A Comprehensive Review on AI-Driven Phytochemical Discovery and Insights in Herbal Research

HerbIntel is an AI-powered platform created to transform the way we find and decipher plant-derived medicalchemistry. Consequently, Herbintel uses next-gen data-driven method and AI algorithms to provide a comprehensive chemical composition of molecular structures found in plants. Today, HerbIntel integrates drug informatics with molecular network analysis to give us an inside view of plant-based compounds` electron density fields. This makes it possible to predict relevant compounds pharmacophores which can potentially be used in finding drugs. HerbIntel's project is mainly focused on building a complete phytochemical database and using machine learning models to forecast bioactivity or pharmaceutical attributes for the same. Evenup until now, no one has collected together such an entire list of those substances, But really, what will be of interest to experts today. Namely for scientists trying to discover new drugs- that means they are lost without maps as to which places are available to house their structures and for businesses involved in health care products.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-22
DOI
https://doi.org/10.5281/zenodo.15491924
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
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article

A Comprehensive Review on AI-Driven Phytochemical Discovery and Insights in Herbal Research

Zenodo (CERN European Organization for Nuclear Research)
Computational Drug Discovery Methods
article

A Comprehensive Review on AI-Driven Phytochemical Discovery and Insights in Herbal Research

article en

Abstract

HerbIntel is an AI-powered platform created to transform the way we find and decipher plant-derived medicalchemistry. Consequently, Herbintel uses next-gen data-driven method and AI algorithms to provide a comprehensive chemical composition of molecular structures found in plants. Today, HerbIntel integrates drug informatics with molecular network analysis to give us an inside view of plant-based compounds` electron density fields. This makes it possible to predict relevant compounds pharmacophores which can potentially be used in finding drugs. HerbIntel's project is mainly focused on building a complete phytochemical database and using machine learning models to forecast bioactivity or pharmaceutical attributes for the same. Evenup until now, no one has collected together such an entire list of those substances, But really, what will be of interest to experts today. Namely for scientists trying to discover new drugs- that means they are lost without maps as to which places are available to house their structures and for businesses involved in health care products.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 50%
Computational Drug Discovery Methods
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