Martin Darius R, Ajmal Antoinette, Meyer Mervin, Madiehe Abram M
Nanobiotechnology Research Group, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa.
Department of Science, Technology and Innovation/TIA Nanotechnology Platform, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa.
In Silico Pharmacol. 2025 Jul 22;13(2):106. doi: 10.1007/s40203-025-00386-6. eCollection 2025.
In this study computational methods were used to explore the anti-inflammatory properties of () extracts; focusing on their activity against pro-inflammatory cytokine, interleukin-1 (IL-1). Molecular docking was performed on 18 phytoconstituents using AutoDock VinaXB. The study identified five compounds (CIDs 8122, 33934, 605626, 638072, 5363269) with high affinity for IL-1. Notably, CID 638072 demonstrated superior binding affinity compared to standard controls such as thalidomide. Pharmacokinetic and toxicity profiles were assessed using SwissADME and pkCSM which showed that all these compounds met acceptable criteria as promising anti-inflammatory agents. Molecular dynamics simulations with GROMACS (version 2019) confirmed the stability and interaction dynamics of these compounds, which support the docking results. The findings validate the traditional medicinal use of for the treatment of inflammation, suggesting that CID 638072 holds significant potential for further development into a natural anti-inflammatory therapeutic. This research provides clues for the therapeutic applications of , advancing the search for effective natural remedies for the treatment of inflammation. Further experimental validation is necessary to transition this study from computational predictions to clinical applications.
在本研究中，采用计算方法探索了（）提取物的抗炎特性；重点关注其对促炎细胞因子白细胞介素 -1（IL -1）的活性。使用AutoDock VinaXB对18种植物成分进行了分子对接。该研究确定了对IL -1具有高亲和力的五种化合物（化合物识别码8122、33934、605626、638072、5363269）。值得注意的是，与沙利度胺等标准对照相比，化合物识别码638072表现出卓越的结合亲和力。使用SwissADME和pkCSM评估了药代动力学和毒性概况，结果表明所有这些化合物均符合作为有前景的抗炎剂的可接受标准。使用GROMACS（2019版）进行的分子动力学模拟证实了这些化合物的稳定性和相互作用动力学，这支持了对接结果。这些发现验证了（）在传统医学中用于治疗炎症的用途，表明化合物识别码638072在进一步开发成为天然抗炎疗法方面具有巨大潜力。本研究为（）的治疗应用提供了线索，推动了寻找治疗炎症的有效天然药物的研究。要将本研究从计算预测转化为临床应用，还需要进一步的实验验证。
