Screening Chinese herbs
With diminishing pipelines and the dramatic growth of the East Asian pharmaceutical industry, interest in natural products and traditional Chinese medicines
LONDON—With diminishing pipelines and the dramatic growth of the East Asian pharmaceutical industry, interest in natural products and traditional Chinese medicines (TCMs) as a source of novel therapeutics is increasing. With this in mind, researchers at King's College London undertook a systematic analysis of the TCM landscape using informatics tools.
In the first of two papers in the Journal of Chemical Information and Modeling, the researchers scanned primary and secondary literature sources to establish two databases of information about TCMs. As they explained, basic biological and chemical data about these herbs exist in a variety of locations but not in formats easily parsed for data mining and molecular modeling.
The Chinese Herb Chemistry Database (CHCD) examines approximately 7000 unique compounds identified in 240 species of Chinese herbs, including information on compound structure, trivial and systematic names, compound class and skeletal type, chirality, CAS Registry number, pharmacology and toxicology, as well as other data. The Bioactive Plant Compounds Database (BPCD) meanwhile also includes information about molecular targets, ligand type, inhibition data, and botanical species.
In the second paper, the researchers used ligand-based virtual screening to identify potential molecular targets of an array of herbal compounds. They relied on an ensemble decision tree algorithm, Random Forest, to highlight similarities between known target ligands and herbal compounds.
Screening more than 8000 compounds from 240 herb species, the researchers noted that most of the compounds were 2- to 3-orders of magnitude less potent than typical pharmaceuticals (i.e., IC50 1-100 µM). At the same time, they found that more than 60 percent of the herbs offered hits for one or more targets, and that half of these hit two or more targets. They then used the literature to check their results and found evidence to support 83 herb-target predictions, suggesting the system works well.
"What this work shows is that the relatively new science of molecular informatics may have much to offer in furthering our understanding of how herbs work, and in developing new, and perhaps safer, medicines based on nature's own resources," says co-author Dr. Tom Ehrman.
