Predicting Regioselectivityand Lability of Cytochrome P450 Metabolism using Quantum Mechanical Simulations
Poster Sep 23, 2015
Tyzack, Nicholas Foster, Peter Hunt, Matthew Segall
Many computational methods have been developed that predict the regioselectivity of metabolism by drug metabolising isoforms of the Cytochrome P450 class of enzymes (P450) [1-5]. Here we describe recent developments to a method for predicting P450 metabolism that combines quantum mechanical (QM) simulations to estimate the reactivity of potential sites of metabolism on a compound with a ligand-based approach to account for the effects of orientation and steric constraints due to the binding pockets of different P450 isoforms. These new developments include modeling reaction pathways for epoxidations and developing new models for different P450 isoforms.
While valuable, predicting the relative proportion of metabolite formation at different sites on a compound is only a partial solution to designing more stable compounds. The advantage of a quantum mechanical approach is that it provides a quantitative estimate of the reactivity of each site, from which additional information can be derived regarding the vulnerability of each site to metabolism in absolute terms. One such measurement is the site lability, as calculated by StarDrop™ , which is a measure of the efficiency of the product formation step. This is an important factor influencing the rate of metabolism and we will illustrate how this provides valuable guidance regarding the potential to redesign compounds to overcome issues due to rapid P450 metabolism.
A New Method for Analyzing MSe/All Ions Fragmentation in Xenobiotic Metabolism StudiesPoster
During early drug discovery, the study of metabolism plays an essential role in determining which drug candidates move forward into development and later stages. As an alternative to traditional Data Dependent Acquisition (DDA), the use of MSE/All Ions Fragmentation (AIF) has become common in metabolite identification workflows for the analysis of metabolic hot spots. Here we present a solution for analysis of MSE/AlF in metID studies.READ MORE
Exploiting Polypharmacology in Precision Oncology: Identification of Differential Kinase Off-targets Among Clinical PARP InhibitorsPoster
Can we use computational methods to identify previously unknown off-targets of PARP inhibitors that can explain their observed differences?READ MORE
Bioluminescent Assay for GTPases Allows Measurement of GTPase, GAP and GEF ActivitiesPoster
We have developed a homogenous bioluminescent assay (GTPase-Glo) system to analyze these proteins in a simple, convenient “add-mix-read” format.READ MORE