A comprehensive analytical framework integrating liquid chromatography-tandem mass spectrometry metabolomics with chemometrics for metabolite profiling of lettuce varieties and discovery of antibacterial agents

LC/MS-Based Metabolomics Reveals Chemical Variations of Two Broccoli Varieties in Relation to Their Anticholinesterase Activity: In vitro and In silico Studies

Broccoli is commonly consumed as food and as medicine. However, comprehensive metabolic profiling of two broccoli varieties, Romanesco broccoli (RB) and purple broccoli (PB), in relation to their anticholinergic activity has not been fully disclosed. A total of 110 compounds were tentatively identified using UPLC-Q-TOF-MS metabolomics. Distinctively different metabolomic profiles of the two varieties were revealed by principal component analysis (PCA). Furthermore, by volcano diagram analysis, it was found that PB had a significantly higher content of phenolic acids, flavonoids, and glucosinolates, indicating the different beneficial health potentials of PB that demonstrated higher antioxidant and anticholinergic activities. Moreover, Pearson's correlation analysis revealed 18 metabolites, mainly phenolic and sulfur compounds, as the main bioactive. The binding affinity of these biomarkers to the active sites of acetyl- and butyryl-cholinesterase enzymes was further validated using molecular docking studies. Results emphasize the broccoli significance as a functional food and nutraceutical source and highlight its beneficial effects against Alzheimer's disease.

A voltammetric method coupled with chemometrics for determination of a ternary antiparkinson mixture in its dosage form: greenness assessment

An electroanalytical methodology was developed by direct differential pulse voltammetric (DPV) measurement of Levodopa (LD), Carbidopa (CD) and Entacapone (ENT) mixture using bare glassy carbon electrode (GCE) in Britton Robinson (BR) buffer (pH = 2.0). A multivariate calibration model was then applied to the exported preprocessed voltammetric data using partial least square (PLS) as a chemometric tool. Additionally, the model was cross-validated and the number of latent variables (LVs) were determined to produce a reliable model for simultaneous quantitation of the three drugs either in their synthetic mixtures or in their marketed pharmaceutical formulation with high accuracy and precision. Data preprocessing was used to tackle the problem of lacking bi-linearity which is commonly found in electrochemical data. The proposed chemometric model was able to provide fast and reliable technique for quantitative determination of antiparkinson drugs in their dosage forms. This was successfully achieved by utilizing sixteen mixtures as calibration set and nine mixtures as validation set. The percent recoveries for LD, CD and ENT were found to be 100.05% ± 1.28%, 100.04% ± 0.53% and 99.99% ± 1.25%, respectively. The obtained results of the proposed method were statistically compared to those of a previously reported High Performance Liquid Chromatography (HPLC) methodology. Finally, the presented analytical method strongly supports green analytical chemistry regarding the minimization of potentially dangerous chemicals and solvents, as well as reducing energy utilization and waste generation.

Metabolite Profiling of Colvillea racemosa via UPLC-ESI-QTOF-MS Analysis in Correlation to the In Vitro Antioxidant and Cytotoxic Potential against A549 Non-Small Cell Lung Cancer Cell Line

In this study, flower and leaf extracts of Colvillea racemosa were considered a source of bioactive compounds. In this context, the objective of the study focused on investigating the anticancer potential as well as the phytochemical composition of both extracts. The extracts were analyzed by UPLC-ESI-QTOF-MS, and the bioactivity was tested using in vitro antioxidant assays (FRAP, DPPH, and ABTS) in addition to cytotoxic assays on non-small cell lung cancer cell line (A549). Our results clearly indicated the potent radical scavenging capacity of both extracts. Importantly, the flower extract exhibited a greater antioxidant capacity than the leaf extract. In terms of cytotoxic activity, leaf and flower extracts significantly inhibited cell viability with IC50 values of 17.0 and 17.2 µg/mL, respectively. The phytochemical characterization enabled the putative annotation of 42 metabolites, such as saccharides, phenolic acids, flavonoids, amino acids, and fatty acids. Among them, the flavonoid C-glycosides stand out due to their high relative abundance and previous reports on their anticancer bioactivity. For a better understanding of the bioactive mechanisms, four flavonoids (vitexin, kaempferol-3-O-rutinoside, luteolin, and isoorientin) were selected for molecular docking on hallmark protein targets in lung cancer as represented by γ-PI3K, EGFR, and CDK2 through in-silico studies. In these models, kaempferol-3-O-rutinoside and vitexin had the highest binding scores on γ-PI3K and CDK2, followed by isoorientin, so they could be highly responsible for the bioactive properties of C. racemosa extracts.

Assessment of the effect of drying on Brassica greens via a multiplex approach based on LC-QTOF-MS/MS, molecular networking, and chemometrics along with their antioxidant and anticancer activities

Turnip (Brassica rapa var rapa L.) leaves are a rich source of versatile bioactive phytochemicals with great potential in the food and herbal industries. However, the effect of drying on its constituents has never been studied before. Hereto, three drying techniques were compared, namely, lyophilization (LY), vacuum oven (VO), and shade drying (SD). Chemical profiling utilizing liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (LC-QTOF-MS/MS) combined with chemometrics showed the different impacts of the drying methods on the phytochemical composition of the alcoholic leaf extracts. Unsupervised principal component analysis (PCA) and supervised partial least squares-discriminant analysis (PLS-DA) of the LC-QTOF-MS/MS data showed distinct distant clustering across the three drying techniques. Loading plots and VIP scores demonstrated that sinapic acid, isorhamnetin glycosides, and sinapoyl malate were key markers for LY samples. Meanwhile, oxygenated and polyunsaturated fatty acids were characteristic for SD samples and oxygenated polyunsaturated fatty acids and verbascoside were characteristic for VO samples. LY resulted in the highest total phenolics (TP) and total flavonoid (TF) contents followed by SD and VO. LY and SD samples had much higher antioxidant activity than VO measured by 2,2-diphenyl-1-picrylhydrazyl (DPPH), oxygen radical absorbance capacity (ORAC), and iron metal chelation assays. According to the anticancer activity, the drying methods were ranked in descending order as SD > LY ≫ VO when tested against colon, breast, liver, and lung cancer cell lines. Among the identified compounds, flavonoids and omega-3 fatty acids were key metabolites responsible for the anticancer activity as revealed by partial least squares (PLS) regression and correlation analyses. In conclusion, compared to LY, SD projected out as a cost-effective drying method without compromising the phytochemical and biological activities of Brassica greens. The current findings lay the foundation for further studies concerned with the valorization of Brassica greens.

Stability and Biosimilarity Assessment of Bevacizumab Monoclonal Antibody; Orthogonal Testing Protocol Coupled With Peptide Mapping-Principal Component Analysis

BACKGROUND

Biologics are essential in cancer treatment because they stimulate the body's natural response to fight cancer, but they are expensive. Biosimilars are more affordable compared to patent biologicals, but it must be verified that they are as effective as their innovators. Characterization of biosimilars and assessment of interchangeability requires many data points for verification.

OBJECTIVE

The proposed study provides a quality assessment of two new bevacizumab (BVZ) biosimilars, produced by Amgen and Biocad, Inc., through the development and greenness assessment of an orthogonal testing protocol and purity indicating assay, including size-exclusion (SE-HPLC), reversed-phase (RP-HPLC), and cation exchange chromatography (CEX-HPLC) in addition to dynamic light scattering (DLS) and sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE).

METHODS

SE-HPLC method was performed and validated to screen the BVZ monomer and its aggregates and/or fragments. Peak purity and system suitability parameters were calculated. Results indicate that the orthogonal protocol is a useful tool for assessing monoclonal antibody stability. It is a key criterion for biosimilarity assessment. DLS and SDS-PAGE results were compared to each other to reveal close retention times and banding patterns between BVZ innovator and its biosimilars. These results showed that Avastin® and the investigated biosimilars have the same profile in terms of peak area of related compounds within the acceptance limit and apparent molecular weight, and the SDS-PAGE technique was found to be the most eco-friendly technique among others.

CONCLUSIONS

The results obtained highlighted the importance of assessing similarities and differences in ensuring the biosimilarity and interchangeability of the studied products.

HIGHLIGHTS

BVZ is one of the essential monoclonal antibodies in the treatment of colorectal cancer (CRC). BVZ biosimilars were evaluated by developing an orthogonal testing protocol and a purity-indicating assay. The size-exclusion (SE)-HPLC method was applied and validated to monitor the BVZ monomer and its aggregates. The results demonstrated the importance of assessing the stability and biosimilarity of BVZ.

Smart chemometrics-assisted spectrophotometric methods for efficient resolution and simultaneous determination of paracetamol, caffeine, drotaverine HCl along with three of their corresponding related impurities

Three novel, simple and accurate multivariate spectrophotometric assisted mathematical techniques were developed for determination of paracetamol, caffeine, drotaverine HCl and their related impurities. The used multivariate algorithms are principal component regression (PCR), partial least squares (PLS), and synergy intervals partial least squares (siPLS). Linearity of the suggested methods was found to be (1.00-14.60, 1.40-7.00, 1.40-3.80, 1.00-3.00, 1.50-3.50 and 2.50-4.50 µg/mL) for paracetamol, caffeine, drotaverine HCl, and their related impurities; p-aminophenol, theophylline and homoveratric acid, correspondingly. The presented methods were effectively implemented in the determination of the cited compounds in their laboratory prepared mixtures. Commercially available tablet preparation was also analyzed using the applied methods where no impurities were detected and without interference from tablet additives. Moreover, statistical analysis did not reveal any noticeable differences between the obtained results and those acquired from the reported method in terms of accuracy and precision. The developed multivariate algorithms were validated by means of internal and external validation sets. The obtained results showed the siPLS algorithm's superiority to PCR and PLS according to the values of correlation coefficient values (r) and the lowest root mean square error of prediction (RMSEP). The combination of four subintervals [10, 12, 14, and 17] produced the highest efficiency model. Furthermore, these methods may be an applicable substitute to HPLC ones in quality control laboratories during rush of analyses where several samples have to be analyzed in a short time.