Systematic screening and structural characterization of dipeptides using offline 2D LC-LTQ orbitrap MS: A case study of Cordyceps sinensis

A multi-level strategy based on comprehensive two-dimensional liquid chromatography-Q-Orbitrap-mass spectrometry combined with PLS regression model and RT-Ensemble Pred model to intelligently distinguish different geographical locations of Huanglian sample

Huanglian (HL) is a member of the Ranunculaceae family, including Coptis chinensis Franch., Coptis deltoidea C. Y. Cheng et Hsiao, or Coptis teeta Wall. The dried rhizomes are highly esteemed herbal medicine in Chinese pharmacopeia. However, the composition of HL is complex, and current identification technologies are insufficient for conducting a comprehensive analysis of HL, leading to major obstacles in quality control. Therefore, an in-depth exploration of the influence of species diversity and geographic provenance on the chemical profile of HL is imperative for its rational application and quality assurance. To comprehensively analyze compounds in HL samples from diverse geographical regions, this study employed an integrated approach combining offline two-dimensional ultra-high-performance liquid chromatography coupled with quadrupole-Orbitrap mass spectrometry (2D-LC-MS/MS) with online 2D-LC-MS/MS. This dual-platform strategy enabled detailed characterization of complex compound profiles. Additionally, the retention time prediction (RT-Ensemble Pred) models were utilized to predict and identify the retention times of unknown compounds, which particularly facilitated the differentiation of isomers. The comprehensive research resulted in the identification of 150 chemical constituents in HL, including 72 isomers. Furthermore, the compounds were analyzed and categorized according to mathematical classification models, allowing for distinction between various geographical origins. Based on unexposed data, the model demonstrated robust predictive capability, enabling the selection of 20 distinctive characteristic compounds with prominent features for use in geographical origin discrimination. Overall, this multidimensional investigation significantly enhanced our understanding of the chemical composition and inherent variability of HL plant resources, providing crucial technical underpinnings and methodological insights for the comprehensive exploitation and utilization of HL in biomedical and pharmaceutical applications.

Comprehensive profiling and identification of C21 steroids in the root of Marsdenia tenacissima (Dai-Bai-Jie) using offline two-dimensional chromatography (LC × SFC) with Q-TOF/MS

Dai-Bai-Jie, the root of the plant Marsdenia tenacissima from the Asclepiadaceae family, is well-known for its therapeutic effects in clearing heat, detoxifying, reducing swelling, and relieving pain as one of the most commonly used Dai medicine. Due to numerous structurally similar C21 steroidal compounds in Dai-Bai-Jie, chemical composition profiling has been substantially challenged. In this study, an offline two-dimensional chromatographic method (LC × SFC separation system) was developed to address these issues. Using the Hypersil Gold (1stD LC column) and 2-PIC (2ndD SFC column) based on 40 reference standards, the orthogonality was as high as 83.83 %. Most profiled ion peaks were tentatively identified through quadrupole time-of-flight mass spectrometry and a self-built compound virtual library. Consequently, the integrated method effectively addressed and resolved the issues associated with co-elution, thus significantly expanding the peak capacity. This advancement identified 362 C21 steroidal components, 319 of which were speculated to be potentially novel compounds. Furthermore, 86 groups of isomeric compounds were distinguished. This method provides a comprehensive understanding of chemical composition of Dai-Bai-Jie and an integrated qualitative analysis method for the C21 steroids.

Screening for promising multi-target bioactive components from Cortex Mori Radicis for the treatment of chronic cor pulmonale based on immobilized beta1-adrenergic receptor and beta2-adrenergic receptor chromatography

Cortex Morin Radicis (CMR) is the dried root bark of Morus alba. L. It has a variety of effects such as antibacterial, anti-tumour, treatment of cardiovascular diseases or upper respiratory tract disease and so on. The pursuit for drugs selected from Cortex Mori Radicis having improved therapeutic efficacy necessitates increasing research on new assays for screening bioactive compounds with multi-targets. In this work, we applied immobilized β1-AR and β2-AR as the stationary phase in chromatographic column to screen bioactive compounds from Cortex Morin Radicis. Specific ligands of the two receptors (e.g. esmolol, metoprolol, atenolol, salbutamol, methoxyphenamine, tulobuterol and clorprenaline) were utilized to characterize the specificity and bioactivity of the columns. We used high performance affinity chromatography coupled with ESI-MS to screen targeted compounds of Cortex Morin Radicis. By zonal elution, we identified morin as a bioactive compound simultaneously binding to β1-AR and β2-AR. The compound exhibited the association constants of 3.10 × 104 and 2.60 × 104 M-1 on the β1-AR and β2-AR column. On these sites, the dissociation rate constants were calculated to be 0.131 and 0.097 s-1. Molecular docking indicated that the binding of morin to the two receptors occurred on Asp200, Asp121, and Val122 of β1-AR, Asn312, Thr110, Asp113, Tyr316, Gly90, Phe193, Ile309, and Trp109 of β2-AR. Likewise, mulberroside C was identified as the bioactive compound binding to β2-AR. The association constants and dissociation rate constants were calculated to be 1.08 × 104 M-1 and 0.900 s-1. Molecular docking also indicated that mulberroside C could bind to β2-AR receptor on its agonist site. Taking together, we demonstrated that the chromatographic strategy to identify bioactive natural products based on the β1-AR and β2-AR immobilization, has potential for screening bioactive compounds with multi-targets from complex matrices including traditional Chinese medicines.

An Analysis of Polysaccharides from Eight Plants by a Novel Heart-Cutting Two-Dimensional Liquid Chromatography Method

Natural polysaccharides are important active biomolecules. However, the analysis and structural characterization of polysaccharides are challenging tasks that often require multiple techniques and maps to reflect their structural features. This study aimed to propose a new heart-cutting two-dimensional liquid chromatography (2D-LC) method for separating and analyzing polysaccharides to explore the multidimensional information of polysaccharide structure in a single map. That is, the first-dimension liquid chromatography (1D-LC) presents molecular-weight information, and the second-dimension liquid chromatography (2D-LC) shows the fingerprints of polysaccharides. In this 2D-LC system, the size-exclusion chromatography-hydrophilic interaction chromatography (SEC-HILIC) model was established. Coupling with a charged aerosol detector (CAD) eliminated the need for the derivatization of the polysaccharide sample, allowing the whole process to be completed within 80 min. The methods were all validated in terms of precision, linearity, stability, and repeatability. The capability of the new 2D-LC method was demonstrated in determining various species of natural polysaccharides. Our experimental data demonstrated the feasibility of the whole systematic approach, opening the door for further applications in the field of natural polysaccharide analysis.

An on-line stop-flow RPLC × SEC-MS/DPPH radical scavenging activity analysis system and its application in separation and identification of antioxidant peptides

Food-derived antioxidant peptides have become the focus of research due to their high safety and low cost. However, the discovery is suffering from a low efficient and empirical approach, involving multi-step off-line separation and identification. In this work, an on-line stop-flow RPLC × SEC-MS/DPPH radical scavenging activity analysis system was developed. For optimization, the conditions: 10 m reaction loop, 200 μM DPPH radical concentration, 40℃ temperature and 0.06 % formic acid were recommended. The system was fully validated by its application in glutathione analysis. The system was further applied in analysis of complex mixed standards, and the dipeptides GC (Gly-Cys) and CW (Cys-Trp) with relatively strong DPPH radical scavenging activity were validated. Maize protein hydrolysates were used for tests and the peptide AC (Ala-Cys) of high probability with strong DPPH radical scavenging activity was identified, demonstrating a high potential of the system. This would help to facilitate the discovery of antioxidative peptides in the future.

Comprehensive metabolome characterization and comparison between two sources of Dragon's blood by integrating liquid chromatography/mass spectrometry and chemometrics

Dragon's Blood (DB) serves as a precious Chinese medicine facilitating blood circulation and stasis dispersion. Daemonorops draco (D. draco; Qi-Lin-Jie) and Dracaena cochinchinensis (D. cochinchinenesis; Long-Xue-Jie) are two reputable plant sources for preparing DB. This work was designed to comprehensively characterize and compare the metabolome differences between D. draco and D. cochinchinenesis, by integrating liquid chromatography/mass spectrometry and untargeted metabolomics analysis. Offline two-dimensional liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (2D-LC/IM-QTOF-MS), by utilizing a powerful hybrid scan approach, was elaborated for multicomponent characterization. Configuration of an XBridge Amide column and an HSS T3 column in offline mode exhibited high orthogonality (A0 0.80) in separating the complex components in DB. Particularly, the hybrid high-definition MSE-high definition data-dependent acquisition (HDMSE-HDDDA) in both positive and negative ion modes was applied for data acquisition. Streamlined intelligent data processing facilitated by the UNIFI™ (Waters) bioinformatics platform and searching against an in-house chemical library (recording 223 known compounds) enabled efficient structural elucidation. We could characterize 285 components, including 143 from D. draco and 174 from D. cochinchinensis. Holistic comparison of the metabolomes among 21 batches of DB samples by the untargeted metabolomics workflows unveiled 43 significantly differential components. Separately, four and three components were considered as the marker compounds for identifying D. draco and D. cochinchinenesis, respectively. Conclusively, the chemical composition and metabolomic differences of two DB resources were investigated by a dimension-enhanced analytical approach, with the results being beneficial to quality control and the differentiated clinical application of DB.

Progress and prediction of multicomponent quantification in complex systems with practical LC-UV methods

Complex systems exist widely, including medicines from natural products, functional foods, and biological samples. The biological activity of complex systems is often the result of the synergistic effect of multiple components. In the quality evaluation of complex samples, multicomponent quantitative analysis (MCQA) is usually needed. To overcome the difficulty in obtaining standard products, scholars have proposed achieving MCQA through the "single standard to determine multiple components (SSDMC)" approach. This method has been used in the determination of multicomponent content in natural source drugs and the analysis of impurities in chemical drugs and has been included in the Chinese Pharmacopoeia. Depending on a convenient (ultra) high-performance liquid chromatography method, how can the repeatability and robustness of the MCQA method be improved? How can the chromatography conditions be optimized to improve the number of quantitative components? How can computer software technology be introduced to improve the efficiency of multicomponent analysis (MCA)? These are the key problems that remain to be solved in practical MCQA. First, this review article summarizes the calculation methods of relative correction factors in the SSDMC approach in the past five years, as well as the method robustness and accuracy evaluation. Second, it also summarizes methods to improve peak capacity and quantitative accuracy in MCA, including column selection and two-dimensional chromatographic analysis technology. Finally, computer software technologies for predicting chromatographic conditions and analytical parameters are introduced, which provides an idea for intelligent method development in MCA. This paper aims to provide methodological ideas for the improvement of complex system analysis, especially MCQA.