Synergistic modulation of ABC transporter-mediated multidrug resistance by Kalanchoe laciniata (L.) DC. phytochemicals: integrative phytochemical profiling, network pharmacology, and molecular docking insights
Abstract
Kalanchoe laciniata (L.) DC. is an underexplored medicinal plant with promising anticancer potential. This study evaluated the phytochemical profile, antioxidant activity, and multidrug resistance (MDR) modulating effects of its methanolic extract (KLM), with emphasis on ABC transporter regulation. Soxhlet methanol extraction yielded the highest phenolic and tannin contents and exhibited strong antioxidant activity. GC-MS and LC-MS analyses identified bioactive flavonoids and phytosterols, including quercetin and kaempferol derivatives. Network pharmacology revealed key interactions with ABC transporters and hub genes such as AKT1 and TP53. Molecular docking and dynamics simulations demonstrated stable binding of KLM-derived flavonoids with BCRP, MRP1, and AKT1, supporting their role in MDR modulation. Functionally, KLM exhibited dose-dependent cytotoxicity against MDA-MB-231 breast cancer cells and showed strong synergy with doxorubicin. qPCR analysis further confirmed significant downregulation of AKT1, BCRP, and MRP1 expression following KLM treatment. Collectively, these findings indicate that K. laciniata phytochemicals may act as effective chemosensitizing agents to overcome ABC transporter-mediated drug resistance in breast cancer.
Read the paper
Related studies
- Quercetin Influences Quorum Sensing in Food Borne Bacteria: In-Vitro and In-Silico Evidence
- Phenolic-protein interactions: insight from in-silico analyses – a review
- In Silico Discovery of Candidate Drugs against Covid-19
- Neuropharmacological Effects of Quercetin: A Literature-Based Review
- In vitro and in silico anti-dengue activity of compounds obtained from Psidium guajava through bioprospecting
- Effect of Quercetin Rich Onion Extracts on Bacterial Quorum Sensing
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.