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Harnessing the Potential of Carotenoids for Cancer Therapy: An Integrated Machine Learning and MST Based Approach.

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Τίτλος: Harnessing the Potential of Carotenoids for Cancer Therapy: An Integrated Machine Learning and MST Based Approach.
Συγγραφείς: Varghese R; School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India., Deb KS; School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India., Pal K; School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India., Jonnalagadda A; School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India., Cherukuri AK; School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India., Dawood M; Department of Pharmaceutical Biology, Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg University, Mainz, Germany., Boulos JC; Department of Pharmaceutical Biology, Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg University, Mainz, Germany., Efferth T; Department of Pharmaceutical Biology, Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg University, Mainz, Germany., Ramamoorthy S; School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
Πηγή: Phytotherapy research : PTR [Phytother Res] 2025 Sep; Vol. 39 (9), pp. 4156-4170. Date of Electronic Publication: 2025 Aug 04.
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Wiley Country of Publication: England NLM ID: 8904486 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1099-1573 (Electronic) Linking ISSN: 0951418X NLM ISO Abbreviation: Phytother Res Subsets: MEDLINE
Imprint Name(s): Publication: : Chichester : Wiley
Original Publication: London : Heyden & Son, c1987-
Ιατρικοί όροι (MeSH): Carotenoids*/pharmacology , Carotenoids*/chemistry , Neoplasms*/drug therapy , Receptor Protein-Tyrosine Kinases*/antagonists & inhibitors , Antineoplastic Agents, Phytogenic*/pharmacology , Machine Learning*, Protein Kinase Inhibitors/pharmacology ; Molecular Docking Simulation ; Humans
Περίληψη: Receptor tyrosine kinases (RTKs) are high-affinity membrane-anchored receptors involved in cellular communication via various ligands and manage numerous biological processes such as cell growth, differentiation, and metabolism. However, dysregulation of RTKs is a key instigating factor in the development of a vast array of cancers. Carotenoids are a major family of secondary plant metabolites known for their anti-cancer activities in various cancer models by targeting several molecular intermediates. We aimed to decipher the potential carotenoids as RTK inhibitors through an integrated workflow of in silico approaches and in vitro microscale thermophoresis. The kinase domains of nine RTKs were subjected to molecular docking with potential carotenoids, and the best-scoring carotenoids were selected. The molecular interactions of the best-scoring carotenoids and respective RTKs were validated through dynamics simulation. The selected carotenoid candidates were further validated through comparative analysis with clinically established drugs using various machine learning algorithms to establish the drug likeliness. Microscale thermophoresis was performed to prove the interaction of the best-scoring carotenoid with recombinant PDGFRA and VEGFR2 in vitro. The following five receptors and respective carotenoids were recognized through docking, MDS, and ML analysis: EGFR-fucoxanthin, FGFR2-peridinin, VEGFR2-canthaxanthin, PDGFRA-canthaxanthin, and ALK-crocin. MST experiments further underlined the high binding affinity of canthaxanthin with the targeted RTKs, underlining the possibilities of plant-based chemotherapy. Interestingly, carotenoids were recognized as potential plant-based alternatives for conventional drugs in RTK-targeted cancer therapy via an innovative ML-assisted drug discovery approach, and they provide novel insights into the discovery of phytochemicals as cancer drugs.
(© 2025 John Wiley & Sons Ltd.)
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Contributed Indexing: Keywords: cancer; canthaxanthin; carotenoids; machine learning; phytochemicals; receptor tyrosine kinases
Substance Nomenclature: 36-88-4 (Carotenoids)
EC 2.7.10.1 (Receptor Protein-Tyrosine Kinases)
0 (Antineoplastic Agents, Phytogenic)
0 (Protein Kinase Inhibitors)
Entry Date(s): Date Created: 20250805 Date Completed: 20250911 Latest Revision: 20250911
Update Code: 20260130
DOI: 10.1002/ptr.70064
PMID: 40760729
Βάση Δεδομένων: MEDLINE
Περιγραφή
ISSN:1099-1573
DOI:10.1002/ptr.70064