Multivariate data analysis to evaluate the fingerprint peaks responsible for the cytotoxic activity of Mallotus species

Chemometric-based drug discovery approaches from natural origins using hyphenated chromatographic techniques

INTRODUCTION

Isolation and characterization of bioactive components from complex matrices of marine or terrestrial biological origins are the most challenging issues for natural product chemists. Biochemometric is a new potential scope in natural product analytical science, and it is a methodology to find the compound's correlation to their bioactivity with the help of hyphenated chromatographic techniques and chemometric tools.

OBJECTIVES

The present review aims to evaluate the application of chemometric tools coupled to chromatographic techniques for drug discovery from natural resources.

METHODS

The searching keywords "biochemometric," "chemometric," "chromatography," "natural products bioassay," and "bioassay" were selected to search the published articles between 2010-2023 using different search engines including "Pubmed", "Web of Science," "ScienceDirect," and "Google scholar."

RESULTS

An initial stage in natural product analysis is applying the chromatographic hyphenated techniques in conjunction with biochemometric approaches. Among the applied chromatographic techniques, liquid chromatography (LC) techniques, have taken up more than half (53%) and also, mass spectroscopy (MS)-based chromatographic techniques such as LC-MS are the most widely used techniques applied in combination with chemometric methods for natural products bioassay. Considering the complexity of dataset achieved from chromatographic hyphenated techniques, chemometric tools have been increasingly employed for phytochemical studies in the context of determining botanicals geographical origin, quality control, and detection of bioactive compounds.

CONCLUSION

Biochemometric application is expected to be further improved with advancing in data acquisition methods, new efficient preprocessing, model validation and variable selection methods which would guarantee that the applied model to have good prediction ability in compound relation to its bioactivity.

Authentication of Herbal Medicines Based on Modern Analytical Technology Combined with Chemometrics Approach: A Review

Since ancient times, herbal medicines (HMs) have been widely popular with consumers as a "natural" drug for health care and disease treatment. With the emergence of problems, such as increasing demand for HMs and shortage of resources, it often occurs the phenomenon of shoddy exceed and mixing the false with the genuine in the market. There is an urgent need to evaluate the quality of HMs to ensure their important role in health care and disease treatment, and to reduce the possibility of threat to human health. Modern analytical technology is can be analyzed for analyzing chemical components of HMs or their preparations. Reflecting complex chemical components' characteristic curves in the analysis sample, and the comprehensive effect of active ingredients of HMs. In this review, modern analytical technology (chromatography, spectroscopy, mass spectrometry), chemometrics methods (unsupervised, supervised) and their advantages, disadvantages, and applicability were introduced and summarized. In addition, the authentication application of modern analytical technology combined with chemometrics methods in four aspects, including origin, processing methods, cultivation methods, and adulteration of HMs have also been discussed and illustrated by a few typical studies. This article offers a general workflow of analytical methods that have been applied for HMs authentication and explains that the accuracy of authentication in favor of the quality assurance of HMs. It was provided reference value for the development and application of modern HMs.

Metabolomic study of soft corals from the Colombian Caribbean: PSYCHE and 1H-NMR comparative analysis

Marine organisms have evolved to survive against predators in complex marine ecosystems via the production of chemical compounds. Soft corals (Cnidaria, Anthozoa, Octocorallia) are an important source of chemically diverse metabolites with a broad spectrum of biological activities. Herein, we perform a comparative study between high-resolution proton nuclear magnetic resonance (1H-NMR) and pure shift yielded by chirp excitation (PSYCHE) experiments to analyze the metabolic profile of 24 soft corals from the Colombian Caribbean to correlate chemical fingerprints with their cytotoxic activity against three cancer cell lines (human cervical carcinoma (SiHa), human prostatic carcinoma (PC3) and human lung adenocarcinoma (A549)). All data obtained were explored using multivariate analysis using principal components analysis (PCA) and orthogonal partial least squares (OPLS) analysis. The results did not show a significant correlation between clusters using 1H-NMR data in the PCA and OPLS-DA models and therefore did not provide conclusive evidence; on the other hand, a metabolomic analysis of PSYCHE data obtained under the same parameters revealed that when a decoupled experiment is performed, it was possible to establish a statistically valid correlation between the chemical composition of soft corals and their cytotoxic activity against the PC3 cancer cell line, where the asperdiol and plexaurolone markers were putatively identified and related to the cytotoxic activity presented by extracts of Plexaurella sp. and Plexaura kukenthali, respectively. These results increase the speed, effectiveness and reliability of analyses for the study of this type of complex matrices.

Defining a standardized methodology for the determination of the antioxidant capacity: case study of Pistacia atlantica leaves

Antioxidant activity can be measured by a variety of methods, that include hydrogen atom transfer (HAT) and single electron transfer (ET) methods.

Comparative Analyses of Metabolomic Fingerprints and Cytotoxic Activities of Soft Corals from the Colombian Caribbean

Soft corals (Cnidaria, Anthozoa, Octocorallia) are a diverse group of marine invertebrates that inhabit various marine environments in tropical and subtropical areas. Several species are recognized as prolific sources of compounds with a wide array of biological activities. Recent advances in analytical techniques, supported by robust statistical analyses, have allowed the analysis and characterization of the metabolome present in a single living organism. In this study, a liquid chromatography-high resolution mass spectrometry metabolomic approach was applied to analyze the metabolite composition of 28 soft corals present in the Caribbean coast of Colombia. Multivariate data analysis was used to correlate the chemical fingerprints of soft corals with their cytotoxic activity against tumor cell lines for anticancer purpose. Some diterpenoids were identified as specific markers to discriminate between cytotoxic and non-cytotoxic crude extracts of soft corals against tumor cell lines. In the models generated from the comparative analysis of PLS-DA for tumor lines, A549 and SiHa, the diterpene 13-keto-1,11-dolabell-3(E),7(E),12(18)-triene yielded a high score in the variable importance in projection. These results highlight the potential of metabolomic approaches towards the identification of cytotoxic agents against cancer of marine origin. This workflow can be useful in several studies, mainly those that are time consuming, such as traditional bioprospecting of marine natural products.

Identification of some Bioactive Metabolites in a Fractionated Methanol Extract from Ipomoea aquatica (Aerial Parts) through TLC, HPLC, UPLC-ESI-QTOF-MS and LC-SPE-NMR Fingerprints Analyses

INTRODUCTION

The plant species Ipomoea aquatica contains various bioactive constituents, e.g. phenols and flavonoids, which have several medical uses. All previous studies were executed in Asia; however, no reports are available from Africa, and the secondary metabolites of this plant species from Africa are still unknown.

OBJECTIVE

The present study aims finding suitable conditions to identify the bioactive compounds from different fractions.

METHODOLOGY

Chromatographic fingerprint profiles of different fractions were developed using high-performance liquid chromatography (HPLC) and then these conditions were transferred to thin-layer chromatography (TLC). Subsequently, the chemical structure of some bioactive compounds was elucidated using ultra-performance liquid chromatography-quadrupole time of flight-tandem mass spectrometry (UPLC-QTOF-MS) and liquid chromatography-solid phase extraction-nuclear magnetic resonance (LC-SPE-NMR) spectroscopy.

RESULTS

The HPLC fingerprints, developed on two coupled Chromolith RP-18e columns, using a gradient mobile phase (methanol/water/trifluoroacetic acid, 5:95:0.05, v/v/v), showed more peaks than the TLC profile. The TLC fingerprint allows the identification of the types of chemical constituents, e.g. flavonoids. Two flavonoids (nicotiflorin and ramnazin-3-O-rutinoside) and two phenolic compounds (dihydroxybenzoic acid pentoside and di-pentoside) were tentatively identified by QTOF-MS, while NMR confirmed the structure of rutin and nicotiflorin.

CONCLUSION

The HPLC and TLC results showed that HPLC fingerprints give more and better separated peaks, but TLC helped in determining the class of the active compounds in some fractions. Bioactive constituents were identified as well using MS and NMR analyses. Two flavonoids and two phenolic compounds were tentatively identified in this species for the first time, to the best of our knowledge. Copyright © 2017 John Wiley & Sons, Ltd.

Cytotoxic Constituents of Mallotus Microcarpus

A new 3-methoxybenzensulfonic acid 4- O-β-D-glucopyranoside (1), and ten known compounds (2–11) were isolated from the methanolic extract of the stems of Mallotus microcarpus. The cytotoxicity of the isolated compounds was evaluated by the MTT method. 3-Methoxybenzensulfonic acid 4- O-β-D-glucopyranoside (1) and methyl salicylate 2-rutinoside (5) showed strong cytotoxicity against EGFR-TKI-resistant human lung cancer A549 cells in comparison with camptothecin. Compound 1, leonuriside A (2), 3,4'-dihydroxypropiophenone 3- O-glucoside (6) and (1 R,2 S)-hovetrichoside A (10) inhibited the growth of human breast cancer MCF-7 cell line with IC50 values in the range of 0.48–1.78 μM. This is the first report on the chemical composition and cytotoxic activity of M. microcarpus.

Prediction of Radix Astragali Immunomodulatory Effect of CD80 Expression from Chromatograms by Quantitative Pattern-Activity Relationship

The current use of a single chemical component as the representative quality control marker of herbal food supplement is inadequate. In this CD80-Quantitative-Pattern-Activity-Relationship (QPAR) study, we built a bioactivity predictive model that can be applicable for complex mixtures. Through integrating the chemical fingerprinting profiles of the immunomodulating herb Radix Astragali (RA) extracts, and their related biological data of immunological marker CD80 expression on dendritic cells, a chemometric model using the Elastic Net Partial Least Square (EN-PLS) algorithm was established. The EN-PLS algorithm increased the biological predictive capability with lower value of RMSEP (11.66) and higher values of R_p² (0.55) when compared to the standard PLS model. This CD80-QPAR platform provides a useful predictive model for unknown RA extract's bioactivities using the chemical fingerprint inputs. Furthermore, this bioactivity prediction platform facilitates identification of key bioactivity-related chemical components within complex mixtures for future drug discovery and understanding of the batch-to-batch consistency for quality clinical trials.

Chemometrics-enhanced high performance liquid chromatography-ultraviolet detection of bioactive metabolites from phytochemically unknown plants

This work describes the use of Colubrina greggii as a model to investigate the use of chemometric analysis combined with data from a leishmanicidal bioassay, using Principal Component Analysis (PCA) and Orthogonal Projections to Latent Structures (O-PLS), to detect biologically active natural products in crude extracts from plants having little or no phytochemical information. A first analysis of the HPLC-UV profiles of the extract and its semi-purified fractions using both Principal Component Analysis (PCA) and Orthogonal Partial Least Squares (O-PLS) indicated that the components at tR 48.2, 48.7, 51.8min correlated with the variation in bioactivity. However, a further O-PLS analysis of the HPLC-UV profiles of fractions obtained through a final semi-preparative HPLC purification showed two components at tR 48.7 and 49.5min which correlated with the variation of the bioactivity in a high performance predictive model, with high determination coefficient, high correlation coefficient values (R(2) and Q(2)=0.99) and a low root mean square error (RMSE=0.018). This study demonstrates that the association of chemometric analysis with bioassay results can be an excellent strategy for the detection and isolation of bioactive metabolites from phytochemically unknown plant crude extracts.

Ensemble learning for prediction of the bioactivity capacity of herbal medicines from chromatographic fingerprints

Background

Recent quality control of complex mixtures, including herbal medicines, is not limited to chemical chromatographic definition of one or two selected compounds; multivariate linear regression methods with dimension reduction or regularisation have been used to predict the bioactivity capacity from the chromatographic fingerprints of the herbal extracts. The challenge of this type of analysis requires a multi-dimensional approach at two levels: firstly each herb comprises complex mixtures of active and non-active chemical components; and secondly there are many factors relating to the growth, production, and processing of the herbal products. All these factors result in the significantly diverse concentrations of bioactive compounds in the herbal products. Therefore, it is imminent to have a predictive model with better generalisation that can accurately predict the bioactivity capacity of samples when only the chemical fingerprints data are available.

Results

In this study, the algorithm of Stacking Multivariate Linear Regression (SMLR) and a few other commonly used chemometric approaches were evaluated. They were to predict the Cluster of Differentiation 80 (CD80) expression bioactivity of a commonly used herb, Astragali Radix (AR), from the corresponding chemical chromatographic fingerprints. SMLR provides a superior prediction accuracy in comparison with the other multivariate linear regression methods of PCR, PLSR, OPLS and EN in terms of MSE_test and the goodness of prediction of test samples.

Conclusions

SMLR is a better platform than some multivariate linear regression methods. The first advantage of SMLR is that it has better generalisation to predict the bioactivity capacity of herbal medicines from their chromatographic fingerprints. Future studies should aim to further improve the SMLR algorithm. The second advantage of SMLR is that single chemical compounds can be effectively identified as highly bioactive components which demands further CD80 bioactivity confirmation..