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

This dataset provides a comprehensive phytochemical profile of <i>Saraswata Ghrita</i>, 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.

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Publication Details

Journal
Data in Brief
Published
2025-05-18
DOI
https://doi.org/10.1016/j.dib.2025.111675
Citations
10
Primary Topic
Medicinal Plants and Neuroprotection
Type
article
Field-Weighted Citation Impact
23.81
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article

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

Robin Badal, Lalan Kumar, Ashok Kumar Patel, PK Prajapati et al.
10 citations
Data in Brief
Medicinal Plants and Neuroprotection
23.81
article

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

Robin Badal, Lalan Kumar, Ashok Kumar Patel, PK Prajapati, Pramod Yadav, Subodh Ranjan, Sudhanshu Kumar Jha
article en
10 citations

Abstract

This dataset provides a comprehensive phytochemical profile of <i>Saraswata Ghrita</i>, 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.

Data in BriefVol. 61
National Institute of Ayurveda (IN), Ministry of AYUSH (IN), Dr. Sarvepalli Radhakrishnan Rajasthan Ayurved University (IN), Indian Institute of Technology Delhi (IN)
Zero hunger
Openalex Percentile: Top 0%
Medicinal Plants and Neuroprotection
23.81
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