Computational analysis of antimicrobial phytochemicals from Bambusa vulgaris Schrad. ex J.C.Wendl.: Pharmacokinetics, toxicity, and molecular docking
Antimicrobial resistance is a worldwide health concern that requires immediate attention. The abundance of bioactive phytochemicals with a variety of structures found in natural products has made them a promising source for drug discovery. Large numbers of bioactive phytochemicals associated with antimicrobial activity have been found in the common bamboo, Bambusa vulgaris, such as phenolic acid, polyphenols, flavonoids and sterols. Although there have been some reports about the antimicrobial activity of B. vulgaris and its bioactive phytochemicals, there is currently a lack of research regarding the pharmacokinetics and toxicity of these phytochemicals. Determining the pharmacokinetics and toxicity of the phytochemicals is crucial to ensure safety, minimize the toxicity, identify the bioavailability, and support clinical research and regulatory approval of B. vulgaris as a source of antimicrobial agents. Here, computational analyses were performed on 17 phytochemicals that were isolated from B. vulgaris and taken from the scientific literature. The findings demonstrate that 12 of the 17 phytochemicals complied with Veber's rule and Lipinski's rule of five, indicating their good oral bioavailability and drug-likeness. Only half of the filtered phytochemicals, p-coumaric acid, ferulic acid, caffeic acid, protocatechuic acid, gallic acid and vanillic acid, were found to be non-toxic after further testing for potential toxicity. Molecular docking simulations were then performed, and it is evident that these six phytochemicals may thermodynamically bind to selected microbial proteins, with hydrophobic interactions predominating. p-coumaric acid had the strongest affinity for binding to all three microbial proteins: S. aureus DNA gyrase A (PDB: 2XCT), S. aureus DNA gyrase B (PDB: 3G75), and secreted aspartic protease (PDB ID: 1ZAP).
Authors
- Chun Hoe Tan (ORCID: https://orcid.org/0000-0002-1730-6650)
- Sandeep Poddar (ORCID: https://orcid.org/0000-0001-9771-877X)
- Asita Elengoe (ORCID: https://orcid.org/0000-0003-3582-4846)
Publication Details
- Journal
- Advances in Bamboo Science
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1016/j.bamboo.2025.100157
- Citations
- 5
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 7.52