Molecular Docking, Drug‐Likeness, and Toxicity Prediction of Coldenia procumbens L. Chemical Constituents Against Tumor Necrosis Factor‐Alpha
ABSTRACT Tumor necrosis factor‐alpha (TNF‐α) is a pivotal cytokine produced by various immune cells, playing a key role in inflammation, autoimmune disorders, and anti‐cancer responses. Coldenia procumbens L. has long been valued in traditional medicine for treating conditions such as rheumatoid swelling, boils, pain, non‐healing abscesses, wounds, menorrhagia, and snake bites. In this study, molecular docking simulations were employed to assess the TNF‐α inhibitory potential of 110 compounds derived from C. procumbens L. The findings identified six promising inhibitors of TNF‐α, namely α‐amyrin, oleanolic acid, β‐stigmasterol, chlorogenin diacetate, stigmasta‐3,5‐diene, and 2,4‐bis(1‐phenylethyl) phenol, based on their binding affinities compared to the reference inhibitor SPD‐304. Further toxicity predictions revealed that α‐amyrin, chlorogenin diacetate, and 2,4‐bis(1‐phenylethyl) phenol exhibit low toxicity and are considered safe, with LD50 values of 70 000, 5000, and 2510, respectively. Remarkably, chlorogenin diacetate was shown to have no hepatotoxic, neurotoxic, nephrotoxic, respiratory, or cardiotoxic effects. In terms of drug‐likeness, most compounds adhered to Veber's and Lipinski's rules, except for chlorogenin diacetate, which did not conform to Lipinski's rule. So, these potential compounds represent a promising avenue for future in vitro and in vivo studies, with the potential to lead to the development of novel anti‐inflammatory drugs.
Authors
- Dinh Thi Huyen Trang
- Nguyen Xuan Ha (ORCID: https://orcid.org/0000-0002-8779-256X)
- Phan Thi Thuy (ORCID: https://orcid.org/0000-0002-4571-5953)
- Ngu Thi Tra Giang
- Nguyen Thi Thuy Tram
- Tran Thi Ngoc Mai
Institutions
- Vinh University (VN)
- Vietnam Academy of Science and Technology (VN)
Publication Details
- Journal
- Vietnam Journal of Chemistry
- Published
- 2026-08-20
- DOI
- https://doi.org/10.1002/vjch.70168
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00