Validation of Model of Cytochrome P450 2D6:

An in Silico Tool for Predicting

Metabolism and Inhibition

Carol A. Kemp, Jack U. Flanagan, Annamaria J. van Eldik, Jean-Didier Mare´chal, C. Roland Wolf, Gordon C. K. Roberts,§ Mark J. I.

Paine & Michael J. Sutcliffe

J. Med. Chem. 2004

Cytochrome P450 (Cyp450)

• Group of oxidative enzymes

• Exits in all lineages

• Membrane protein (ER, mitochondria)

• Metabolite thousands of endogenous and exogenous compounds

Importance of Cyp 2D6

Oxidation of >50 drugs Inhibited by drugs

Cytochrome

P450 2D6

Analgesics

(pain killers)

Beta Blockers

(cardiovascular diseases)

Quinidine

(heart rhythm disturbance)

fluoxertine

(depression)

Research Goals

• Previous work: HM + docking position metabolism site above hemeTypical (basic nitrogen) substrates

• Screening a database for CYP2D6 inhibitors• Can 3D method improve over 2D approach• Asses model accuracy

Comparative Modeling of 2D6

FSSP = Fold classification & Secondary Structure Alignment (DALI)

Bacterial P450 Mammalian P450

Model Validation

Does a sequence fit a structure ?

1. Buried area

2. % side chain buried with polar atoms

3. Secondary structure

Errat

non covalently pairs interactions( CC, CN, CO, NN, NO, OO )

9 residue sliding window

Screened Available Databases

Ekins ( 21 compounds )

Strobl (30 compounds )

Docking Software: GOLD 2.0

•Genetic algorithm

•Full ligand flexibility partial protein flexibility

•Energy functions partly based on conformational and non-bonded contact information from the CSD

12 ring systems r2 = 0.561 ring system r2 = 0.36

Creating an Additional Dataset

NCI database (compounds tested for treating cancer)

Weight ~ Ekins & Strobl datasets

< 4 Ring Systems

Availability

33 Compunds

Basic Nitrogen & Aromatic Group

Consistency with known inhibition measurements

Cyp4502D6

Small Molecule

AMMC demethylase

InhibitionInhibition

AMMCEkins / Strobl

Predicting inhibition using Docking

Cutoffs: IC50 < 10 µM = inhibitor

-30 kJ/mol = predicted inhibitor

Predictions: 13 correct

7 false positives

Questions for discussion

1. Is the method applicable for large scale database scanning ?(~7 min CPU on a one processor Silicon Graphics R14)

2. Can substrate affinity be predicted with the same accuracy ?

3. Are positions reliable enough for predicting drug-drug interactions ?

Thank you for your attention