incana. Differences in the flavonoid composition between leaves, stems, and roots in S. incana were observed although the flavonoid profile of S. incana is consistent with other Scutellaria species. Further work should focus on assessing the potential of S. incana as a source of these bioactive metabolites.