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DOI: 10.1055/a-2660-2042
Antimycobacterial Activities of Cryptolepis sanguinolenta, Lantana camara, Zanthoxylum leprieurii Modeled as a Function of Their Fingerprints for Active Compounds Identification
The authors express their gratitude to the VLIR-UOS and World Bank for their funding through the Global Minds Scholarship and the PHARMBIOTRAC-Africa Center of Excellence (ACEII), Mbarara University of Science and Technology, respectively. This study is part of the Ph.D. program that is funded by the World Bank and the Vrije Universiteit Brussel (VUB).

Abstract
There is a pressing need to discover novel anti-tuberculosis agents to combat emerging drug-resistant strains. Cryptolepis sanguinolenta, Lantana camara, and Zanthoxylum leprieurii have been identified as potential sources of anti-tuberculosis (TB) drug candidates. Previous studies have examined the metabolites and metabolic pathways in mycobacterial strains affected by methanolic extracts of these plants, but the specific active compounds responsible for the antimycobacterial activity, the effect on affected metabolites and metabolic pathways of mycobacterial cell cultures, remain unclear. Untargeted metabolic fingerprinting may help identify the active compounds. The objective of this study was to model the antimycobacterial activity of methanolic extracts of C. sanguinolenta, L. camara, and Z. leprieurii as a function of their UHPLC-MS fingerprints and determine whether specific peaks (compounds) in the fingerprints contributed significantly to the activity. In this study, fingerprints of 18 methanolic extracts from C. sanguinolenta roots, L. camara leaves, and Z. leprieurii stem barks were obtained with ultra-high-performance liquid chromatography–mass spectrometry (UHPLC-MS). The minimal inhibitory concentrations (MICs) of these extracts against a pan-sensitive M. tuberculosis strain were determined using a resazurin-based microdilution assay. Fingerprints were processed and analyzed using regions of interest–multivariate curve resolution (ROIMCR). Partial least squares (PLS) regression was employed to model the MICs. Potential active compounds, including cryptolepine (from C. sanguinolenta), verbascoside (from L. camara), and isofagaridine (from Z. leprieurii), were identified as antimycobacterial compounds. These compounds likely influence mycobacterial metabolic processes, including cell wall synthesis, protein production, nucleotide metabolism, and energy generation. Further investigations are required to validate our findings.
Keywords
untargeted metabolite fingerprinting - multivariate calibration - antimycobacterial phytochemicals and their mechanisms - Cryptolepis sanguinolenta (Apocynaceae) - Lantana camara (Verbenaceae) - Zanthoxylum leprieurii (Rutaceae)Supporting Information
- Ergänzendes Material
The supporting information shows the sequence of injections.
Publikationsverlauf
Eingereicht: 23. März 2025
Angenommen nach Revision: 27. Juni 2025
Artikel online veröffentlicht:
07. August 2025
© 2025. Thieme. All rights reserved.
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