HOME- Bryn Mawr Conference
- Workshops & Training
- 2010 Oxford (Discovery)
- 2010 Oxford (ADMET)
- Hardy, B
- Hardy, L
- Jeliazkova, N
- Judson, R
- Leahy, D
- Li, J
- Myatt, G
- Rydberg, P
- Tsaioun, K
- Wiseman, J
- Bursary Award
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- 2009 Oxford (Discovery)
- 2009 Oxford (ADMET)
- 2008 Oxford
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| About Patrik Rydberg (University of Copenhagen) |
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Dr. Patrik Rydberg is currently a post-doc at the department of medicinal chemistry at the University of Copenhagen in Denmark. He obtained his Ph.D. in 2007 from Lund University (Sweden) working in the area of computational chemistry, studying heme proteins with various computational methods. In 2007 he received the Alfred Benzon Investigator Fellowship, and since then he has worked on drug metabolism mediated by cytochromes P450. He has published 15 peer-reviewed papers and one book chapter. Recently he published the SMARTCyp software for P450 metabolism prediction.
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Using Computational Chemistry to Predict Drug Metabolism Mediated by Cytochromes P450
Patrik Rydberg (University of Copenhagen)
Almost all drug metabolism in phase I is caused by the cytochromes P450 enzyme family. These enzymes can oxidize almost any site on a molecule, and creates more hydrophilic products which the body can more easily excrete. The major reactions performed by P450s are hydroxylations, dealkylations, epoxidations, and heteroatom oxidations. The major challenges in predicting the metabolism mediated by this enzyme family is that the various isoforms in the family contribute to the metabolism of different drugs, they have flexible active sites of different shape, and the reaction is caused by an iron-containing heme molecule, making simple assumptions with regard to reactivity invalid in many cases.
Thus, there are multiple things that should be included in the perfect prediction method (which unfortunately does not exist yet): prediction of which isoform will contribute most to the metabolism of a specific drug, prediction of how the drug will bind in the active site in this isoform, what site on the drug will be oxidized, and prediction of what metabolite will be formed by this drug.
During the last decade many methods for the prediction of this metabolism have been developed, using various computational techniques. The binding can be modeled using docking, shape matching, pharmacophore models, and even molecular dynamics. The reactivity can be computed using quantum chemical methods, semi-empirical methods, or by fragment matching using pre-computed energies. Using statistical methods, one can also relate substrate properties to metabolites.
The various programs available make different approximations to overcome the challenges described above using one or combinations of several techniques and all have different limitations. Thus, the performance of the methods can vary quite a lot depending on dataset and application.
In the workshop the participants will learn how to identify potential metabolites, and how to design compounds to overcome potential drug development problems. The metabolism of drugs which are known to undergo P450 metabolism will be discussed and predicted using SMARTCyp. The advantages and limitations of different methods, how to choose methods, and how to combine them to get the best possible results will be discussed and tested using SMARTCyp and other available programs.
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