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Computer Aided Drug Design and Hits identification

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Computer Aided Drug Design and Hits identification La struttura tridimensionale della proteina è stata determinata mediante cristallografia a raggi X o NMR oppure è stata ottenuta per homology modelling. De novo drug design Building - PowerPoint PPT Presentation
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Computer Aided Drug Design and Hits identification La struttura tridimensionale della proteina è stata determinata mediante cristallografia a raggi X o NMR oppure è stata ottenuta per homology modelling
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Page 1: Computer Aided Drug Design  and Hits identification

Computer Aided Drug Design and

Hits identification

La struttura tridimensionale della proteina è stata determinata mediante cristallografia a raggi X o NMR

oppure

è stata ottenuta per homology modelling

Page 2: Computer Aided Drug Design  and Hits identification

De novo drug design BuildingRicerca con gruppi funzionali partendo da un sito ed espandendosi nel sito attivo.

LinkingRicerca con gruppi funzionali partendo da diversi punti del sito attivo e collegandoli successivamente con uno scaffold.

In silico screening

Docking da librerie virtuali o reali

Scoring function

Page 3: Computer Aided Drug Design  and Hits identification

Modification of ligands in situ or design of new ligands

Drug Design

Docking of designed ligands into the binding site (AutoDock, Dock, FlexX…)

Score of the new complexes

Synthesis of new compounds

Page 4: Computer Aided Drug Design  and Hits identification

The Master Equation

G = H - TS

Page 5: Computer Aided Drug Design  and Hits identification
Page 6: Computer Aided Drug Design  and Hits identification
Page 7: Computer Aided Drug Design  and Hits identification

ab

c

dceg

f

Page 8: Computer Aided Drug Design  and Hits identification

H is relatively easy to calculate

• Enthalpy (H) is derived from static models of molecular or bimolecular structure.

• Molecular mechanics force field methods deconvolve H into intramolecular and intermolecular terms from bond stretches, angle bends, torsions, etc., electrostatic interactions and van der Waals (London) forces.

• Many academic and commercial force field programs are available, using similar approaches with essentially comparable results.

Page 9: Computer Aided Drug Design  and Hits identification

S is much harder to calculate

• Entropy = disorder. Computers don’t like disorder!

• Must account for all components of the system, including solvent molecules. (Explicitly?)

• Must add “movement” to the molecule(s) using something like molecular dynamics.

• Entropy itself is not directly (experimentally) measured – calibration of model calculations is less reliable than for enthalpy.

Page 10: Computer Aided Drug Design  and Hits identification

How can we calculate G directly?

• Free Energy Perturbation method (Kollman, Karplus, Beveridge and others)Thermodynamic cycle: Gbind = GI2 - GI1 = Genz – Gsol

(Genz = free energy binding difference between two ligands I1 and I2, Gsol = solvation energy difference between I1 and I2)

Genz and Gsol calculated from extensive molecular dynamics simulations of enzyme/inhibitor systems.

• MC/MD LR (Monte Carlo/Molecular Dynamics with a Linear Response method (Jorgensen et al.)G = [Helec] + [Hvdw] + [SASA]106 to 107 analyzed configurations

Page 11: Computer Aided Drug Design  and Hits identification

Metodi di predizione

• Decomposizione del G° (la teoria dice che è una procedura scorretta)

• Metodi FEP (Free Energy Perturbation) [Kollman, Karplus, Beveridge….]

• MC/MD LR (Monte Carlo/Molecular Dynamics con un metodo Linear Response) [Jorgensen et al.]

• Metodi empirici

Page 12: Computer Aided Drug Design  and Hits identification

A “natural” force field• No preservatives and 9944/100% Hamiltonian

and wave function free!• Biological binding events are not a neat set of

terms specific to hydrogen bonding, acid-base, Coulombic and/or hydrophobic interactions – binding is a concerted process!

• Design a Free Energy force field derived from an experiment that measures the free energy of molecular interactions.

Page 13: Computer Aided Drug Design  and Hits identification

Log Po/w = G° / 2.303 RTThe partition of a compound between water and octanole is a process driven by intermolecular interactions between the solvent and the compound, and by hydrophobic interactions, involving solvation-desolvation. These events are the same that take place in the formation of a

ligand-protein complex.

water octanole

Log PA = Log[Aoct/Awater]

Page 14: Computer Aided Drug Design  and Hits identification

Hydrophobicity

• Measured as Water / Octanol Partition Coefficient (P)

• log P > 0 : lipid phase log P < 0 : water phase

Log PA = Log[A]1-octanol

[A]water

Page 15: Computer Aided Drug Design  and Hits identification

Leo (CLOG-P) Method

m

mmn

n

n FjfiLogP11

i = number of occurrences of the fragment constant f of type n.

j = number of occurrences of the factor F of type m.

Page 16: Computer Aided Drug Design  and Hits identification

What is HINT?

Page 17: Computer Aided Drug Design  and Hits identification

Software model based on experimental LogPLogPO/W O/W values for interaction classification and quantitative scoring evaluates enthalpy and entropyenthalpy and entropy

HINT calculates empirical atom-based hydropathic parameters that encode all significant intermolecular and intramolecular non-covalent interactions implicated in drug binding or protein interactions and folding.

The hydrophobic atom constants are calculated using an adaptation of the fragment constant methods of Leo and Rekker.

HINT (Hydropathic HINT (Hydropathic INTeraction)INTeraction)

Page 18: Computer Aided Drug Design  and Hits identification

The “HINT equation”

HINT SCORE = bij = aiSi ajSj Rij Tij + rij

a = hydrophobic atom constantS = solvent accessible surface areaRij = exponential (e-r)Tij = discriminant function for polar-polar interactionsrij = van der Waals term

Page 19: Computer Aided Drug Design  and Hits identification

ai = Log Po/w = - G / 2.303 RT

bij = f (G)

(G. E. Kellogg and D. J. Abraham Eur. J. Med. Chem.2000, 35, 651-661)

Page 20: Computer Aided Drug Design  and Hits identification

Classes of Non-Covalent Interactions 

 

 

Hydrogen Bonds - A-H…B- 1 – 10 kcal/mole

Coulombic -A+ B-- 0.5 – 5 kcal/mole

Hydrophobic -CHn CHm- 0.5 – 2 kcal/mole

Van der Waals (London) -X Y- < 1

kcal/mole

Note: Any comprehensive method that attempts to model ligandbinding must also consider the energy of solvation and entropiccontributions to the binding process.

Page 21: Computer Aided Drug Design  and Hits identification

Hydropathic Interactions

Coulombic Repulsion

Acid-Base (Hydrogen Bond)

Hydrophobic-Polar (desolvation)

Polar Lewis Base (H-Bond Acceptor)

Acid-Base (Hydrogen Bond)

Coulombic Repulsion

Hydrophobic-Polar (desolvation)

Polar Lewis Acid (H-Bond donor)

Hydrophobic-Polar (desolvation)

Hydrophobic-Polar (desolvation)

Hydrophobic Interaction

Hydrophobic

Polar Lewis Base (H-Bond Acceptor)

Polar Lewis Acid (H-Bond Donor)

Hydrophobic

Page 22: Computer Aided Drug Design  and Hits identification

Negative interactions

Page 23: Computer Aided Drug Design  and Hits identification

Asp-Asp Interaction

Page 24: Computer Aided Drug Design  and Hits identification

Leu-Leu Interaction

Page 25: Computer Aided Drug Design  and Hits identification

Correlazione tra l’energia libera di legame tra proteina e ligandi

determinata mediante HINT e l’energia libera determinata

mediante metodi sperimentali

Page 26: Computer Aided Drug Design  and Hits identification

Model BuildingModel Building• Starting point: protein-ligand complexes for

which 3D structure (PDB files) and experimental binding affinity are determined

• Hydrogen atoms added and minimized, hydrogen bound to polar atoms examined and optimized

Working Working ProcedureProcedure

• Evaluation of the protonation state of ionizable groups on protein and ligand (Computational Titration - Fornabaio et al. J. Med. Chem. 2003, 46, 4487-4500)

• Optimization of water molecules bridging protein and ligand

Hydropathic Analysis for the evaluation Hydropathic Analysis for the evaluation

of all contributions to the ligand-of all contributions to the ligand-protein complex formationprotein complex formation

Page 27: Computer Aided Drug Design  and Hits identification

93 complexes93 complexes formed by 18 different proteins of know 3D structure, R < 3.2R < 3.2 Å Å

General Relationship between Hint Score and General Relationship between Hint Score and G°G°

Hint Score units0 1000 2000 3000 4000 5000 6000

G

° (Kc

al/m

ol)

-20

-16

-12

-8

-4

0

bovine thrombinhuman thrombinhydroxynitrile lyaseadipocyte l.b.p.retinol b.p.bovine trypsin

tryptophan synthasepenicillopepsinsaccharopepsinHIV-1 proteaseothers

G° = -0.0018 HINT score – 3.9041G° = -0.0018 HINT score – 3.9041 R R22 = 0.47 R = 0.68 = 0.47 R = 0.68 se = se = 2.33 K2.33 Kcal/molcal/molCozzini et al., J. Med. Chem. 2002, 45, 2469-2483

Page 28: Computer Aided Drug Design  and Hits identification

73 complexes73 complexes R < 2.5 ÅR < 2.5 Å and at least 3 ligands for each protein

General Relationship between Hint Score and General Relationship between Hint Score and G°G°

Hint Score units0 1000 2000 3000 4000 5000 6000

G

° (Kc

al/m

ol)

-20

-16

-12

-8

-4

0

G° = -0.0024 HINT score – 2.2187 RG° = -0.0024 HINT score – 2.2187 R22 = 0.65 R = 0.81 = 0.65 R = 0.81 se = se = 1.89 K1.89 Kcal/molcal/molKellogg et al. J. Mol. Graph. Model. 2004, in press

Page 29: Computer Aided Drug Design  and Hits identification

Which is the contribution of water Which is the contribution of water molecules bridging ligand and protein to molecules bridging ligand and protein to

the free energy of binding?the free energy of binding?

Page 30: Computer Aided Drug Design  and Hits identification

Active site of HIV-1 Active site of HIV-1 ProteaseProtease

and presence of a and presence of a ligandligand

in the absence

Page 31: Computer Aided Drug Design  and Hits identification

Water molecules in Ligand Binding to Water molecules in Ligand Binding to HIV-1 HIV-1 ProteaseProtease

• is crystallographically detected in the active site• occupies the same position in all complexes•usually forms four hydrogen bonds – two with the protein and two with the ligand•plays a crucial role in molecular recognition

wat301wat301

wat313, 313’, 313bis, 313bis’wat313, 313’, 313bis, 313bis’•not always crystallographically detected •located in a more peripheral area of the active site

w301w301

w313bis’w313bis’

w313’w313’

w313bisw313bis

w313w313

D25 D125

I150 I50

R108 R8

D29

R187R87

D129

Page 32: Computer Aided Drug Design  and Hits identification

The software GRID (P. Goodford, J. Med. Chem. 1985) was used to locate water molecules in HIV-1 protease active site, when they were not present in the crystallographic structures.

D25 D125

I150 I50

R108 R8

D29

R187R87

D129

Page 33: Computer Aided Drug Design  and Hits identification

Hydrophatic Interaction Map: P-L

Page 34: Computer Aided Drug Design  and Hits identification

Hydrophatic Interaction map: P-L + L-H2O

Page 35: Computer Aided Drug Design  and Hits identification

withoutwithout and withwith wat301

The Role of Structural Waters in The Role of Structural Waters in HIV-1 Protease-Ligand Complexes

RR22 = 0.30 R = 0.55 SE = 1.3 = 0.30 R = 0.55 SE = 1.3 Kcal molKcal mol-1-1

RR22 = 0.63 R = 0.80 SE = 1.0 = 0.63 R = 0.80 SE = 1.0 Kcal molKcal mol-1-1

HINT score units2000 3000 4000 5000 6000 7000

G

° (K

cal/m

ol)

-17

-15

-13

-11

-9

-7

with wat301without wat301

Page 36: Computer Aided Drug Design  and Hits identification

The Role of Structural Waters in Ligand Binding to The Role of Structural Waters in Ligand Binding to ProteinsProteins

G

° (K

cal/m

ol)

-17

-15

-13

-11

-9

-7

2000 3000 4000 5000 6000 7000

-17

-15

-13

-11

-9

-7

Hint Score units

G° (

Kca

l/mol

)

-17

-15

-13

-11

-9

-7

SE = SE = 0.8 0.8 kcal/molkcal/molR = 0.84R = 0.84

Hint Score units2000 3000 4000 5000 6000 7000

-17

-15

-13

-11

-9

-7

with wat301-313with wat301-313

with wat301-313-313’-313bis-313bis’with wat301-313-313’-313bis-313bis’

SE = SE = 1.0 1.0 Kcal/molKcal/molR = R =

0.780.78

with wat301-313-313’-313biswith wat301-313-313’-313bis

with wat301-313-313’with wat301-313-313’

SE = SE = 1.0 1.0 Kcal/molKcal/molR = R =

0.780.78

SE = SE = 1.0 1.0 Kcal/molKcal/molR = R =

0.770.77

Page 37: Computer Aided Drug Design  and Hits identification

O

OH

O OP

O O

H

O

O

O OP

O O

H

O

O

O OP

OO

pH 3.5 pH 4.5 pH 5.5

-H

+H

-H

+H

Asp213Asp33

Asp213Asp33

Asp213Asp33

Hint Score units-8000 -6000 -4000 -2000 0 2000 4000

G (K

cal m

ol-1)

-10

-9

-8

-7

-6

-5pH 5.5

pH 4.5

pH 3.5

pH 3.5 pH 4.5 pH 5.5

The role of pH on Ligand BindingThe role of pH on Ligand Binding Penicillopepsin-Phosphonate Ligand Complex

•Binding constants experimentally determined at three different pH values (Bartlett et al., J. Org. Chem. 1990). •Models corresponding to the different protonations of the two catalytic aspartates were built, assuming that addition of one H decrease in one pH unit.

Page 38: Computer Aided Drug Design  and Hits identification

Computational TitrationComputational TitrationDrop protons into the molecular models, one

hydrogen at a time acidification in silico of the environment of the protein-ligand complexes at the binding site

Model ALL possible cases for each “pH” level (corresponding to a defined number of protons into the model)

Calculate the HINT score for each model, averaging the values that correspond to each “pH” level

Plot the mean HINT score values as a function of the number of added protons

The role of pH on Ligand BindingThe role of pH on Ligand Binding

Page 39: Computer Aided Drug Design  and Hits identification

pH3.03.54.04.55.0

G

° (K

cal/m

ol)

-7.0

-6.5

-6.0

-5.5

-5.0

-4.5

-4.0

G° -6.39 -6.36 -6.12 -5.85 -5.25 -5.03 -4.49

pH 3.10 3.40 3.90 4.30 4.40 4.75 4.90

The Role of pH on Ligand Binding:The Role of pH on Ligand Binding:HIV-1 Protease-Peptidic Ligand HIV-1 Protease-Peptidic Ligand

ComplexComplexFor a complex between HIV-1 protease and a peptidic ligand (Glu-Asp-Leu), binding affinities were experimentally determined as a function of pH.

experimental titration experimental titration curvecurve

(J. M. Louis et al., Biochemistry 1998, 37, 2105-2110)

Page 40: Computer Aided Drug Design  and Hits identification

H2N

HN

ONH

OO

O

O

O

OOO

O

O

O

OO

O O_

_

_

__

__

ASP30

ASP29 ASP25

ASP25

H2N

HN

ONH

OO

O

O

O

OOO

O

O

O

OO

O O_

_

_

__

__

ASP30

ASP29 ASP25

ASP25

H+

?… 8 ionizable groups ………. 4374 models to be evaluated

Glu-Asp-Leu bound at HIV-1 protease …

Page 41: Computer Aided Drug Design  and Hits identification

How many protons should be dropped into the models?How many models should be built?How much time does it take?Which is the most favourable ionization state?

All possible ionization states are modeled and scored automatically with the “COMPUTATIONAL TITRATION” procedure

-8000

-6000

-4000

-2000

0

2000

-8 -7 -6 -5 -4 -3 -2 -1 0 1 2Site Charge

HIN

T Sc

ore

-10

-8

-6

-4

-2

0

2

4

6

pH

G (kcal/m

ol)

Model ScoresNormal Ave.Boltzmann Ave.Louis et al.

345

pH of crystallization

Page 42: Computer Aided Drug Design  and Hits identification

Active site of the complex

neuraminidase-DANA (2,3-didehydro-2-deoxy-N-

acetylneuraminic acid)

Conserved interactions :•Three Arg interact with ligand carboxylate•The hydroxyl groups (O8, O9) of the glycerol side chain hydrogen bonded with Glu276•The hydroxyl O4 sits at the entrance of the pocket formed by Asp151, Glu119 (Glu227)

GLU276

ARG292

ARG371

ARG118

O

O

ASP151

O

O

GLU119O

O

HN

H2N NH2

NH

H2N

H2N

HN

NH2

NH2

HO

O

OGLU277

TYR406

-

-

-

-

+

+ +

HO

OH

OH

O

OH

HN

OO

O

-

Computational Titration: Computational Titration: neuraminidase-inhibitor complexesneuraminidase-inhibitor complexes

Page 43: Computer Aided Drug Design  and Hits identification

Protons

0 1 2 3 4 5 6

HIN

T sc

ore

units

3000

3600

4200

4800

Protons 0 1 2 3 4 5 6

HIN

T Sc

ore

units

4000

5000

6000

Computational Titration:Computational Titration: neuraminidase-inhibitor complexesneuraminidase-inhibitor complexes

HO

OH

OH

O

NH2

HN

O-O

O

O

O

OO

ASP151

GLU119O

OGLU276

HO

OH

OH

O

OH

HN

O-O

O

O

O

OO

O

O

ASP151

GLU119

GLU276

G2AR 92R 3GA 71

R 1GA 1 8 G2AR 92R 3GA 71

R 1GA 1 8

The titration curves show a peak HINT score (maximal binding energy) that The titration curves show a peak HINT score (maximal binding energy) that should correspond to the should correspond to the “optimum” pH for binding“optimum” pH for binding..

Page 44: Computer Aided Drug Design  and Hits identification

TOPOGRAPHIC WATER CLASSIFICATION

HIV-1 protease Lipid Binding Proteinp120GAP GTPase-activating domain

Ribonuclease AHsp90 geldanamycin-binding domain

Page 45: Computer Aided Drug Design  and Hits identification

Total number of analyzed water molecules: 817

H-bond ranking

% w

ater

mol

ecul

es

-10

0

10

20

30

40

0-1 1-2 2-3 3-4 4-5

HINT score

% w

ater

mol

ecul

es0

5

10

15

20

25

30

35

-1

00 -

0

0 -

100

100

- 20

0 2

00 -

300

300

- 40

0 4

00 -

500

500

- 60

0 6

00 -

700

700

- 80

0 8

00 -

900

900

- 10

00

mean HINT score PW: 199mean ranking: 1.6

Page 46: Computer Aided Drug Design  and Hits identification

Next:

Analisi delle classi di molecole d’acqua (in cavità, in superficie, in siti attivi,…)

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