università degli studi di milano dipartimento di scienze farmaceutiche “pietro pratesi”

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Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi” Alessandro Pedretti tein modeling by fragmental approa connecting global homologies with local peculiarities

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Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”. Protein modeling by fragmental approach: connecting global homologies with local peculiarities. Alessandro Pedretti. Molecular docking. Molecular dynamics. Protein modelling. Structure-based studies. - PowerPoint PPT Presentation

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Page 1: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Università degli Studi di MilanoDipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Alessandro Pedretti

Protein modeling by fragmental approach:connecting global homologies

with local peculiarities

Page 2: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Structure-based studies

• In order to perform structure-based studies as:

– ligand optimization;

– virtual screening;

– signal transduction;

– substrate recognition.

the 3D structure of the biological target is required.

• Unluckily, the experimental structure (X-ray diffraction or NMR) is not available for all proteins.

Molecular docking

Molecular dynamics

Protein modelling

Page 3: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

What’s the protein modelling ?

• The protein modelling allows to obtain the 3D structure of a protein from its aminoacid sequence (primary structure):

GFGPHQRLEKLDSLLS…

Protein modelling1D structure

3D structure

• It can be classified into two main approaches:

Protein modellingProtein modelling

Comparative modellingComparative modelling

Ab-initio modellingAb-initio modelling

Page 4: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Comparative modelling

• It’s based on the assumption: proteins with high homology of sequence should have similar folding.

Target sequenceTarget sequence

3D template3D template

AlignmentAlignment

Rough 3D modelRough 3D model

3D structure database3D structure database

Homology > 70 %

Structures obtained by experimental approaches (X-ray and NMR).

To refinement workflow

Between target and template

Page 5: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Ab-initio modelling

• It’s based on physical principles and geometric rules obtained by sequence and structure analysis of the 3D experimental models.

Target sequenceTarget sequence

Multiple solutionsMultiple solutions

Global optimizationGlobal optimization

Rough 3D modelRough 3D model

Folding predictionFolding prediction

To refinement workflow

Application of physical and geometric rules

By MM and stochastic approaches

Page 6: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Comparative vs. ab-initio modelling

• The possibility to obtain structural “clones” is very high, submitting whole query sequences of protein families with high homology to a limited number of 3D templates (e.g. transmembrane proteins).

Comparative Ab-initio

3D template Yes No

Success High Low

Computational time Low Very high

Structural “clones”* Yes No

*Models that are structurally similar due to the common template.

Page 7: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Fragmental approach

Target sequenceTarget sequence

Fragmentation in structural domains

Fragmentation in structural domains

Folding prediction of each fragment

Folding prediction of each fragment

Assembling using the global 3D template

Assembling using the global 3D template

Rough modelRough model

Done on the basis of information included indatabases and/or domain finder tools.

Trough multiple comparative modelling procedures.

By geometric superimposition with the 3D structure of the global template, using molecular modelling tools as VEGA ZZ.

To refinement workflow

Page 8: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Model refinement procedure

Missing residuesMissing residues

Side chains addSide chains add

Hydrogens addHydrogens add

Energy minimizationEnergy minimization

Final modelFinal model

Rough modelRough model

VEGA ZZ+

NAMD

Structure checkStructure check

Page 9: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Human 42 nicotinic receptor

• The nicotinic acetylcholine receptors (nAchRs) are composed by five subunits assembled around a central pore permeable to cations.

17 subunit types17 subunit types

1, 1, , 1, 1, , 2-10, 2-42-10, 2-4

MuscleMuscle Nervous systemNervous system

• The therapeutic interest on nicotinic ligands is highlighted by diseases involving the nAchRs as: Alzheimer’s and Parkinson’s disease, autism, epilepsy, schizophrenia, depression, etc.

Human4 subtype

• The complete model didn’t exist.• The design of selective 42 ligands is problematic

due to the low information about the binding mode.

Pedretti A. et Al., Biochemical and Biophysical Research Communications, Vol. 369, 648–53 (2008).

Page 10: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Monomer modeling

Primary structurePrimary structure FragmentationFragmentation

Folding prediction of each fragment

Folding prediction of each fragment

Helices assembly by molecular docking

Helices assembly by molecular docking

Side chainsSide chains

HydrogensHydrogens

MM refinementMM refinement Final monomerFinal monomer

VEGA ZZ

VEGA ZZ + NAMD

ESCHER NG

Fugue

SwissProt

Full assemblyFull assembly

4 transmembrane domains2 cytoplasmic loops1 extracellular loop2 terminal domains

The docking results were filtered the Torpedo Californica nAChR structure.

Page 11: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Complex assembling

+

2x4

3x 2

42

Side view

Top view

Multistep docking:4 + 2 → 422 42 → (4)2(2)2

2 + (4)2(2)2 → (4)2(2)3

ESCHER NG

Page 12: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Model validation

• The soundness of the resulting model was checked docking a set of know nicotinic ligands:

NH

N

Cl

N N

CH3

ON

CH3

N

H

CH3

N

O

NH

N

NH

Nicotine Epibatidine ABT-418 Citisine A-85380

• All these ligands were simulated in their ionized form.

LigandLigand

42 receptor42 receptor

+ DockingDockingBinding site selectionTrp182, Cys225, Cys226 in 4

Binding site selectionTrp182, Cys225, Cys226 in 4 MinimizationMinimization

Final complexFinal complex

VEGA ZZ FRED 2 NAMD

Page 13: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Docking results

• After the final MM minimization, the docking scores were recalculated by Fred 2 (ChemGauss2 scoring function):

CompoundKi

(nM)Score

(Kcal/mol)

Epibatidine 0.009 -48.7

A-85380 0.05 -45.1

Citisine 0.16 -42.6

Nicotine 1.0 -38.9

ABT-418 4.6 -35.9

Cys225 4

Cys226 4

Trp182 4Phe144 2

Asn134 2

Trp82 2

42 – nicotine complex

Page 14: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Human glutamate transporter EAAT1

Pedretti A. et Al., ChemMedChem, Vol. 3, 79-90 (2008).

• L-glutamate is the main excitatory neurotransmitter in the CNS.

Glutamate

Synaptic cleft

Excitatory effects

Axon Dendrite

Metabotropic receptor

Ionotropic receptor

EAAT1-5

• It can also overactivate the ionotropic receptors, inducing a series of destructive processes involved in acute and chronic neurological diseases (e.g. amyotrophic lateral sclerosis, Alzheimer’s disease, epilepsy, CNS ischemia, etc).

Page 15: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

EAAT ligand classification

• They can be classified in:

• Natural substrates.

• Substrate inhibitors.

• Non transported uptake blockers.

• The last two classes are interesting because in pathological conditions, when the electrochemical gradient is damaged, EAATs can operate in reverse mode, overactivating the post-synaptic receptors.

Research aims:

• Human EAAT-1 3D structure by homology modeling.

• Pharmacophore models for all ligand classes.

Page 16: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Monomer modeling

Primary structurePrimary structure FragmentationFragmentation

VEGA ZZ

MM refinementMM refinement Final monomerFinal monomerVEGA ZZ + NAMD

Folding prediction of each fragment

Folding prediction of each fragmentFugue

SwissProt

HydrogensHydrogens

Side chainsSide chains

Full assemblyFull assembly

The domains were found aligning the sequences of EAAT1 and glutamate transporter from Pyrococcus horikoshii.

The assembly was carried out using the crystal structure of glutamate transporter homologue from Pyrococcus horikoshii.

Page 17: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Complex assembling

ESCHER NG VEGA ZZ + NAMD

DEEP surface

Monomer

Homotrimer

Complex refinement protocol:• 1 ns of simulation time;• restrained transmembrane segments;• final conjugate gradients minimization.

Page 18: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Docking studies

• Two ligand subsets were docked:

• natural substrates and competitive substrates inhibitors (16);• non-transported blockers (16).

• The following procedure was applied to all ligands:

LigandLigand MinimizationMinimization DockingDocking

EAAT1 monomerEAAT1 monomer

ComplexComplex

Mopac 7 FlexX

• The docking analyses were focused on residues enclosed in a sphere centered on Arg479 (TM4). Mutagenesis studies showed this residue plays a pivotal role in the substrate interaction.

Page 19: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Docking results: substrate inhibitors

pKm = 4.88 (±0.04) – 1.52 (±0.12) Vover

N = 15, r2 = 0.93, s = 0.11, F = 174.11

Where Vover is maximum overlapping volume between the ligand and EAAT1 computed by FlexX.

Gln445

Thr450

Val449Met451

Arg479

Gln204

EAAT1 – (2S, 4R)-methylglutamate complex

Page 20: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Docking results: non-transported blockers

pIC50 = 0.4446(±0.07) – 0.141(±0.02)ScoreFlexX

N = 16, r2 = 0.77, s = 0.55, F = 43.46

Ile468

Trp473

Arg479

Gln204Gln445

Thr450

Val449

Leu448

Ile465

EAAT1 – L-TBOA complex

Page 21: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

• Mapping the docking results onto the pharmacophores, it’s possible to highlight the two approaches are successfully overlapped.

Pharmacophore mapping

Natural and substrate inhibitors Non-transported blockersL-glutamate TFB-TBOA

• The two pharmacophore models were obtained by Catalyst 4 software.• Both models highlight the key features required for the interaction.

En = excluded volumeAn = H-bond acceptors

P = ionisable group (positively charged)Y = hydrophobic region

Page 22: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Conclusions

• We obtained the full model of two transmembrane protein through the fragmental approach.

• Performing molecular docking studies, we highlighted the main interaction between ligands and the proteins that were confirmed by experimental data, obtained by mutagenesis studies.

• Although the number of considered ligands isn’t statistically relevant, we obtained good relationships between the docking scores and the experimental data, confirming the soundness of both models.

• All these results show the power and the goodness of the fragmental approach that is able to overcame the problems introduced by global homologies and the possibility to obtain structural clones.

Page 23: Università degli Studi di Milano Dipartimento di Scienze Farmaceutiche “Pietro Pratesi”

Acknowledgments

www.ddl.unimi.itwww.vegazz.net

• Giulio Vistoli

• Cristina Marconi

• Cristina Sciarrillo

• Laura De Luca