Enzymologie : aspects fondamentaux, passé et présent

Pr Michèle Reboud-Ravaux

UMR 8256 - Institut de Biologie Paris-Seine

Université Pierre et Marie Curie (UPMC)

michele.reboud@upmc.fr

Cours Franco-Québécois d’Enzymologie AvancéeEnzymologie Moléculaire & Mécanistique

UE 5EV107 (UPMC)

& BMC 6225 (Université de Montréal)

23 septembre 2016

PLAN DE L’EXPOSE

Efficacité

ENZYME

Eléments d’analyse basés sur le modèle de Michaelis

Les enzymes, importantes cibles thérapeutiques :

pourquoi?

Les caractéristiques de l’action enzymatique

L’apport de l’enzymologie de la molécule unique

0Affinité

0Fonctionnement régulé

0

Spécificité mais aussi

Promiscuité

Pourquoi les enzymes sont-elles des cibles thérapeutiques ?

Enzymes 47%

Protéines G couplées aux récepteurs 30%

Canaux ioniques 7%

Autres récepteurs 2%

Récepteurs nucléaires 2%

Divers 1%

Intégrines 1%

ADN 1%

Cibles biochimiques des médicaments(adapté de Hopkins et Groom, 2002, Nature Rev. Drug Discov., 1, 727).

Les enzymes demeurent des cibles essentielles

Représentent toujours 50-75% des efforts recherche pour

découvrir de nouveaux médicaments.

Aspirine

Rivatigmine BortezomibOseltamivir

CaptoprilLovastatine

Fluorouracile

Acyclovir

Méthotrexate

Raltegravir

Tipranavir

AZT (zidovudine)

Attractiveness of enzymes as drug targets

- Essentiality of their activity.

- By their nature (proteins) and catalytic mechanism, are

highly amenable to inhibition by small molecules :

enzymes are primary targets.

- Related enzymes to primary targets must be studied to

avoid unwanted side effects.

Example: HIV protease inhibitors/ human aspartic proteases

(renin, pepsin, cathepsins D and E).

- Enzymes are implicated in drug metabolism and

pharmacokinetics that drive metabolic transformations.

Critical for the drug discovery and development process:

. a good understanding of the structure and mechanisms of action of enzymes

. quantitative studies of enzyme-ligand interactions.

Adapted from R. A. Copeland. Evaluation of Enzyme Inhibitors in Drug Discovery (2013)

- Involved in prodrug conversion to active

species.

- Enzymes form the basis of a number of

diagnostic tests that are in current clinical use.

- Some enzymes are used as therapeutic agents:

rt-PA (recombinant tissue plasminogen activator),

ingestion of pancreatic enzymes.

- Genes that encode specific enzymes are also

potential therapeutic agents for enzyme-based

therapies.

The chosen microstate is stabilized leading to a shift in the distribution of microstates towards the

deeper potential well (i.e. lower potential energy) of the preferred microstate.

Its degree of stabilization is directly related to what is called the ‘affinity’ of the ligand for this state.

The structure of the free enzyme and enzyme ligand-complexes is dynamic:

a manifold conformational substates, or microstates, that are interconvertible.

Po

ten

tia

l e

nerg

y

Microstate

Enzyme Complex ES

Microstate

Enzymes are dynamic entities

(conformational fluctuations)

Po

ten

tia

l e

nerg

y

Unique opportunity

for interaction

A ligand binds specifically to

a specific microstate

(best complementarity

between pocket and ligand)

Conformational fluctuations can be exploited for drug interactions:

large molecular diversity for the ligands of an enzyme

*

The Henri-Michaelis-Menten equation

See Deichman et al. 2014, FEBS J, 281, 426

v Vmax [S]

[S]KM

kcat[E][S]

[S]KM

Victor Henri

Leonor MichaelisCornish-Bowden 2014, FEBS J, 587, 2715

Maud Leonora Menten

Citations to Michaelis and Menten’s paper of 1913

. Henri V (1902) Théorie générale de l’action de quelques diastases, C. R. Hebd. Séances Acad Sci. 153, 916-919;

(1903) Lois générales de l’action des diastases, Herman.

. Michaelis L & Menten M. L. (1913) Kinetik der Invertinwirkung, Biochem. Z. 49, 333-369.

Characterization of enzymatic reactions

Inhibition

6679

Activation

195

After Mc Donal & Tipton 2014, FEBS J, 281, 583

Michaelis-

Menten

18594

Kinetic data statistics in SABIO-RK

Inhibition

6,679

Activation

195

Michaelis-

Menten

18,594

Hill cooperativity

1,702

Number of parameters Distribution of kinetic law types

(number of database entries)

Km

34,485

kcat

17,611

Vmax

13,237

kcat/Km

13,237

Ki

6,775

Modèle

michaélien

Efficacité : kcat & kcat/KM

Acétylcholinestérase : kcat = 25.000 s-1

2

+

Choline

AchE

Ach

AchE + Acétylcholine (Ach)

Acide acétique

E + S ES E-S’

P1

P2

Non covalent Covalent

E + P2

P1

kcat = VM/[E]0 (s-1)Anhydrase carbonique : kcat = 1.00.000 s-1

kcat (temps-1) = activité moléculaire spécifique ou nombre d’actes catalytiques/unité de

temps/molécule d’enzyme ou ‘turnover number’

k1

k-1k2

k3

kcat k2k3

k2 k3

kcat/KM( temps-1. M-1) = efficacité ‘vraie’ ou efficacité dynamique

Relié à KM

Acetyl-enzyme

E + S ES E+Pk2k1

k-1

kcat = k2

[S]0 < < KM [S]0 = KM [S]0 >> KM

[E]0 << [S]0

[S]2 > [S]1[S]1[S]3 > [S]2

Enzyme saturée

vi = Vmax/2 vi = Vmax

Affinité

1/KM = AFFINITE APPARENTE de l’enzyme pour son substrat

Plus KM est faible, plus l’enzyme aura ‘de l’affinité’ pour son substrat

Le modèle de Michaelis : sens physique et schéma cinétique

Equation de Henri-Michaelis-Menten

[P]

Temps (min)

[S]0

v

vi1

vi2

vi3

vi4

vi5 = vi

6 = Vmax

[E]0 << [S]0

Etat stationnaire pour les formes enzymatiques

E + S ES E+Pk2k1

k-1

0

0.2

0.4

0.6

0.8

1

1.2

0 5 10 15 20 25

vi

vi1

vi2

vi3

vi4

vi5 vi

6

[S]0

Schéma cinétique minimum

Vmax

Vmax/2

(Ici, kcat = k2)

v Vmax [S]

[S]KM

kcat[E][S]

[S]KM

Vmax = kcat [E]0a

v

e

c

Etape physique

de liaisonEtape chimique

de catalyse

KM

Vi = vitesse initiale

KM = (k-1 + k2)/k1

Saturation de

l’enzyme

Various data types that may be used to estimate the kinetic parameters

obtained from the classical Michaelis–Menten equation.

After Tummler et al. 2014, FEBS J, 281, 549

Estimation of kinetic parameters

Flux measurements

- Nutrient

uptake rates

- 13C-labeling

(steady-state

and dynamics)

Enzyme concentrations

-- Quantitive

proteomics

- Qualitative

proteomics

- Expression data

Kinetic parameters

Substrate concentrations

- In vitro assays

- Biacore

- Existing models

- Structure

calculations

- Metabolomics

(steady-state and

dynamic)

- Proteomics for

signaling systems

v [E]0kcat[S]

Km [S]

v [E ]0 kcat[S]

Km [S]

Towards single-molecule enzymology

But both enzyme

conformation and catalytic

activity fluctuate with time

. Are they methods to measure

precisely this stochasticity?

. Is the Michaelis model still valid ?

11-mer

TRAP

12-mer

TRAP

Matsunada et al. PLOS One , 2012, é50011

Enzymologie de la molécule unique

Mesure directe de la distribution en fonction du temps d’une propriété moléculaire

pour une seule molécule et pour un temps long (plutôt que mesure pour la moyenne d’un

ensemble de molécules) : construction d’histogrammes d’une variable particulière et analyse

statistique des données.

L’analyse statistique des trajectoires d’une seule molécule donne une information

dynamique détaillée sur le fonctionnement de cette molécule.

Possibilité de suivre des processus biochimiques en temps réel et de capturer des

intermédiaires.

Vers l’élucidation de mécanismes réactionnels.

Nécessite :

(1) un important travail théorique;

(2) des techniques particulières pour conduire les essais expérimentaux : elles sont

en continuelle évolution et sont utilisables y compris dans les cellules.

De nouvelles expériences révolutionnaires permettent d’observer et de manipuler des molécules

uniques et de suivre la dynamique d’une seule molécule enzymatique :

. il y a des fluctuations pour la production du produit.

Why and how do enzymes fluctuate?

Moffitt & Bustamante. 2014, FEBS J, 281, 498

It is the thermal energy (the energy stored in the motion of the surrounding solvent

molecules) that allows enzymes to pass through the energetically unfavourable transition states that

separate kinetic intermediates.

This energy is transferred to the enzyme from random collisions with the surrounding

solvent molecules that are naturally stochastic.

E + S

E + P

E.ET±

The directionality of enzyme-catalyzed reaction comes from the

free energy released in the conversion S to P.

Free energy

Reaction coordinates

Reaction rate (activation free energy)

Finally, enzyme dynamics is dominated by random

fluctuations that depends of:

. the number of kinetic intermediates, their lifetimes, the

order in which they are formed;

. the number of times each intermediate is visited.

Fluctuations are not independent

of the enzymatic mechanism.

The total duration of the reactions

fluctuates.

How are the fluctuations measured and quantified?

Moffitt & Bustamante. 2014, FEBS J, 281, 498

Regardless the method used, measurements of the exact time at which the enzyme completed each cycle = ‘cycle

completion time’ or ‘dwell time’: total time that an enzyme takes to complete a cycle = sum of the time spent in each of its

different enzymatic states. The times spent between each state are often termed ‘waiting times’.

Formalization of the concept by defining the probability that the enzyme will visit a given state at least

once in the cycle.

p0 = 1: for on-way states through which the enzyme must pass.

p0 < 1: for states that are not necessarily visited each cycle (ex. EI)

Single molecule fluorescence

microscopy. Burst for the production

of fluorescent product

Change in position of a molecular motor on

its polymer track detected by the movement of

optically or magnetically trapped bead

Change in a DNA molecule length

strechted between two optical trapped

beads to reveal a nucleic acid motor

E + S ES E + P

E + S ES E + P

IEI

Fluctuations

Theoritical understanding of single-molecule kinetics

Steady state approximation

with

Ensemble averaged kinetics Single-molecule kinetics

C C [S]

[P]

C [S] Cste

[P] Cste

Obtention of waiting time distribution

normalized such as

Adapted from Kou et al. 2005, J Phys Chem B 109, 19068

E + S ES E0+P E0 Ek2k1

k-1

d

with at t = 0: PE(0) = 1, PES(0) = 0, PE0 (0) = 0

and PE(t) + PES(t) + PE0 (t) = 1

Probability

density of the

waiting time

Vitesse

initiale

Ensemble averaged kinetics Single-molecule kinetics

Each emission intensity peak corresponds

to a burst of enzymatic turnover.

Bursts

Blank

v

0

0.2

0.4

0.6

0.8

1

1.2

0 5 10 15 20 25

vi

[S]0

KM

Vmax

Vmax/2

[P]

Time (min)

[S]0

vi1

vi2

vi3

vi4

vi5 = vi

6 = Vmax

Michaelis-Menten equation

Real-time single-molecule recordings

of enzymatic turnovers

Statistical analysisProbability density of waiting time

Michaelis-Menten equation?

Probability density of the waiting time, f(t)

with k1 = 107 M-1 s-1, k2 = 250 s-1, k-1 = 50 s-1

Exponential rise followed by an

exponential decay corresponding to the

generation of the intermediate ES.

Average reaction rate 1/<t> or its equivalent v/[E]T as a function of [S]:

Single molecule

Michaelis-Menten

equation

v/[E]T = 1/<t>

KM = 30 µM

Single-Molecule Michaelis-Menten Kinetics in the Absence of Dynamic Disorder

Characteristic hyperbolic profile of the classical

Michaelis-Menten saturation curve.

Adapted from Kou et al. 2005, J Phys Chem B 109, 19068

<t>: mean waiting

time for the reaction

Consistency between the single-molecule

and ensemble averaged kinetics

Single-Molecule Michaelis-Menten Kinetics in the Presence of Dynamic Disorder

General applicability of the Michaelis-

Menten equation to single-molecule kinetics

even in the presence of dynamic disorder.

Multiexponentiality attributed to dynamic disorder.

The three states of the enzyme E, ES and E0 can each

exist in two interconverting conformations.

Two state model

Single molecule Michaelis-Menten equation holds

even under the condition of dynamic disorder.

Multistate model

Real enzyme systems are likely to interconvert among a

large number of conformational substates.

The value of kcat fluctuates.

Rate limiting step:

. at low [S], binding of the substrate to the enzyme;

. at high [S], dissociation of the ES to product.

Adapted from Kou et al. 2005, J Phys Chem B 109, 19068

Concentration initiale de substrat [S]0

Vit

esse

init

iale

[E]0 << [S]0

Conditions d’état stationnaire

Dans ce type d’expérience, les concentrations

d’enzyme et de substrat sont maintenues constantes

(comme dans les cellules vivantes)

D’après Xie Sunney X 2013 Science 342 1457

Equation de Henri-Michaelis-Menten :

(1) Quantification des cinétiques enzymatiques;

(2) Moyen pratique pour caractériser une enzyme

en termes de kcat et KM.

Indicateurs de l’efficacité enzymatIque :

haut kcat, bas KM et haut rapport kcat /KM .

Volume d’intérêt

En résumé

Pour une cinétique donnée, [S] diminue

Cinétiques

rapides(stopped-flow, flux

continu)

Mise en

évidence de la formation

d’intermédiaires

Donne en plus des informations cruciales sur la

formation d’intermédiaires et le désordre dynamique.

Etablissement d’état stationnaire

‘Turnover’ d’une molécule uniquePas d’état stationnaire

Enthalpie libre DGEtats de transition ET‡

Coordonnées réactionnelles

DGcc‡

DGnc‡

DG0

DGenz‡

Non catalysé

Catalyse chimique

Catalyse enzymatique

RéactifsE + S

ComplexeES Complexe

EP

ProduitsE + P

Non catalysé

Catalyseur chimique

Catalyseur enzymatique

ES, EP : complexes non covalents

Diagramme traditionnel d’enthalpie libre pour une réaction enzymatiqueComparaison avec une réaction non catalyése ou catalysée par un réactif chimique

DG‡ Enthalpie libre d’activation

DG0 Enthalpie libre de la réaction

DGnc‡DGcc

‡DGenz‡ < <

Le catalyseur stabilise l’état de transition de la réaction catalysée par rapport à la réaction non catalysée : DG‡ DIMINUE et la constante de vitesse k AUGMENTE d’où l’accéleration.

Relation de Eyring: k = (kBT/h) e-DG‡ /RT

L’équilibre de la réaction n’est pas modifié par le catalyseur : DG0 est INCHANGE. DG0 = -RT ln Keq

kB : constante de Boltzman; h : constante de Planck; R : 2 cal/mol/degré

[ES]‡

[S]‡

Free

energy

Reaction coordinate

Transition state

Products

Reactants

A- + B-C

A-----B-----C

d d

A-B + C-

Free energy profile of a chemical reaction

Cleavage of B-C bond

Formation of

A-B bond

A- + B-CReactants

Products

A-B + C-

Transition state

A-B--C

Unstable

inermedaite

A- + B+ + C-

Unstable

intermediate

Free energy surface

Reactants

Products

1

2

21

Enzyme fluctuations: standard free energy lanscape

Hammes-Schiffer 2013 Biochemistry, 52, 2012.

S + E1 ES1 P + E10 E1

S + E2 ES2 P + E20 E2

S + En ESn P + En0 En

… … …

Kinetic scheme of the multistate model

involving n interconverting conformers.

Schematic representation of the standard free energy

landscape for the catalytic network of an enzyme reaction

Parallel catalytic

pathways

The reaction paths can slide along and between both coordinates:

fluctuations of kcat

kcat

Single Molecule Fluorescence Assays by Fluorescent Measurements

. Assays with fluorescent active sites (cholesterol oxidase).

. Assays with fluorescently labeled substrates (single molecule DNA sequencing).

. Assays based on a fluorogenic substrate converted to a fluorescent product molecule by an

enzymatic reaction.

. Assays with fluorescent resonance energy transfer (FRET) pairs that report conformational changes

triggered by enzyme tunrovers (staphylococcal nuclease, a ribozyme, T4 lysozyme).

. Assays based on photo-induced electron transfer used between excited states (flavin and tyrosine

residues to probe conformational motions associated with enzymatic reactions of flavoenzymes).

- Complementary to FRET, probes conformational changes at shorter distances (several Å) than FRET

probes (several nm).

. Assays based on rotational and translational trajectories of molecular motors by recording movies

of fluorescent labels (relative rotation of RNA polymerase and RNA usisng a magnetic and fluorescent

bead; translation of possessive motor enzymes such as kinesin, myosin, DNA polymerase, helicase).

Flow Stretching Assay

Other single molecule manipulation methods

Single molecule tools for enzymology

Xie 2001, Single Mol 2, 4, 229 ; Widom et al. 2014 Arch Toxicology 88, 1965

Single-molecule fluorescence microscope

Schematic illustration of an objective-type total

internal reflection fluorescence (TIRF) microscope.

Grima et al. 2014 FEBS J, 281, 518 - Widom et al. 2014 Arch Toxicology 88, 1965.

c

Immobilized enzyme (agarose or polyacrylamide gel; fixed on

a surface; trapped by optical or magnetic tweezers)

Real-time single-molecule recordings of enzymatic turnovers

A fluorogenic substrate is converted into fluorescent product. Each emission intensity peak corresponds to a burst

of enzymatic turnover.

Binding and unbinding of fluorescently labeled probes to an immobilized oligonucleotide.

Grima et al. 2014 FEBS J, 281, 518 - Widom et al. 2014 Arch Toxicology 88, 1965.

Recordings

Experimental setup Fluorescent intensity trace

Adapted from English et al. Nature Chemical Biology, 2 2006, 87,

Stochastic time trace of repetitive reactions (20.000)

of a single b-galactosidase molecule at 20 µM RGP

b-galactosidase

Threshold used to

determine waiting

times between two

adjacent bursts.

Histogram of

enzymatic time

trace

f(t)

20 10

0

0Intensity

Mean of t:

<t>

SINGLE ENZYME ASSAY WITH FLUORESCENT PRODUCT

RGP: resorufin-b-D-

galactopyranoside

(20 µM)

For a given [S]

Determination of the probability density of the

waiting time t for an enzymatic reaction to occur: f(t)

v k2[S]

[S]KM

Variation with [S]

w

i

t

h Michaelis equation

Number

The Michaelis function holds on a single molecule basis despite fluctuations

< t > tf (t )dt0

Waiting time fluctuations are explained by enzyme conformation fluctuations.

Aim: create conformations that able to accommodate the substrate.

. Spontaneous or thermal activated fluctuations (ubiquituous).

. Nonequilibrium process driven by substrate binding or chemical reactions.

Techniques used to study conformational changes

- FRET (fluorescence resonance energy transfer), only sensitive to the distance

change on the order of nanometers (Weiss 2000);

- method based on photo-induced single-electron transfer (Yang et al. 2003);

- method based on motion hindering in the excitated stated (Luo et al 2007)

Two types

conformational

changes

Single molecule conformational dynamics

Preuve de la dynamique d’une molécule unique par transfert d’électrons photoinduit

hn

hn :excitation laser UV à faible

let forte fréquence

g

g :vitesse de recombinaison

radiative (réémission d’un photon

à une fréquence plus basse)

kg: vitesse de recombinaison non

radiative (désexcitation)

kg

kEt

Influence du

milieu extérieur

Un microscope confocal est utilisé pour détecter

le signal de fluorescence d’une seule molécule.

kEt: transfert d’énergie sur une autre molécule (par

ex, entre un donneur et un accepteur)

Diagramme d’énergie de l’état excité Et

Très sensible à la fluctuation de la distance entre

donneur et accepteur (échelle de l’Å) qui se traduit par

une fluctuation du temps de fluorescence.

Donneurs naturels : Tyr, Trp, guanine du DNA

Accepteurs naturels : flavine ou colorants artificiels

comme la rhodamine

Single-Molecule Conformational Dynamics Probed by Electron Transfer

Structure of flavin reductase Fluorescence decays of the wild type

and mutants of flavin reductase

By probing the fluorescence lifetime of the single flavin:

variation of flavin-tyrosine distance over time thus conformational

fluctuations at multiple time scales spanning from hundreds of µs to s.

Yang et al. 2003 Science, 302, 262

Oxidized flavin Reduced flavin

NADH NAD

Favin reductase

Y35S/FMN

Free FMN

2 H+,

2 e-

Reduction

Pulse laserDrastic increase of fluorescence lifetime only

observed for the Y35S complex (red curve), proving

the quenching by tyrosine Y35.

Existence of multiple interconverting conformers related to the fluctuating catalytic activity.

Fluorescence intensity of Cy3 is increased when the nonradiative decay rate of Cy3 is decreased due to hindered torsional motions of the excited state of Cy3 molecule: reflects closing of the fingers domain.

Probing Non-equilibrium Conformational Motions by Fluorescence Intensity Changes of a Hindered Fluorophore

Primed DNA duplex

labeled with Cy3 dye

molecule

Exonuclease part

Closing of DNA Polymerase fingers domain

dNTP

Primed DNA

With dNTP

Li et al 1998 EMBO J, 17, 7514; Luo et al.

2007 PNAS, 104, 12610

closedopen

Ternary

complex

Detection real time

conformational changes

Assays with fluorescent active sites

Cholesterol oxidase

Crystal structureFluorescence image

(8 x 8 µm) of single E

molecules immobilized

in a agarose gel

Distribution of on-timesReal-time observation of enzymatic turnovers of a single

enzyme catalyzing oxidation of cholesterol moleculesLu et al. 1998, Science, 282, 1877

E + S ES Productk2k1

on

on

on off

off off

Occu

ren

ce

Flow Stretching Assay

Van Oijen et al , 2003, Science, 301, 1235,

Monitoring the activity of individual nucleic acid enzymes on DNA simultaneously

Two digestion traces showing complete enzymatic

conversion of l-phage dsDNA into ssDNA The coiling of l-phage ssDNA causes it

to be shorter than dsDNA

Model of the l

exonuclease complex

dsDN

A

ssDNA

ssDNA

dsDN

A

Other single molecule manipulation methods

Novo folding of ribosome-bound nascent proteins

Bustamante et al , 2014, Ann Rev Biophys, 43, 119

Optical tweezer measurements

Spécificité

. Types de réaction catalysée

. Nature du (des) substrat(s) pour un type de réaction donnée

. Selon l’enzyme, la spécificité est plus ou moins étroite: notion de promiscuité

La spécificité dépend d’un arrangement très précis des atomes du centre actif

The specificity is related to the chiral structure of the enzyme molecule, including the three-dimensional folding of the polypeptide backbone and the orientation of

the amino acid side chains in the folded enzyme .

Total chemical synthesis

of D-enzymes

Milton et al. Science 1992

256, 1445 – Kent J Peptide

Science, 2003, 574

L-HIV-1 protease D-HIV-1 protease

L-PR

+

L-Sub

L-PR

+

D-Sub

Time (min)Time (min)

D-PR

+

L-Sub

D-PR

+

D-Sub

Flu

ore

scen

ce

Each enzyme eniantomer cuts only the corresponding substrate eniantomer:

reciprocal chiral specificity on peptide substrates

Flu

ore

scen

ce

Promiscuité enzymatique

L’enzyme peut effectuer des réactions non prévues (si on se base sur sa spécificité connue)

Promiscuité de conditions réactionnelles.

Enzymes ayant une activité catalytique dans diverses conditions réactionnelles qui sont différentes

de ses conditions naturelles (par exemple : milieu anhydre, températures ou pH extrêmes).

Promiscuité dans la gamme de substrats reconnus.

Enzymes ayant une spécificité très large.

Promiscuité catalytique.

Enzymes catalysant de manière distincte différentes transformations chimiques qui présentent des

états de transition différents.

Elle peut être

a. accidentelle : réaction annexe catalysée par l‘enzyme.

b. induite : une nouvelle réaction est établie suite à une ou plusieurs mutations ce qui change la

nature de la réaction par rapport à l’enzyme sauvage (ingéniérie des protéines).

Induction de promiscuité

catalytique

Glycosidase

(type sauvage)

Glycosynthase

Thioglycoligase

Thioglycosynthase

Acide aminé

muté

See also Hancock et al 2005 ChemBioChem, 6, 866 and references therein.

F. Stoll et al. 2011 Drug Discovery Today,

16

Promiscuity of ligand binding of cytochrome P450 2C9

Superposition of several X-ray structures of

complexes enzyme-ligands

Active site

Fonctionnement régulé des enzymes

. Régulation de l’activité par changement de conformation.

Rétro-contrôle; effecteurs allostériques

A B C ------ Y

. Régulation par modification de la structure covalente de l’enzyme.

Modifications covalentes réversibles : phosphorylation, adénylation, protéines G (GDP/GTP).Modifications irréversibles : protéolyse (activations protéolytiques), ADP-ribosylation.

. Contrôle exercé par des inhibiteurs naturels.

Si déficient : polymérisation et induction de pathologies conformationnelles.

. Régulation par des molécules exogènes d’intérêt pharmacologique

-E1 E2 E3 En

The proteolytic cascade of kallikreins (hKs) involved in

epidermidermal homeostasis

LEKT

I

hK5pro hK5

hK14

hK14pro

Cornification Desquamation Innate immunity Inflammation

hK7

hK7pro

CathelicidinProfilaggrin PAR-2

IL - 1 β

Desmoglein (DSG-

1)

Desmoplakin

Desmocollin 1-3

hK5

hK5

Matriptase LEKTI: natural inhibitor

(145 kDa)

The current repertoire of epidermal proteases and inhibitors

SJ de Veer et al. Proteomics Clin Appl 2014, 1-4.

Skin disorders linked to dysregulated

proteolytic activity affect different

homeostatic processes.

EI, exfoliative ichtyosis; APSS, acral peeling syndrome ;NS,

Netherton syndrome; IS & BD, inflammatory skin and bowel

disorder IHS,ichtyosis hypotrychosis syndrome ; PLS; .

Black: monogenic disorders

White: multifactorial diseases

Mauvais repliement

Trafic incorrect

(Emphysème pulmonaire)

Repliement toxique : agrégats fibrillaires

(Amyloïdoses)

Maladies conformationnelles ou du mauvais

repliement des protéines

Probabilité augmentée de dégradation

(caveolin-3, LGMD-1C; CFTR, mucoviscidose)

Protéine dépliée Protéine native

fonctionnelle

La perte d’activité des inhibiteurs peut être due à un

mauvais repliement

a1-PI(a1-antitrypsine)

Recyclage et

perte de

fonction

Synthèse et

acquisition de

fonction

Etat cellulaire normalEquilibre entre synthèse et

recyclage des protéines

(pour une protéine donnée)

From Nature Chem Biol, nov 2014)

Lomas & Mahadeva J

Clin Invest 2002, 110,

1585

Bibliography

Special Issue. Enzyme Catalysis and Allostery: A Century of Advances in Molecular

Understanding. FEBS J, 2014, 281.

References cited in the diaporama.

Website: http://bernstein.harvard.edu/research/singlemolecule.html

Books

Athel Cornish-Bowden

Fundamental of enzyme kinetics (2004; 2012); Ed. Wiley-Blackwell.

Robert A. Copeland

Enzymes: A pratical introduction to structure, mechanisms and data analysis (2000)

Evaluation of Enzyme Inhibitors in Drug Discovery (2013); Ed. Wiley-VCH.

Daniel L. Purlich

Enzyme kinetics: catalysis and control (2010) Elsevier.

Alan Fehrst

Enzyme structure and mechanism in protein science: a guide to enzyme analysis and protein folding (1999 );

Ed. WH Freeman.

The selected papers of Sir Alan Fersrt: development of protein engeneering. ICP selected papers (2010).

Jeannine Yon-Kahn & Guy Hervé.

Molecular and cellular enzymology (2010); Ed. Springer-Verlag.

Irwin H. Segel

Enzyme kinetics: behavior and analysis of rapid equilinbrium and steady-state enzyme systems (1993); Ed.

Wiley Classics Library.