{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T10:28:54Z","timestamp":1783420134062,"version":"3.54.6"},"reference-count":48,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2024,12,20]],"date-time":"2024-12-20T00:00:00Z","timestamp":1734652800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European H2020-MSCARISE-2018","award":["823973"],"award-info":[{"award-number":["823973"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Molecules"],"abstract":"<jats:p>High-Performance Thin Layer Chromatography (HPTLC) is widely utilized in natural products research due to its simplicity, low cost, and short total analysis time, including data treatment. While bioautography can be used for rapid detection of bioactive compounds in extracts, the number of available bioautographic methods is limited mainly due to the high cost and difficulty in developing protocols that lead to accurate and reproducible results. For this reason, an alternative method for the detection of bioactive compounds in plant extracts prior to their isolation using HPTLC, combined with multivariate chemometrics, was previously explored by our lab. To evaluate this method and compare it to other chemometrics-based methods, an artificial mixture (ArtExtr) of 59 standard compounds was used as a case study. The ArtExtr was fractionated by FCPC and the inhibitory activity of all fractions against DPPH was evaluated, while their chemical profiles were recorded using HPTLC. Multivariate statistics and the heterocovariance approach (HetCA) were employed and compared, with the success rate in detecting the ArtExtr bioactive substances being 85.7% via sparse heterocovariance (sHetCA). HPTLC combined with sHetCA can serve as a valuable tool for the detection of bioactive compounds in complex mixtures when bioautography is not feasible.<\/jats:p>","DOI":"10.3390\/molecules29246027","type":"journal-article","created":{"date-parts":[[2024,12,23]],"date-time":"2024-12-23T10:06:52Z","timestamp":1734948412000},"page":"6027","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["HPTLC Combined with sHetCA and Multivariate Statistics for the Detection of Bioactive Compounds in Complex Mixtures"],"prefix":"10.3390","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-0328-0323","authenticated-orcid":false,"given":"Vaios","family":"Amountzias","sequence":"first","affiliation":[{"name":"Department of Pharmacognosy and Natural Products Chemistry, Faculty of Pharmacy, National and Kapodistrian University of Athens, 15771 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0107-9991","authenticated-orcid":false,"given":"Evagelos","family":"Gikas","sequence":"additional","affiliation":[{"name":"Department of Analytical Chemistry, Faculty of Chemistry, National and Kapodistrian University of Athens, 15771 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3335-8135","authenticated-orcid":false,"given":"Nektarios","family":"Aligiannis","sequence":"additional","affiliation":[{"name":"Department of Pharmacognosy and Natural Products Chemistry, Faculty of Pharmacy, National and Kapodistrian University of Athens, 15771 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"12647","DOI":"10.1021\/acs.analchem.8b02866","article-title":"Office Chromatography: Miniaturized All-in-One Open-Source System for Planar Chromatography","volume":"90","author":"Fichou","year":"2018","journal-title":"Anal. Chem."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"14554","DOI":"10.1021\/acs.analchem.2c02339","article-title":"2LabsToGo\u2014Recipe for Building Your Own Chromatography Equipment Including Biological Assay and Effect Detection","volume":"94","author":"Sing","year":"2022","journal-title":"Anal. Chem."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"12494","DOI":"10.1021\/acs.analchem.6b04017","article-title":"Proof-of-Principle of rTLC, an Open-Source Software Developed for Image Evaluation and Multivariate Analysis of Planar Chromatograms","volume":"88","author":"Fichou","year":"2016","journal-title":"Anal. Chem."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"842","DOI":"10.1021\/ed084p842","article-title":"Digitally Enhanced Thin-Layer Chromatography: An Inexpensive, New Technique for Qualitative and Quantitative Analysis","volume":"84","author":"Hess","year":"2007","journal-title":"J. Chem. Educ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"11642","DOI":"10.1039\/D3RA01211E","article-title":"A Novel Smartphone HPTLC Assaying Platform versus Traditional Densitometric Method for Simultaneous Quantification of Alfuzosin and Solifenacin in Their Dosage Forms as Well as Monitoring Content Uniformity and Drug Residues on the Manufacturing Equipment","volume":"13","author":"Wadie","year":"2023","journal-title":"RSC Adv."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"6984","DOI":"10.1021\/acs.analchem.8b01298","article-title":"Powerful Artificial Neural Network for Planar Chromatographic Image Evaluation, Shown for Denoising and Feature Extraction","volume":"90","author":"Fichou","year":"2018","journal-title":"Anal. Chem."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.chroma.2018.05.027","article-title":"quanTLC, an Online Open-Source Solution for Videodensitometric Quantification","volume":"1560","author":"Fichou","year":"2018","journal-title":"J. Chromatogr. A"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"9057","DOI":"10.1021\/acs.analchem.0c01251","article-title":"Orthogonal Hyphenation of Planar and Liquid Chromatography for Mass Spectrometry of Biomarkers out of the Bioassay Matrix (NP-HPTLC-UV\/Vis\/FLD-Bioassay-RP\/IEX-HPLC-UV\/Vis-ESI-MS)","volume":"92","author":"Kirchert","year":"2020","journal-title":"Anal. Chem."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Wang, M., Zhang, Y., Wang, R., Wang, Z., Yang, B., and Kuang, H. (2021). An Evolving Technology That Integrates Classical Methods with Continuous Technological Developments: Thin-Layer Chromatography Bioautography. Molecules, 26.","DOI":"10.3390\/molecules26154647"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"123553","DOI":"10.1016\/j.jchromb.2022.123553","article-title":"Planar Chromatography\u2014Current Practice and Future Prospects","volume":"1214","author":"Wilson","year":"2023","journal-title":"J. Chromatogr. B"},{"key":"ref_11","unstructured":"(2024, March 07). CAMAG visionCATS Guide\u2014visionCATS 4.0 Documentation. Available online: https:\/\/visioncats-doc.camag.com\/400\/VisionCatsGuide\/VisionCatsGuide.html#peak-profile-from-images-ppi."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Spangenberg, B., Poole, C.F., and Weins, C. (2011). Quantitative Thin-Layer Chromatography: A Practical Survey, Springer.","DOI":"10.1007\/978-3-642-10729-0"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.jpba.2012.03.034","article-title":"HPTLC Methods to Assay Active Ingredients in Pharmaceutical Formulations: A Review of the Method Development and Validation Steps","volume":"66","author":"Shewiyo","year":"2012","journal-title":"J. Pharm. Biomed. Anal."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Lawag, I.L., Sostaric, T., Lim, L.Y., Hammer, K., and Locher, C. (2022). The Development and Application of a HPTLC-Derived Database for the Identification of Phenolics in Honey. Molecules, 27.","DOI":"10.3390\/molecules27196651"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2684","DOI":"10.1016\/j.chroma.2010.12.069","article-title":"Bioautography Detection in Thin-Layer Chromatography","volume":"1218","author":"Choma","year":"2011","journal-title":"J. Chromatogr. A"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1002\/pca.2669","article-title":"Recent Advances in Effect-directed Enzyme Assays Based on Thin-layer Chromatography","volume":"28","author":"Wolfram","year":"2017","journal-title":"Phytochem. Anal."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1080\/10826076.2020.1725548","article-title":"Evaluation of Various Biological Activities of Natural Compounds by TLC\/HPTLC","volume":"43","author":"Hosu","year":"2020","journal-title":"J. Liq. Chromatogr. Relat. Technol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1080\/10408347.2020.1797467","article-title":"The TLC-Bioautography as a Tool for Rapid Enzyme Inhibitors Detection\u2014A Review","volume":"52","year":"2022","journal-title":"Crit. Rev. Anal. Chem."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1198","DOI":"10.1055\/s-0035-1546250","article-title":"Prevention of False-Positive Results: Development of an HPTLC Autographic Assay for the Detection of Natural Tyrosinase Inhibitors","volume":"81","author":"Taibon","year":"2015","journal-title":"Planta Med."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.chroma.2014.10.091","article-title":"Current Approaches and Challenges for the Metabolite Profiling of Complex Natural Extracts","volume":"1382","author":"Wolfender","year":"2015","journal-title":"J. Chromatogr. A"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"704","DOI":"10.1021\/acs.analchem.8b05112","article-title":"Accelerating Metabolite Identification in Natural Product Research: Toward an Ideal Combination of Liquid Chromatography\u2013High-Resolution Tandem Mass Spectrometry and NMR Profiling, in Silico Databases, and Chemometrics","volume":"91","author":"Wolfender","year":"2019","journal-title":"Anal. Chem."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"855","DOI":"10.1039\/C9NP00004F","article-title":"Innovative Omics-Based Approaches for Prioritisation and Targeted Isolation of Natural Products\u2014New Strategies for Drug Discovery","volume":"36","author":"Wolfender","year":"2019","journal-title":"Nat. Prod. Rep."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1967","DOI":"10.1039\/D1NP00023C","article-title":"Advances in Decomposing Complex Metabolite Mixtures Using Substructure- and Network-Based Computational Metabolomics Approaches","volume":"38","author":"Beniddir","year":"2021","journal-title":"Nat. Prod. Rep."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"758","DOI":"10.1021\/acs.jnatprod.7b00737","article-title":"Bioactivity-Based Molecular Networking for the Discovery of Drug Leads in Natural Product Bioassay-Guided Fractionation","volume":"81","author":"Nothias","year":"2018","journal-title":"J. Nat. Prod."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.aca.2019.04.038","article-title":"Targeting Bioactive Compounds in Natural Extracts\u2014Development of a Comprehensive Workflow Combining Chemical and Biological Data","volume":"1070","author":"Ory","year":"2019","journal-title":"Anal. Chim. Acta"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1021\/acscentsci.1c01108","article-title":"NP Analyst: An Open Online Platform for Compound Activity Mapping","volume":"8","author":"Lee","year":"2022","journal-title":"ACS Cent. Sci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1235","DOI":"10.1002\/pca.3175","article-title":"Correlation of Chemical Profiles Obtained from 1H-NMR and LC\u2013MS Metabolomics with A-glucosidase Inhibition Activity for Varietal Selections of Ficus deltoidea","volume":"33","author":"Kasim","year":"2022","journal-title":"Phytochem. Anal."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Xiong, Y., Kim, H.K., \u00d6zer, \u00d6.\u00c7., Van Duijn, B., Korthout, H.A.A.J., Zi, L., and Cai, A. (2023). Synergistic Inhibiting Effect of Phytochemicals in Rheum palmatum on Tyrosinase Based on Metabolomics and Isobologram Analyses. Molecules, 28.","DOI":"10.3390\/molecules28030944"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2531","DOI":"10.1002\/slct.201600744","article-title":"Heterocovariance Based Metabolomics as a Powerful Tool Accelerating Bioactive Natural Product Identification","volume":"1","author":"Aligiannis","year":"2016","journal-title":"ChemistrySelect"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1016\/j.phytol.2017.03.001","article-title":"Could Multivariate Statistics Exploit HPTLC and NMR Data to Reveal Bioactive Compounds? The Case of Paeonia mascula","volume":"20","author":"Boka","year":"2017","journal-title":"Phytochem. Lett."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"111547","DOI":"10.1016\/j.jep.2018.10.008","article-title":"Efficient Identification of Acetylcholinesterase and Hyaluronidase Inhibitors from Paeonia Parnassica Extracts through a HeteroCovariance Approach","volume":"257","author":"Michalea","year":"2020","journal-title":"J. Ethnopharmacol."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Grienke, U., Foster, P.A., Zwirchmayr, J., Tahir, A., Rollinger, J.M., and Mikros, E. (2019). 1H NMR-MS-Based Heterocovariance as a Drug Discovery Tool for Fishing Bioactive Compounds out of a Complex Mixture of Structural Analogues. Sci. Rep., 9.","DOI":"10.1038\/s41598-019-47434-8"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Zwirchmayr, J., Grienke, U., Hummelbrunner, S., Seigner, J., de Martin, R., Dirsch, V.M., and Rollinger, J.M. (2020). A Biochemometric Approach for the Identification of In Vitro Anti-Inflammatory Constituents in Masterwort. Biomolecules, 10.","DOI":"10.3390\/biom10050679"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1021\/acs.jnatprod.2c00481","article-title":"1H NMR-Based Biochemometric Analysis of Morus Alba Extracts toward a Multipotent Herbal Anti-Infective","volume":"86","author":"Langeder","year":"2023","journal-title":"J. Nat. Prod."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.chroma.2016.08.005","article-title":"The Use of Chemometrics to Study Multifunctional Indole Alkaloids from Psychotria nemorosa (Palicourea comb. nov.). Part II: Indication of Peaks Related to the Inhibition of Butyrylcholinesterase and Monoamine Oxidase-A","volume":"1463","author":"Viaene","year":"2016","journal-title":"J. Chromatogr. A"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1002\/pca.2670","article-title":"Integrated HPTLC-Based Methodology for the Tracing of Bioactive Compounds in Herbal Extracts Employing Multivariate Chemometrics. A Case Study on Morus alba: Integrated HPTLC-Based Methodology to Identify Bioactive Compounds","volume":"28","author":"Chaita","year":"2017","journal-title":"Phytochem. Anal."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"20090","DOI":"10.1021\/acs.analchem.4c05080","article-title":"Can NMR-HetCA Be a Reliable Prediction Tool for the Direct Identification of Bioactive Substances in Complex Mixtures?","volume":"96","author":"Amountzias","year":"2024","journal-title":"Anal. Chem."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Yamauchi, M., Kitamura, Y., Nagano, H., Kawatsu, J., and Gotoh, H. (2024). DPPH Measurements and Structure\u2014Activity Relationship Studies on the Antioxidant Capacity of Phenols. Antioxidants, 13.","DOI":"10.3390\/antiox13030309"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Edwards, A.A., and Alexander, B.D. (2017). UV-Visible Absorption Spectroscopy, Organic Applications. Encyclopedia of Spectroscopy and Spectrometry, Elsevier.","DOI":"10.1016\/B978-0-12-803224-4.00013-3"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1126","DOI":"10.1107\/S0021889810030499","article-title":"Fityk: A General-Purpose Peak Fitting Program","volume":"43","author":"Wojdyr","year":"2010","journal-title":"J. Appl. Crystallogr."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1002\/pca.3178","article-title":"Data Fusion-based Discovery (DAFdiscovery) Pipeline to Aid Compound Annotation and Bioactive Compound Discovery across Diverse Spectral Data","volume":"34","author":"Borges","year":"2023","journal-title":"Phytochem. Anal."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1282","DOI":"10.1021\/ac048630x","article-title":"Statistical Total Correlation Spectroscopy: An Exploratory Approach for Latent Biomarker Identification from Metabolic 1H NMR Data Sets","volume":"77","author":"Cloarec","year":"2005","journal-title":"Anal. Chem."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"594","DOI":"10.1002\/cem.1187","article-title":"CV-ANOVA for Significance Testing of PLS and OPLS\u00ae Models","volume":"22","author":"Eriksson","year":"2008","journal-title":"J. Chemom."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"981","DOI":"10.2307\/41703490","article-title":"Does PLS Have Advantages for Small Sample Size or Non-Normal Data?","volume":"36","author":"Goodhue","year":"2012","journal-title":"Manag. Inf. Syst. Q."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1002\/cem.695","article-title":"Orthogonal Projections to Latent Structures (O-PLS)","volume":"16","author":"Trygg","year":"2002","journal-title":"J. Chemom."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1002\/minf.201200158","article-title":"Orthogonal PLS (OPLS) Modeling for Improved Analysis and Interpretation in Drug Design","volume":"31","author":"Eriksson","year":"2012","journal-title":"Mol. Inform."},{"key":"ref_47","first-page":"92","article-title":"Multivariate Analysis in Metabolomics","volume":"1","author":"Worley","year":"2012","journal-title":"Curr. Metabolomics"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1007\/s11696-021-01902-6","article-title":"Absorption Spectra of Coumarin and Its Derivatives","volume":"76","author":"Fatima","year":"2022","journal-title":"Chem. Pap."}],"container-title":["Molecules"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1420-3049\/29\/24\/6027\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:57:04Z","timestamp":1760115424000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1420-3049\/29\/24\/6027"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,20]]},"references-count":48,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["molecules29246027"],"URL":"https:\/\/doi.org\/10.3390\/molecules29246027","relation":{},"ISSN":["1420-3049"],"issn-type":[{"value":"1420-3049","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,20]]}}}