FilamentID reveals the composition and function of metabolic enzyme polymers during gametogenesis.

Gamete formation and subsequent offspring development often involve extended phases of suspended cellular development or even dormancy. How cells adapt to recover and resume growth remains poorly understood. Here, we visualized budding yeast cells undergoing meiosis by cryo-electron tomography (cryoET) and discovered elaborate filamentous assemblies decorating the nucleus, cytoplasm, and mitochondria. To determine filament composition, we developed a "filament identification" (FilamentID) workflow that combines multiscale cryoET/cryo-electron microscopy (cryoEM) analyses of partially lysed cells or organelles. FilamentID identified the mitochondrial filaments as being composed of the conserved aldehyde dehydrogenase Ald4ALDH2 and the nucleoplasmic/cytoplasmic filaments as consisting of acetyl-coenzyme A (CoA) synthetase Acs1ACSS2. Structural characterization further revealed the mechanism underlying polymerization and enabled us to genetically perturb filament formation. Acs1 polymerization facilitates the recovery of chronologically aged spores and, more generally, the cell cycle re-entry of starved cells. FilamentID is broadly applicable to characterize filaments of unknown identity in diverse cellular contexts.

Intricacies of single-cell multi-omics data integration.

A wealth of single-cell protocols makes it possible to characterize different molecular layers at unprecedented resolution. Integrating the resulting multimodal single-cell data to find cell-to-cell correspondences remains a challenge. We argue that data integration needs to happen at a meaningful biological level of abstraction and that it is necessary to consider the inherent discrepancies between modalities to strike a balance between biological discovery and noise removal. A survey of current methods reveals that a distinction between technical and biological origins of presumed unwanted variation between datasets is not yet commonly considered. The increasing availability of paired multimodal data will aid the development of improved methods by providing a ground truth on cell-to-cell matches.

A semi-automated workflow for DIA-based global discovery to pathway-driven PRM analysis.

Targeted proteomics, which includes parallel reaction monitoring (PRM), is typically utilized for more precise detection and quantitation of key proteins and/or pathways derived from complex discovery proteomics datasets. Initial discovery-based analysis using data independent acquisition (DIA) can obtain deep proteome coverage with low data missingness while targeted PRM assays can provide additional benefits in further eliminating missing data and optimizing measurement precision. However, PRM method development from bioinformatic predictions can be tedious and time-consuming because of the DIA output complexity. We address this limitation with a Python script that rapidly generates a PRM method for the TIMS-TOF platform using DIA data and a user-defined target list. To evaluate the script, DIA data obtained from HeLa cell lysate (200 ng, 45-min gradient method) as well as canonical pathway information from Ingenuity Pathway Analysis was utilized to generate a pathway-driven PRM method. Subsequent PRM analysis of targets within the example pathway, regulation of apoptosis, resulted in improved chromatographic data and enhanced quantitation precision (100% peptides below 10% CV with a median CV of 2.9%, n = 3 technical replicates). The script is freely available at https://github.com/StevensOmicsLab/PRM-script and provides a framework that can be adapted to multiple DDA/DIA data outputs and instrument-specific PRM method types.

Recognition of Molecular Structure of Phosphonium Salts from the Visual Appearance of Material with Deep Learning Can Reveal Subtle Homologs.

Determining molecular structures is foundational in chemistry and biology. The notion of discerning molecular structures simply from the visual appearance of a material remained almost unthinkable until the advent of machine learning. This paper introduces a pioneering approach bridging the visual appearance of materials (both at the micro- and nanostructural levels) with traditional chemical structure analysis methods. Quaternary phosphonium salts are opted as the model compounds, given their significant roles in diverse chemical and medicinal fields and their ability to form homologs with only minute intermolecular variances. This research results in the successful creation of a neural network model capable of recognizing molecular structures from visual electron microscopy images of the material. The performance of the model is evaluated and related to the chemical nature of the studied chemicals. Additionally, unsupervised domain transfer is tested as a method to use the resulting model on optical microscopy images, as well as test models trained on optical images directly. The robustness of the method is further tested using a complex system of phosphonium salt mixtures. To the best of the authors' knowledge, this study offers the first evidence of the feasibility of discerning nearly indistinguishable molecular structures.

A novel, high-performance, low-volume, rapid luciferase immunoprecipitation system (LIPS) assay to detect autoantibodies to zinc transporter 8.

BACKGROUND: Zinc transporter 8 autoantibodies (ZnT8A) are thought to appear close to type 1 diabetes (T1D) onset and can identify high-risk multiple (≥2) autoantibody positive individuals. Radiobinding assays (RBA) are widely used for ZnT8A measurement but have limited sustainability. We sought to develop a novel, high-performance, non-radioactive luciferase immunoprecipitation system (LIPS) assay to replace RBA. METHODS: A custom dual C-terminal ZnT8 (aa268-369; R325/W325) heterodimeric antigen, tagged with a NanoluciferaseTM (Nluc-ZnT8) reporter, and LIPS assay was developed. Assay performance was evaluated by testing sera from new onset T1D (n = 573), healthy schoolchildren (n = 521), and selected first-degree relatives (FDRs) from the Bart's Oxford family study (n = 617; 164 progressed to diabetes). RESULTS: In new-onset T1D, ZnT8A levels by LIPS strongly correlated with RBA (Spearman's r = 0.89; P < 0.0001), and positivity was highly concordant (94.3%). At a high specificity (95%), LIPS and RBA had comparable assay performance [LIPS pROC-AUC(95) 0.032 (95% CI: 0.029-0.036); RBA pROC-AUC(95) 0.031 (95% CI: 0.028-0.034); P = 0.376]. Overall, FDRs found positive by LIPS or RBA had a comparable 20-year diabetes risk (52.6% and 59.7%, respectively), but LIPS positivity further stratified T1D risk in FDRs positive for at least one other islet autoantibody detected by RBA (P = 0.0346). CONCLUSION: This novel, high-performance, cheaper, quicker, higher throughput, low blood volume Nluc-ZnT8 LIPS assay is a safe, non-radioactive alternative to RBA with enhanced sensitivity and ability to discriminate T1D progressors. This method offers an advanced approach to current strategies to screen the general population for T1D risk for immunotherapy trials and to reduce rates of diabetic ketoacidosis at diagnosis.

The method developer's guide to oligonucleotide design.

INTRODUCTION: Development of new methods is essential to make great leaps in science, opening up new avenues for research, but the process behind method development is seldom described. AREAS COVERED: Over the last twenty years we have been developing several new methods, such as in situ PLA, proxHCR, and MolBoolean, using oligonucleotide-conjugated antibodies to visualize protein-protein interactions. Herein, we describe the rationale behind the oligonucleotide systems of these methods. The main objective of this paper is to provide researchers with a description on how we thought when we designed those methods. We also describe in detail how the methods work and how one should interpret results. EXPERT OPINION: Understanding how the methods work is important in selecting an appropriate method for your experiments. We also hope that this paper may be an inspiration for young researchers to enter the field of method development. Seeing a problem is a motivation to develop a solution.

Urea Ligand-Promoted Chainwalking Heteroannulation for the Synthesis of 6- and 7-membered Azaheterocycles.

Typical approaches to heterocycle construction require significant changes in synthetic strategy even for a change as minor as increasing the ring size. The ability to access multiple heterocyclic scaffolds through a common synthetic approach, simply through trivial modification of one reaction component, would enable facile access to diverse libraries of structural analogues of core scaffolds. Here, we show that urea-derived ligands effectively promote Pd-mediated chainwalking processes to enable remote heteroannulation for the rapid construction of six- and seven-membered azaheterocycles under essentially identical reaction conditions. This method demonstrates good functional group tolerance and effectively engages sterically hindered substrates. In addition, this reaction is applicable to target-oriented synthesis, demonstrated through the formal synthesis of antimalarial alkaloid galipinine.

Comparing in vitro affinity measurements of antibodies to TfR1: Surface plasmon resonance versus on-cell affinity.

Despite years of utilizing the transferrin receptor 1 (TfR1) to transport large biomolecules into the brain, there is no consensus on how to optimally measure affinity to it. The aim of this study was to compare different methods for measuring the affinities of anti-TfR1 antibodies. Antibodies 15G11, OX26 and 8D3 are known to successfully carry large biologics across the blood-brain barrier in humans, rats, and mice, respectively. The affinity to their respective species of TfR1 was measured with different surface plasmon resonance setups in Biacore and an on-cell assay. When the antibody was captured and TfR1 was the analyte, the dissociation in Biacore was very slow. The dissociation was faster when the antibody was the analyte and TfR1 was the ligand. The Biacore setup with capture of N-terminal FLAG-tag TfR1 yielded the most similar apparent affinities as the cell assay. In conclusion, it is important to evaluate assay parameters including assay orientation, surface capture method, and antibody-format when comparing binding kinetics for TfR1 antibodies. Although it seems possible to determine relative affinities of TfR1 antibodies using the methods described here, both the FLAG-tag TfR1 capture setup and cell assays likely yield apparent affinities that are most translatable in vivo.

Structure Based Machine Learning Prediction of Retention Times for LC Method Development of Pharmaceuticals.

PURPOSE: Significant resources are spent on developing robust liquid chromatography (LC) methods with optimum conditions for all project in the pipeline. Although, data-driven computer assisted modelling has been implemented to shorten the method development timelines, these modelling approaches require project-specific screening data to model retention time (RT) as function of method parameters. Sometimes method re-development is required, leading to additional investments and redundant laboratory work. Cheminformatics techniques have been successfully used to predict the RT of metabolites & other component mixtures for similar use cases. Here we will show that these techniques can be used to model structurally diverse molecules and predictions of these models trained on multiple LC conditions can be used for downstream data-driven modelling. METHODS: The Molecular Operating Environment (MOE) was used to calculate over 800 descriptors using the strucutres of the analytes. These descriptors were used to model the RT of the analytes under four chromatographic conditions. These models were then used to create data-driven models using LC-SIM. RESULTS: A structural-based Random Forest (RF) model outperformed other techniques in cross-validation studies and predicted the RTs of a randomized test set with a median percentage error less than 4% for all LC conditions. RTs predicted by this structure-based model were used to fit a data-driven model that identifies optimum LC conditions without any additional experimental work. CONCLUSIONS: These results show that small training sets yield pharmaceutically relevant models when used in a combination of structure-based and data-driven model.

N-Butylpyrrolidinone is an equally good solvent as N,N-dimethylformamide for microwave assisted solid phase peptide synthesis.

Solid-phase peptide synthesis (SPPS) is the prevailing method for synthesizing research peptides today. However, SPPS is associated with a significant environmental concern due to the utilization of hazardous solvents such as N,N-dimethylformamide (DMF) or N-methylpyrrolidone, which generate substantial waste. In light of this, our research endeavors to identify more environmentally friendly solvents for SPPS. In this study, we have assessed the suitability of five green solvents as alternatives to DMF in microwave assisted SPPS. The solvents evaluated include Cyrene, ethyl acetate, 1,3-dioxolane, tetrahydro-2-methylfuran, and N-Butylpyrrolidinone (NBP). Our investigation encompassed all stages of the synthesis process, from resin swelling, dissolution of reagents, culminating in the successful synthesis of five diverse peptides, including the challenging ACP 65-74, Peptide 18A, Thymosin α1, and Jung-Redemann peptide. Our findings indicate that NBP emerged as a strong contender, performing on par with DMF in all tested syntheses. Furthermore, we observed that combinations of NBP with either ethyl acetate or tetrahydro-2-methylfuran demonstrated excellent results. This research contributes to the pursuit of more sustainable and environmentally conscious practices in peptide synthesis.

A comprehensive guide for secondary structure and tertiary structure determination in peptides and proteins by circular dichroism spectrometer.

Secondary structure refers to highly regular local sub-structures formed by the polypeptide backbone through hydrogen bonding. The two main types of secondary structures are α-helices and ß-strands (which can form ß-sheets). The development of a robust circular dichroism (CD) method for structural analysis of biomolecules requires careful consideration of several key factors. Solvent selection plays a crucial role in maintaining the native or desired conformation of the sample while ensuring transparency in the relevant wavelength regions. Aqueous buffers are often preferred for studying proteins in their native state. Optimizing the sample concentration and path length is essential to achieve an optimal absorbance range and maximize the signal-to-noise ratio. Typical concentrations for far-UV CD measurements range from 0.1 to 1 mg/ml, with shorter path lengths (1 mm) allowing for higher concentrations and longer path lengths (5 mm) suitable for dilute solutions. Instrumental parameters, such as scanning speed, accumulations, and nitrogen flow rate, significantly impact the quality and reliability of the acquired CD spectra. Data processing is a critical step in obtaining accurate and interpretable CD spectra. Baseline correction, smoothing, and conversion to mean residue ellipticity are essential for reliable secondary structure analysis.

A stability-indicating method development and validation for the determination of related substances in novel synthetic decapeptide by HPLC.

In the present scenario, peptide is an emerging field of research having vast therapeutic applications. Diverse impurities may rise from various stages of the synthesis process and storage of the peptides. Because these contaminants may have an impact on the therapeutic safety and effectiveness of peptides in their approaching applications, they must be identified and carefully monitored. Considering the pharmaceutical importance of the extent of peptides, we were motivated to synthesize a decapeptide and establish a novel gradient reversed-phase high-performance liquid chromatography (RP-HPLC) method for its analysis along with efficient separation of its six related impurities. Different buffers, organic modifiers, and columns were used in the tests for good separation of these impurities. To establish a stability-indicating method, a stress study was also conducted. The International Conference on Harmonization (ICH) guidelines have been followed for validation of the developed analytical method. The validated method revealed sufficient accuracy, specificity, linearity, robustness, precision, and high sensitivity for its intended use. The proposed method could be appropriate for routine analysis and stability assessment of the decapeptide, which might be useful for further scientific investigation.

Analyte and matrix method extension of per- and polyfluoroalkyl substances in food and feed.

The development and expansion of analytical methods for per- and polyfluoroalkyl substances (PFAS) in food are essential for the continued monitoring of the United States (US) food supply and assessments of dietary exposure. In March 2022, the European Union Reference Laboratory for Halogenated Persistent Organic Pollutants in Feed and Food (EURL POPs) released a guidance document covering priority PFAS of interest, including analytical method parameters and limits of quantification (LOQs). As a result, the Food and Drug Administration (FDA) began method extension work to incorporate ten new additional analytes to method C-010.02 including long-chain perfluorosulfonic acids, fluorotelomer sulfonates, and perfluorooctane sulfonamide. Four long-chain carboxylic acids were also validated across all foods, which were previously added to C-010.02 but only validated in seafood. In December 2022, the European Union published Commission Regulation 2022/2388, establishing maximum levels for perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), and perfluorohexane sulfonic acid (PFHxS) in certain foodstuffs, primarily fish, molluscs, crustaceans, and eggs. As a result, the FDA method was evaluated for performance in reaching LOQs defined in Commission Regulation (EU) 2022/1431. The FDA method was found to be able to reach all required LOQs for analytes in matrices with established maximum levels. Currently, method detection limits (MDLs), which are used by the FDA as the lower limit for reporting PFAS in surveillance samples, were in the same range as defined indicative levels. With further method modifications, required LOQs could be met in fruits, vegetables, and milk. Reaching the lower targeted LOQs for these food matrices will require moving the method to an instrument that can provide increased signal:noise gains at the lower limits of quantification.

PFAS ghosts: how to identify, evaluate, and exorcise new and existing analytical interference.

With increasing public awareness of PFAS, and their presence in biological and environmental media across the globe, comes a matching increase in the number of PFAS monitoring studies. As more matrices and sample cohorts are examined, there are more opportunities for matrix interferents to appear as PFAS where there are none (i.e., "seeing ghosts"), impacting subsequent reports. Addressing these ghosts is vital for the research community, as proper analytical measurements are necessary for decision-makers to understand the presence, levels, and potential risks associated with PFAS and protect human and environmental health. To date, PFAS interference has been identified in several matrices (e.g., food, shellfish, blood, tissue); however, additional unidentified interferents are likely to be observed as PFAS research continues to expand. Therefore, the aim of this commentary is several fold: (1) to create and support a publicly available dataset of all currently known PFAS analytical interferents, (2) to allow for the expansion of that dataset as more sources of interference are identified, and (3) to advise the wider scientific community on how to both identify and eliminate current or new analytical interference in PFAS analyses.

Subzero project: comparing trace element profiles of enriched mitochondria fractions from frozen and fresh liver tissue.

From organs to subcellular organelles, trace element (TE) homeostasis is fundamental for many physiological processes. While often overlooked in early stages, manifested TE disbalance can have severe health consequences, particularly in the context of aging or pathological conditions. Monitoring TE concentrations at the mitochondrial level could identify organelle-specific imbalances, contributing to targeted diagnostics and a healthier aging process. However, mitochondria isolation from frozen tissue is challenging, as it poses the risk of TE losses from the organelles due to cryodamage, but would significantly ease routine laboratory work. To address this, a novel method to isolate an enriched mitochondria fraction (EMF) from frozen tissue was adapted from already established protocols. Validation of manganese (Mn), iron (Fe), and copper (Cu) quantification via inductively coupled plasma tandem mass spectrometry (ICP-MS/MS) showed sufficiently low quantification limits for EMF TE analysis. Successful mitochondrial enrichment from frozen liver samples was confirmed via immunoblots and transmission electron microscopy (TEM) revealed sufficient structural integrity of the EMFs. No significant differences in EMF TEs between frozen and fresh tissue were evident for Mn and Cu and only slight decreases in EMF Fe. Consequently, EMF TEs were highly comparable for isolates from both tissue states. In application, this method effectively detected dietary differences in EMF Fe of a murine feeding study and identified the disease status in a Wilson disease rat model based on drastically increased EMF Cu. In summary, the present method is suitable for future applications, facilitating sample storage and high-throughput analyses of mitochondrial TEs.

An improved workflow for the development of MS-compatible liquid chromatography assay purity and purification methods by using automated LC Screening instrumentation and in silico modeling.

The development of liquid chromatography UV and mass spectrometry (LC-UV-MS) assays in pharmaceutical analysis is pivotal to improve quality control by providing critical information about drug purity, stability, and presence and identity of byproducts and impurities. Analytical method development of these assays is time-consuming, which often causes it to become a bottle neck in drug development and poses a challenge for process chemists to quickly improve the chemistry. In this study, a systematic and efficient workflow was designed to develop purity assay and purification methods for a wide range of compounds including peptides, proteins, and small molecules with MS-compatible mobile phases (MP) by using automated LC screening instrumentation and in silico modeling tools. Initial LC MPs and chromatography column screening experiments enabled quick identification of conditions which provided the best resolution in the vicinity of the target compounds, which is further optimized using computer-assisted modeling (LC Simulator from ACD/Labs). The experimental retention times were in good agreement with the predicted retention times from LC Simulator (ΔtR < 7%). This workflow presents a practical workflow to significantly expedite the time needed to develop optimized LC-UV-MS methods, allowing for a facile, automatic method optimization and reducing the amount of manual work involved in developing new methods during drug development.

A comprehensive approach for evaluating the virucidal performance of domestic laundry detergents under practical conditions.

AIMS: We aimed to develop a method to assess the virucidal performance of domestic laundry in a lab-scale washing machine (Rotawash) based on EN 17658. METHODS AND RESULTS: For method development, virus recovery was investigated after drying on cotton carriers for three test viruses murine norovirus (MNV), modified vaccinia virus Ankara (MVA), and bovine coronavirus (BCoV), followed by washing simulations in flasks and Rotawash. MNV and MVA demonstrated sufficient recovery from carriers after drying and washing (up to 40°C and 60 min). BCoV exhibited lower recovery, indicating less relevance as a test virus. Rotawash efficacy tests conducted with MNV, a resistant, non-enveloped virus, showed limited efficacy of a bleach-free detergent, aligning with results from a domestic washing machine. Rotawash washes achieved higher reductions in infectious virus titers than suspension tests, indicating the role of washing mechanics in virus removal. CONCLUSIONS: This study established a practical method to test the virucidal efficacy of laundry detergents in Rotawash, simulating domestic washing.

Development of a metabolomic risk score for exposure to traffic-related air pollution: A multi-cohort study.

To synthesize vast amounts of high-throughput biological information, omics-fields like epigenetics have applied risk scores to develop biomarkers for environmental exposures. Extending the risk score analytic tool to the metabolomic data would be highly beneficial. This research aimed to develop and evaluate metabolomic risk score (metRS) approaches reflecting the biological response to traffic-related air pollution (TRAP) exposure (fine particulate matter, black carbon, and nitrogen dioxide). A simulation study compared three metRS methodologies: elastic net regression, which uses penalized regression to select metabolites, and two variations of thresholding, where a p-value cutoff is used to select metabolites. The methods performance was compared to assess 1) ability to correctly select metabolites associated with daily TRAP and 2) ability of the risk score to predict daily TRAP exposure. Power calculations and false discovery rates (FDR) were calculated for each approach. This metRS was applied to two real cohorts, the Center for Health Discovery and Wellbeing (CHDWB, n = 180) and Environment and Reproductive Health (EARTH, n = 200). In simulations, elastic net regression consistently presented inflated FDR for both high and low effect sizes and across all three sample sizes (n = 200; 500; 1000). Power to detect correct metabolites exceeded 0.8 for all three sample sizes in all three methods. In the real data application assessing associations of metabolomics risk scores and TRAP, associations were largely null. While we did not identify strong associations between the risk scores and TRAP in the real data application, metabolites selected by the risk score approaches were enriched in pathways that are well-known for their association with TRAP. These results demonstrate that certain methodologies to construct metabolomics risk scores are statistically robust and valid; however, standardized metabolic profiling and large sample sizes are required.

Arsenic speciation analysis in human urine for long term epidemiological studies: The Multi-Ethnic Study of Atherosclerosis (MESA).

Arsenic is a ubiquitous toxic metalloid causing serious health problems. Speciation analysis of arsenic in human urine provides valuable insights for large-scale epidemiological studies and informs on sources of exposure as well as human metabolism. The Multi-Ethnic Study of Atherosclerosis (MESA) is a valuable cohort for assessing chronic low-moderate arsenic exposure and health effects in an ethnically diverse US population. We present a state-of-the-art arsenic speciation analysis methodology and its application to 7677 MESA spot urine samples based on high-performance liquid chromatography coupled to inductively coupled plasma mass spectrometry. This method is fast, robust and detects a total of 11 individual As species at method detection limits of 0.02-0.03 µg arsenic/L urine for each individual species. Our analytical approach features excellent mean method accuracy (98%) and precision (5%) for the main arsenic species in urine (arsenobetaine, methylarsonic acid, dimethylarsinic acid, and total inorganic As); intra- (3-6%) and inter-day coefficients of variability (5-6%); column recovery (96 ± 7%); and spike recovery (97 ± 6%). The main arsenic species were detectable in ≥95% of urine samples due to the implementation of an oxidation step. Each individual minor arsenic species was detectable in ≤25% of all urines, although at least one of them was detected in almost half the participants. We identified two minor urinary arsenic species as dimethylarsinoylacetic acid and dimethylarsinoylpropionic acid, potential metabolites of seafood-related arsenicals. We observed differences in individual As species excretion by race/ethnicity, with Asian-American participants featuring 3-4 times higher concentrations compared to other participants. We also found differences by site, body mass index, smoking status, rice intake, and water arsenic levels, potentially indicating different exposures or related to individual bio-metabolism. The proposed approach is suitable for epidemiological studies and the collected data will constitute the base for future research on potential health effects of chronic low-level arsenic exposure.

The Development of One New Normal Phase Liquid Chromatography Method and Thermodynamic Investigation of Olodaterol Hydrochloride Enantiomer.

In order to improve and replace the enantiomer method outlined in the olodaterol hydrochloride draft monograph (From the European Pharmacopoeia forum), one new, simple, and fast enantioselective normal phase high-performance liquid chromatography chiral method was developed on polysaccharide-based Chiral MX (2) (4.6 × 250 mm, 5 µm) column. n-Hexane, ethanol, and diethylamine in the ratio of 40:60:0.1 (V/V/V) were selected as mobile phase at a flow rate of 0.8 mL/min, and the detection was performed on a photodiode array detector at 225 nm with 5 µL injection volume. The column temperature was set at 40°C for better peak shape and sensitivity. The analysis time can be shortened to 15 min, whereas the resolution between enantiomer and olodaterol was found to be even more than 10.0, which was far better than that obtained with the reported method in this draft monograph. The developed chiral method was validated in accordance with ICH Q2 (R1), including specificity, LOD&LOQ, precision, linearity, accuracy, and robustness. Thereby, the proposed method was demonstrated to be suitable for the determination of enantiomer in olodaterol hydrochloride bulk drug and drug product. Besides, the thermodynamic parameters were evaluated on the basis of Van't Hoff plots that was used to explain correlative chiral recognition mechanisms with the chiral stationary phase.