ORIGINAL RESEARCH article
Front. Mol. Biosci.
Sec. Biological Modeling and Simulation
Volume 12 - 2025 | doi: 10.3389/fmolb.2025.1666360
Decoding the Anticancer and Biofilm-Inhibiting Efficacy of Adansonia digitata Using Experimental, AI-Powered, and Molecular Modeling Approaches
Provisionally accepted- 1Karpagam Academy of Higher Education, Coimbatore, India
- 2Alagappa University Department of Biotechnology, Karaikudi, India
- 3Chettinad Hospital and Research Institute, Kanchipuram, India
- 4Dr DY Patil Vidyapeeth University Dr DY Patil Dental College and Hospital, Pune, India
- 5Sri Venkateswara Dental College and Hospital, Thalambur, India
- 6Alagappa University, Karaikudi, India
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Adansonia digitata, commonly known as the Baobab tree, is a highly multifunctional species with significant cultural and economic value across various regions of Africa. This study aims to investigate the anticancer and cytotoxic properties of ethanol extract derived from A. digitata (ADEE) on MDA-MB-231 breast cancer cells, as well as its potential to inhibit biofilm formation. The study employs GNINA, a deep learning-based docking tool, to evaluate molecular interactions. This work integrates machine learning and molecular modeling methodologies, highlighting the potential of informatics-driven strategies to expedite the discovery of novel plant-based therapies. Fluorescence microscopy demonstrated that ADEE effectively inhibited biofilm formation and reduced cell viability at a concentration of 1.56 µg/mL. These findings suggest that ADEE disrupts quorum-sensing signaling pathways and compromises the structural integrity of the biofilm matrix. Further assessments of cytotoxicity revealed a dose-dependent reduction in cancer cell viability, highlighting the potent anticancer properties of ADEE. The study also confirmed the pro-apoptotic effects of ADEE through Hoechst and AO/EB staining techniques. Validation utilizing GNINA-based deep learning techniques demonstrated an enhanced binding affinity and pose stability of compounds derived from ADEE. Molecular dynamics simulations provided insights into the interactions of ADEE with pqsA and CK2, showing more favorable binding characteristics compared to the reference inhibitor. PCA/FEL analyses indicated stable conformations with significant interactions at critical residues. In summary, the phytocompounds identified in ADEE demonstrated enhanced binding affinity and structural stability, indicating promising therapeutic potential for targeting QS-regulated biofilm development and serving as potential anticancer agents.
Keywords: Adansonia digitata, MDA-MB-231, AI-Based Docking, Molecular Dynamics Simulation, and PCA/FEL analysis
Received: 15 Jul 2025; Accepted: 06 Oct 2025.
Copyright: © 2025 Pandi, Kathiresan, Kumar Subbaraj, Desai, Sekar and Kulanthaivel. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Langeswaran Kulanthaivel, dr.langeswaran@gmail.com
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.