DiaNat-DB-v2: A Molecular Database of Antidiabetic Compounds from Medicinal Plants and Functional Foods

Diabetes mellitus continues to be a significant health problem worldwide, and effective strategies and resources for its prevention and treatment are needed. Here, we present DiaNat-DB-v2, a refined and expanded version of the compound database that incorporates newly identified antidiabetic compounds from medicinal plants. By incorporating food-derived compounds, DiaNat-DB-v2 bridges the gap between medicinal chemistry and functional food research, creating new opportunities for nutraceutical development, personalized dietary interventions, and drug discovery. A comprehensive analysis of structural content, diversity, chemical space coverage, and safety-related metrics revealed that the updated database exhibits minimal overlap with FDA-approved drugs and contains a large proportion of unique molecular scaffolds, underscoring its originality and complementarity. Furthermore, the database has high natural-product likeness, a low incidence of structural alerts, and moderate compliance with classical druglikeness criteria. Together, these findings emphasize the value of DiaNat-DB-v2 as a resource for both health-oriented compound discovery and nutrition-focused research. DiaNat-DB-v2 is freely accessible as Supporting Information.

Authors

Institutions

Publication Details

Journal
ACS Omega
Published
2025-11-24
DOI
https://doi.org/10.1021/acsomega.5c09685
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

DiaNat-DB-v2: A Molecular Database of Antidiabetic Compounds from Medicinal Plants and Functional Foods

Mehdi D. Davari, Berenice Ovalle‐Magallanes, Abraham Madariaga‐Mazón, Karina Martínez‐Mayorga et al.
ACS Omega
Computational Drug Discovery Methods
article

DiaNat-DB-v2: A Molecular Database of Antidiabetic Compounds from Medicinal Plants and Functional Foods

Mehdi D. Davari, Berenice Ovalle‐Magallanes, Abraham Madariaga‐Mazón, Karina Martínez‐Mayorga, David Ramírez‐Palma, José L. Medina‐Franco, Juan F. Avellaneda-Tamayo, Jimena García-Vázquez, Nancy De Jesús-Reyes
article en

Abstract

Diabetes mellitus continues to be a significant health problem worldwide, and effective strategies and resources for its prevention and treatment are needed. Here, we present DiaNat-DB-v2, a refined and expanded version of the compound database that incorporates newly identified antidiabetic compounds from medicinal plants. By incorporating food-derived compounds, DiaNat-DB-v2 bridges the gap between medicinal chemistry and functional food research, creating new opportunities for nutraceutical development, personalized dietary interventions, and drug discovery. A comprehensive analysis of structural content, diversity, chemical space coverage, and safety-related metrics revealed that the updated database exhibits minimal overlap with FDA-approved drugs and contains a large proportion of unique molecular scaffolds, underscoring its originality and complementarity. Furthermore, the database has high natural-product likeness, a low incidence of structural alerts, and moderate compliance with classical druglikeness criteria. Together, these findings emphasize the value of DiaNat-DB-v2 as a resource for both health-oriented compound discovery and nutrition-focused research. DiaNat-DB-v2 is freely accessible as Supporting Information.

ACS OmegaVol. 10(48)
Leibniz Institute of Plant Biochemistry (DE), Autonomous University of Yucatán (MX), Universidad Nacional Autónoma de México (MX)
Openalex Percentile: Top 63%
Computational Drug Discovery Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

DiaNat-DB-v2: A Molecular Database of Antidiabetic Compounds from Medicinal Plants and Functional Foods — Mehdi D. Davari, Berenice Ovalle‐Magallanes, et al. · ACS Omega (2025) | TGRS Research Map | TGRS