GRAYU: graph-based database integrating Ayurvedic formulations, medicinal plants, phytochemicals and diseases

TL;DR

GRAYU is a database connecting traditional Ayurvedic formulations, plants, phytochemicals, and diseases to support drug discovery and research.

Contribution

GRAYU introduces a structured, graph-based database integrating traditional Ayurvedic knowledge with modern computational frameworks.

Findings

GRAYU links 1,039 formulations to 12,743 plants, 129,542 phytochemicals, and 13,480 diseases.

Applications include phytochemical analogs, plant substitution, and disease-network analysis.

The database supports hypothesis generation and exploration of bio-associations from traditional medicine.

Abstract

The translation of India's extensive traditional knowledge on indigenous medicinal plants into modern therapeutic solutions is contingent upon a systematic framework. While traditional Indian medicine offers a rich source of therapeutic leads, this knowledge is often not structured for modern computational analysis, creating a barrier to systematic drug discovery.

To this end, we present GRAYU, a curated and comprehensive online database that integrates data across multiple categories, connecting 1,039 traditional formulations to 12,743 indigenous plants, 129,542 phytochemicals, and 13,480 indicated diseases.

GRAYU provides insights into 1,370,257 plant-phytochemical, 116,531 plant-disease, 2,389 plant-formulation, and 4,087 formulation-disease associations. We show potential applications on phytochemical analogs, sustainable plant substitution, and disease-network analysis, highlighting the potential of integrative graphs to decode shared molecular signatures and therapeutic networks across traditional Ayurvedic formulations.

GRAYU represents a user-friendly resource for researchers to investigate complex bio-associations and formulate novel therapeutic hypotheses, with insights from traditional Indian medicine. GRAYU organises reported associations and computational relationships and can hint at mechanistic causality or biological activity; however, all outputs require contextual interpretation and further experimental validation. The database is available at https://caps.ncbs.res.in/GRAYU/.

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