PreMetabo

PreMetabo predicts sites of metabolism and metabolite formation for xenobiotics by combining knowledge-based site-of-metabolism models and energy calculations for CYP2C9, CYP2C19, CYP2D6, CYP3A4, uridine 5'-diphosphoglucuronosyltransferase (UGT), and sulfotransferase (SULT).

Key Features:

• Knowledge-Based Prediction Models: Uses knowledge-based models to predict the site of metabolism (SOM) for CYP2C9, CYP2C19, CYP2D6, and CYP3A4 and to identify molecular interactions with these enzymes.
• Comprehensive Enzyme Coverage: Includes prediction models for uridine 5'-diphosphoglucuronosyltransferase (UGT) and sulfotransferase (SULT) to enable phase II metabolism predictions.
• Activation and Binding Energy Calculations: Calculates activation energy using the EaMEAD model and estimates binding energy via docking simulations to determine CYP SOM substrates.
• High Predictability and Validation Accuracy: Reports 72.5%–84.5% predictability for major metabolites in top-3 positions across four CYPs; internal validation accuracies of 93.94% for UGT and 80.68% for SULT substrate classification; external validation of 81% accuracy for 11 FDA-approved drugs.

Scientific Applications:

• Drug discovery: Supports drug discovery by predicting metabolic pathways and metabolite formation of new compounds.
• Safety and efficacy assessment: Identifies CYP inhibitors or substrates to assess potential drug–drug interactions, safety, and efficacy early in development.
• Personalized medicine: Facilitates personalized medicine by analyzing individual metabolic responses.

Methodology:

Employs knowledge-based SOM models, activation energy calculation via the EaMEAD model, docking-based binding energy calculations, and analysis of drug–enzyme interactions through computational simulations.