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Saraswata Ghrita各种提取物的气相色谱-串联质谱法和高分辨率液相色谱-四极杆飞行时间质谱分析:关于植物化学化合物的综合数据集

GC-MS/MS and HR-LCMS-QTOF analysis of various extracts of Saraswata Ghrita: A comprehensive dataset on phytochemical compounds.

作者信息

Badal Robin, Ranjan Shivani, Jha Sudhanshu Kumar, Kumar Lalan, Patel Ashok Kumar, Yadav Pramod, Prajapati Pradeep Kumar

机构信息

Department of Rasashastra & Bhaishajya Kalpana, All India Institute of Ayurveda, Sarita Vihar, New Delhi 110076, India.

Department of Electrical engineering, Indian Institute of Technology Delhi, New Delhi 110016, India.

出版信息

Data Brief. 2025 May 18;61:111675. doi: 10.1016/j.dib.2025.111675. eCollection 2025 Aug.

Abstract

This dataset provides a comprehensive phytochemical profile of , a classical Ayurvedic formulation traditionally used for cognitive enhancement. To capture its diverse bioactive constituents, three different extracts-methanol, hexane, and hexane-ethanol-were analyzed using Gas Chromatography-Mass Spectrometry (GC-MS/MS) and High-Resolution Liquid Chromatography-Mass Spectrometry-Quadrupole Time-of-Flight (HR-LCMS/MS-QTOF). The dataset includes volatile and semi-volatile compounds identified through GC-MS/MS, while HR-LCMS/MS-QTOF facilitates the characterization of non-volatile and polar metabolites. Advanced chromatographic and spectrometric techniques were employed, integrating mass spectrometric detection, retention time analysis, and cheminformatics-based compound classification. Spectral data were processed using multiple databases, ensuring accurate compound annotation. Additionally, key parameters such as molecular weight, chemical structure, base peak intensity, and ion fragmentation patterns were recorded to aid in structural elucidation. This dataset is structured for comparative metabolomics, quality control, and pharmacological exploration, offering a valuable reference for researchers investigating the phytochemical complexity of Ayurvedic formulations. The compiled raw data, including chromatograms, peak intensities, spectral fingerprints, and molecular fragmentations, are publicly available for further computational modeling and validation. The dataset can also support future drug discovery efforts, network pharmacology studies, and Ayurvedic formulation standardization, ensuring reproducibility and facilitating integrative research on traditional medicine.

摘要

该数据集提供了一种传统用于增强认知的经典阿育吠陀配方的全面植物化学概况。为了捕捉其多样的生物活性成分,使用气相色谱-质谱联用仪(GC-MS/MS)和高分辨率液相色谱-质谱联用仪-四极杆飞行时间质谱仪(HR-LCMS/MS-QTOF)对三种不同的提取物——甲醇、己烷和己烷-乙醇提取物进行了分析。该数据集包括通过GC-MS/MS鉴定出的挥发性和半挥发性化合物,而HR-LCMS/MS-QTOF有助于对非挥发性和极性代谢物进行表征。采用了先进的色谱和光谱技术,整合了质谱检测、保留时间分析和基于化学信息学的化合物分类。使用多个数据库对光谱数据进行处理,以确保化合物注释的准确性。此外,记录了分子量、化学结构、基峰强度和离子碎裂模式等关键参数,以辅助结构解析。该数据集的构建旨在用于比较代谢组学、质量控制和药理学探索,为研究阿育吠陀配方植物化学复杂性的研究人员提供了有价值的参考。汇编的原始数据,包括色谱图、峰强度、光谱指纹和分子碎裂信息,已公开提供,可供进一步的计算建模和验证使用。该数据集还可以支持未来的药物发现工作、网络药理学研究和阿育吠陀配方标准化,确保可重复性并促进对传统医学的综合研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65b7/12163143/51be18228c9e/gr1.jpg

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