A recent publication out from our lab.
A novel approach for the prediction of species-specific biotransformation of xenobiotic/drug molecules by the human gut microbiota
Abstract
The human gut microbiota is constituted of a diverse group of microbial
species harbouring an enormous metabolic potential, which can alter the
metabolism of orally administered drugs leading to
individual/population-specific differences in drug responses.
Considering the large heterogeneous pool of human gut bacteria and their
metabolic enzymes, investigation of species-specific contribution to
xenobiotic/drug metabolism by experimental studies is a challenging
task. Therefore, we have developed a novel computational approach to
predict the metabolic enzymes and gut bacterial species, which can
potentially carry out the biotransformation of a xenobiotic/drug
molecule. A substrate database was constructed for metabolic enzymes
from 491 available human gut bacteria. The structural properties
(fingerprints) from these substrates were extracted and used for the
development of random forest models, which displayed average accuracies
of up to 98.61% and 93.25% on cross-validation and blind set,
respectively. After the prediction of EC subclass, the specific
metabolic enzyme (EC) is identified using a molecular similarity search.
The performance was further evaluated on an independent set of
FDA-approved drugs and other clinically important molecules. To our
knowledge, this is the only available approach implemented as ‘DrugBug’
tool for the prediction of xenobiotic/drug metabolism by metabolic
enzymes of human gut microbiota.
Please explore and write back to me (ashoks773@gmail.com) in case of any problem. Comments are welcome.
