Computational approaches to predicting xenobiotic metabolism by the human gut microbiota

As experimental characterization of microbiome-mediated metabolism remains resource-intensive, computational prediction has emerged as an auxiliary strategy for comprehensive ADMET profiling.</p> <p>Based on a structured literature search up to 2026, this review evaluates key computational resources: 10 databases, 6 predictive algorithms, 1 genome-scale metabolic reconstruction platform, and 3 microbiome–metabolome integration models.

We analyze their specific strengths, limitations, and integration into drug discovery pipelines and personalized medicine scenarios.</p> <p>While current <i>in silico</i> tools robustly predict qualitative metabolic potential and responsible taxa, their application in physiologically based pharmacokinetic modeling is hindered by data limitations. Training datasets exhibit a profound bias toward isolated <i>in vitro</i> screening, alongside a critical lack of quantitative kinetic parameters.