PREDICTION OF PHASE I AND PHASE II METABOLISM
June 2026, ISSX 16th European Meeting
Tommaso Palomba1,2, Ludovico Venturi1,2, Massimo Baroni1, Paolo Benedetti1, Gabriele Cruciani1,2,3
1Mass Analytica, S.L. Sant Cugat del Vallès, Spain; 2Molecular Discovery Ltd, Kinetic Business Centre, Borehamwood, UK; 3Department of Chemistry, Biology, and Biotechnology, University of Perugia, Italy
Abstract
Many drugs are metabolized in the human body to form metabolites for elimination. This metabolism is categorized into two classes of reactions. Phase I reactions are mediated by Cytochrome P450 enzymes, in addition to approximately thirty other enzymes. An additional twenty other enzymes are involved in Phase II reactions, which often result in conjugation products.
While the cytochrome P450 enzymes have long been studied, there is a growing need to better understand the role of non-CYP enzymes in drug metabolism. To facilitate this, we developed MetaSite 7 to provide the prediction of drug metabolism using 23 non-CYP Phase I enzymes including eight families and their related isoforms. Twenty enzymes, including 12 different families, responsible for Phase II reactions were also considered.
The prediction determines the probability of a molecule to be a substrate for each enzyme by identifying reactive atoms in the molecule structure. In MetaSite 7, we used the enzyme’s 3D structure to identify reactive atoms of the molecule which may be exposed to the cofactor or active binding site of the enzyme. The GRID force field is used to calculate flexible interaction fields between the catalytic residues of the enzyme and the molecule.
Multiple docking poses are considered, and the energy contributions are summed. The poses are ranked, and the lowest energy pose is used to generate a [1,2,3]This prediction can be repeated for each of the enzymes in MetaSite 7, resulting in a more comprehensive view of the site of metabolism (SOM) for both Phase I and Phase II enzymes.
Furthermore, the predictions may be combined by subjecting the potential first-generation metabolites to further predictions, allowing for a more complete view of second-generation metabolites.
In conclusion, we utilized the 3D structures of the different CYP isoforms and 43 non-CYP enzymes to predict both Phase I and Phase II metabolism, along with the probability of a drug molecule to be a substrate for each enzyme. These predictions provide an increased understanding of the potential metabolic pathway in the human body.
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