Malaria Research Group, Department of Biosciences and Bioengineering, Indian Institute of Technology-Guwahati, Guwahati, Assam, India.
J Biomol Struct Dyn. 2024 May;42(8):4297-4312. doi: 10.1080/07391102.2023.2220036. Epub 2023 Jun 8.
Phytochemicals are bioactive agents present in medicinal plants with therapeutic values. Phytochemicals isolated from plants target multiple cellular processes. In the current work, we have used fractionation techniques to identify 13 bioactive polyphenols in ayurvedic medicine Haritaki Churna. Employing the advanced spectroscopic and fractionation, structure of bioactive polyphenols was determined. Blasting the phytochemical structure allow us to identify a total of 469 protein targets from Drug bank and Binding DB. Phytochemicals with their protein targets from Drug bank was used to create a phytochemical-protein network comprising of 394 nodes and 1023 edges. It highlights the extensive cross-talk between protein target corresponding to different phytochemicals. Analysis of protein targets from Binding data bank gives a network comprised of 143 nodes and 275 edges. Taking the data together from Drug bank and binding data, seven most prominent drug targets (HSP90AA1, c-Src kinase, EGFR, Akt1, EGFR, AR, and ESR-α) were found to be target of the phytochemicals. Molecular modelling and docking experiment indicate that phytochemicals are fitting nicely into active site of the target proteins. The binding energy of the phytochemicals were better than the inhibitors of these protein targets. The strength and stability of the protein ligand complexes were further confirmed using molecular dynamic simulation studies. Further, the ADMET profiles of phytochemicals extracted from HCAE suggests that they can be potential drug targets. The phytochemical cross-talk was further proven by choosing c-Src as a model. HCAE down regulated c-Src and its downstream protein targets such as Akt1, cyclin D1 and vimentin. Hence, network analysis followed by molecular docking, molecular dynamics simulation and in-vitro studies clearly highlight the role of protein network and subsequent selection of drug candidate based on network pharmacology.Communicated by Ramaswamy H. Sarma.
植物化学物质是药用植物中具有治疗价值的生物活性物质。从植物中分离出的植物化学物质针对多种细胞过程。在目前的工作中，我们使用了分馏技术来鉴定印度草药 Haritaki Churna 中的 13 种生物活性多酚。采用先进的光谱和分馏技术，确定了生物活性多酚的结构。对植物化学物质的结构进行爆破，使我们能够从 Drug bank 和 Binding DB 中识别出总共 469 个蛋白质靶标。将来自 Drug bank 的植物化学物质及其蛋白质靶标用于创建一个包含 394 个节点和 1023 个边的植物化学物质-蛋白质网络。它突出了不同植物化学物质对应的蛋白质靶标之间的广泛交流。来自 Binding 数据库的蛋白质靶标分析得到了一个由 143 个节点和 275 个边组成的网络。将来自 Drug bank 和 Binding data 的数据结合在一起，发现了七个最突出的药物靶标（HSP90AA1、c-Src 激酶、EGFR、Akt1、EGFR、AR 和 ESR-α）是植物化学物质的靶标。分子建模和对接实验表明，植物化学物质很好地适合于靶蛋白的活性部位。植物化学物质的结合能优于这些蛋白质靶标的抑制剂。使用分子动力学模拟研究进一步证实了蛋白质配体复合物的强度和稳定性。此外，从 HCAE 中提取的植物化学物质的 ADMET 谱表明它们可能是潜在的药物靶标。通过选择 c-Src 作为模型，进一步证明了植物化学物质的相互作用。HCAE 下调了 c-Src 及其下游蛋白质靶标，如 Akt1、cyclin D1 和 vimentin。因此，网络分析后进行分子对接、分子动力学模拟和体外研究清楚地突出了蛋白质网络的作用，并随后根据网络药理学选择药物候选物。由 Ramaswamy H. Sarma 传达。
