Integrated Translational Molecular Biology Unit (ITMBU), Department of Rog Nidan Evam Vikriti Vigyan (Pathology), All India Institute of Ayurveda, New Delhi, 110076, India.
Ayurinformatics Laboratory, Department of Kaumarabhritya (Pediatrics), All India Institute of Ayurveda, New Delhi, 110076, India.
Sci Rep. 2024 Oct 11;14(1):23795. doi: 10.1038/s41598-024-75059-z.
Breast Cancer (BC) is the most common cause of cancer-associated deaths in females worldwide. Despite advancements in BC treatment driven by extensive characterization of its molecular hallmarks, challenges such as drug resistance, tumor relapse, and metastasis persist. Therefore, there is an urgent need for alternative treatment approaches with multi-modal efficacy to overcome these hurdles. In this context, natural bioactives are increasingly recognized for their pivotal role as anti-cancer compounds. This study focuses on predicting molecular targets for key herbal phytoconstituents-gallic acid, piperine, quercetin, resveratrol, and beta-sitosterol-present in the polyherbal formulation, Krishnadi Churna. Using an in-silico network pharmacology model, key genes were identified and docked against these marker compounds and controls. Mammary carcinoma emerged as the most significant phenotype of the putative targets. Analysis of an online database revealed that out of 135 predicted targets, 134 were mutated in breast cancer patients. Notably, ESR1, CYP19A1, and EGFR were identified as key genes which are known to regulate the BC progression. Docking studies demonstrated that the herbal phytoconstituents had similar or better docking scores than positive controls for these key genes, with convincing protein-ligand interactions confirmed by molecular dynamics simulations, MM/GBSA and free energy landscape (FEL) analysis. Overall, this study highlights the predictive potential of herbal phytoconstituents in targeting BC genes, suggesting their promise as a basis for developing new therapeutic formulations for BC.
乳腺癌（BC）是全球女性癌症相关死亡的最常见原因。尽管由于对其分子特征的广泛描述而推动了 BC 治疗的进展，但仍然存在诸如耐药性、肿瘤复发和转移等挑战。因此，迫切需要具有多模式疗效的替代治疗方法来克服这些障碍。在这种情况下，天然生物活性物质因其作为抗癌化合物的关键作用而越来越受到关注。本研究专注于预测关键草药植物成分的分子靶标，这些成分包括存在于复方草药制剂 Krishnadi Churna 中的没食子酸、胡椒碱、槲皮素、白藜芦醇和β-谷甾醇。使用基于网络的药理学模型，鉴定了关键基因，并将其与这些标记化合物和对照物对接。乳腺癌是假定靶标中最显著的表型。对在线数据库的分析表明，在预测的 135 个靶标中，有 134 个在乳腺癌患者中发生了突变。值得注意的是，ESR1、CYP19A1 和 EGFR 被确定为关键基因，已知这些基因可调节 BC 的进展。对接研究表明，与阳性对照相比，草药植物成分对这些关键基因具有相似或更好的对接评分，通过分子动力学模拟、MM/GBSA 和自由能景观（FEL）分析证实了可靠的蛋白-配体相互作用。总体而言，本研究强调了草药植物成分在靶向 BC 基因方面的预测潜力，表明它们有望成为开发新的 BC 治疗制剂的基础。
