Many of the health claims of herbal medicine bear fruit for the pharmaceutical industry, leading to new drugs that are more potent and more targeted than the original remedy. In Traditional Chinese medicine there are many health claims for the likes of Ginkgo biloba and many other remedies that might bear closer scrutiny. Now, pharmaceutical chemist David Barlow and colleagues Peter Hylands and Thomas Ehrman at King’s College London have undertaken the biggest study yet of the active ingredients in TCM and used an analytical system known as a multiple decision tree technique, called Random Forest, to unearth the root of the activity of the natural products in TCM.
Their study seems to vindicate many of the claims of TCM as well revealing several compounds that might be indicated for diseases and symptoms not treated with in the traditional system.
The team built a database containing well over 8000 compounds from 240 of the most commonly used TCM herbs and used a second database of almost 2600 known active plant chemicals and other natural products as a training set for the Random Forest computer algorithm. The team found that about 62% of the herbs they tested in silico against various drug targets (mostly enzymes associated with pathogens or problems in the body) contained candidate drug compounds that might be isolated for treating a single disease without the associated issues of a TCM approach. They also found that more than half of these compounds worked against at least two diseases and so might have multiple applications.
You can read more about this research today on SpectroscopyNOW news round up from David Bradley. I asked Barlow about the wider application of this research and he said it might be applied equally well to other databases. “The same methodology might also be applied in screening other similar databases, constructed, for example, with reference to herbs used in Ayurvedic medicine,” he said.