Modelling protein Modelling protein-surface interactions: a surface ...

Modelling proteinModelling protein--surface interactions: asurface interactions: achallenge for computationschallenge for computations

A. Calzolari, R. Di Felice, F. Iori, S.Corni

INFM-CNR S3 National Research Center on nanoStructures and bioSystems atSurfaces, Modena, Italy

G. Cicero - Politecnico di Torino, Italy

A. Catellani – CNR-IMEM, Parma, Italy

C. Cavazzoni – CINECA, Bologna, Italy

ProteinsProteins

• Long linear chains of a-amino acids

• 20 natural a-amino acids

• Have complex 3D structures• Have complex 3D structures

• Perform different functions, e.g.:– Catalyze chemical reactions (enzymes)

– Bind external molecules (immunoproteins)

– Transport electrons between redox partners

Can specifically recognize other molecules/proteins

Exploiting the intrinsic capabilities of proteinsExploiting the intrinsic capabilities of proteins• Proteins can recognize other proteins/molecules

Exploiting the intrinsic capabilities of proteinsExploiting the intrinsic capabilities of proteins• Proteins can recognize other proteins/molecules

Can proteins recognize surfaces?Can we design a protein specific for a given surface?

ora surface that maximally/minimally binds a given protein?

Proteins specific for a surfaceProteins specific for a surfaceExamples of possible applications

•Use proteins to guide theself-assembly of inorganicnanodevices (proteins as asmart glue)

•Use protein to control the growth of inorganic materials, e.g., to obtain nanocrystalswith new shapes

Examples of possible applicationsExamples of possible applicationsprotein specific for a surface

•Use proteins to guide theself-assembly of inorganicnanodevices (proteins as asmart glue)

large gold sphere

•Use protein to control the growth of inorganic materials, e.g., to obtain nanocrystalswith new shapes

small polystirene sphere

SurfaceSurface--recognizing peptides viarecognizing peptides viacombinatorial biotechnologiescombinatorial biotechnologies

• In recent years, combinatorial biochemical methods have beenused to select the best binder to given surfaces, or to findselective binders

iterateiterate

recoverrecoverthe bindersthe binders

amplifyamplify

iterateiterate

S. Brown, PNAS 89, 8651 (1992); M. Sarikaya et al. Nature Mat. 3, 577 (2003)

Proteins can recognize surfacesProteins can recognize surfaces

• Some specific proteins indeed found in this way, e.g.:

GaP InP Ge

•However:

– Still no understanding of the basic physical mechanisms thatgovern the specific interaction No concepts to enable rationaldesign

–Combinatorial selects proteins for a given surface, not viceversa

K.Goede et al., NanoLett 2004C. Tamerler et al., Small 2006 A.Artzy-Schnirman etal., NanoLett 2006

Our (longOur (long--term) goalterm) goal

Understanding the basic physicalprinciples that govern specific protein-principles that govern specific protein-surface interactions by computational

methods

OutlineOutline

• Motivations

• General computational strategies– Multiscale modelling– Ab initio on case studies

• Ab initio molecular dynamics for poly-serine on Au(111)– Method– Simulated system– Results

• Summary

Complexity of the systemsComplexity of the systems

• Very large systems(103-104 atoms)• Protein + Inorganic Surface + Solvent• Multiple length scales

Computational challenge:

• Multiple length scales

• Require statistical sampling and/orsimulation of time evolution

• Multiple time scales

• Involve interactions of different origins• Chemical bonds, Coulomb, dispersion...• Different methods most suitable fordifferent portions

Choice of prototypical systemsChoice of prototypical systems

• The uncertainties on real surfaces (e.g., presence of defects,steps, amorphous oxide layers) and on proteins/peptides (e.g.,unknown structure, too flexible peptides) introduce furthercomplexity in modelling.

• To minimize uncontrolled assumptions, initially focus on well-defined and well-characterized surfaces and polypeptides.

• The knowledge generated from these studies on a range ofprotoypical systems fosters understanding of more complexexamples.

Computational strategiesComputational strategies

Multiscale modellingrelatively general but long term(needs to be developed)(needs to be developed)

Using the most accurate,already available methodsfeasible only for case studies(need enormous computer power)

SettingSetting--up the multiscale schemeup the multiscale scheme

Parametrization of AA fragment-surface interaction energy: QM

From energy of fragments to free-energy of AAs in water Classical MD

Exper

validation

energy of AAs in water Classical MD

From free-energy of AAs tofree energy of proteins BD

riments

Computational multiscale toolbox

validation

validation

The Prosurf projectThe Prosurf project

Parametrization of AA fragment-surface interaction energy: QM

From energy of fragments to free-energy of AAs in water Classical MD

Exper

validation

“Computationaltoolbox for protein-surface docking”

energy of AAs in water Classical MD

From free-energy of AAs tofree energy of proteins BD

riments


validation

validation

Target surfacesTarget surfaces

• Au(111)– stable in air and water

– important for nanobioelectronics (contacts)

– used in optical detection systems for protein materials– used in optical detection systems for protein materials

– target surface for well-characterized gold binding peptides

• Fully hydroxilated a-Al2O3(0001)– ceramic surfaces used in today's biomaterials

– transparent and thus used in optics application

– well-characterized surface, even when hydrated

GolP: a force field for proteinGolP: a force field for protein--surfacesurfaceinteraction in waterinteraction in water

• Other FFs for gold exist (e.g., Zerbetto et al.), not tailored forproteins in water

• Derived from DFT calculations + experimental data + MP2calculations

acetone

mm

acetone

trans 2 butene

diethylsulfide

1-nonene

F. Iori et al. J. Comp. Chem. 30, 1465 (2009); J. Comp. Chem. 29, 1656 (2008)

GolP force field in actionGolP force field in action

• Studying liquid water on Au(111)

• Simulating b-sheets proteins/peptides adhesion on Au(111) (incollaboration with S.Monti, M. Hoefling, K.Gottschalk)

• Interpreting electron transfer measurements for cytochrome Cmutants on gold (see poster by M. Siwko)

• Studying potential of mean force for amino acids adsorption ongold (by M.Hoefling and K. Gottschalk)

• Developing free-energy models for Brownian dynamics (by

D.Kokh, B. Huang, R. Wade)

Computational strategiesComputational strategies

Multiscale modellingrelatively general but long term(needs to be developed)(needs to be developed)

Using the most accurate,already available methodsfeasible only for case studies(need enormous computer power)

OutlineOutline

• Motivations



• Summary

Ab Initio Molecular Dynamics (AIMD)Ab Initio Molecular Dynamics (AIMD)

• Nuclei: classical particles moving on a energysurface determined by electron density

• Electrons: quantum particles that follow the slowernuclear motion

Car-Parrinello AIMD: a single equation of motion with fictitious electronicdegrees of freedom, to keep electrons in the ground state during thenuclear dynamics

Ab Initio Molecular Dynamics (AIMD)Ab Initio Molecular Dynamics (AIMD)

• Nuclei: classical particles moving on a energysurface determined by electron density

No empirical parameters

• Electrons: quantum particles that follow the slowernuclear motion

Car-Parrinello AIMD: a single equation of motion with fictitious electronicdegrees of freedom, to keep electrons in the ground state during thenuclear dynamics

Simulated systemSimulated system

Water layer

Protein: poly-Serine b-sheetProtein: poly-Serine b-sheet

Surface: Au(111)4 layers; 23x7 supercell; unreconstructed

Interstitial water layer

3D periodic boundary conditions

In total: # atoms = 587; # electrons = 2552

Simulated systemSimulated system

Why polySerine?• Serine (and other hydroxilated AA) appearsin experimental gold binding peptides (GBP)• Redundancy improves averaging

Why b-sheet?• Maximize contact with the surface• Allow easy implementation of periodicboundary condition

Details of the calculationsDetails of the calculations

ab initio Car-Parrinello molecular dynamics

xc: PBE, PW basis set (Ecut=25 Ry ), ultrasoft pseudopotential

CODE = cp.x (quantum espresso package)

Running machine = MareNostrumMareNostrum (Barcelona, Spain) ): DEISA project Running machine = MareNostrumMareNostrum (Barcelona, Spain) ): DEISA project

Total CPU time = 350 000 CPU hours.

Bloechl-Parrinello thermostat for electrons

20 ps of simulated evolution at T= 400K; time step dt=0.17 fs

OutlineOutline

• Motivations



• Summary

Main resultsMain results

• Polyser and water has a weak but notnegligible interaction with on Au(111).

• Protein and water recognize the atomiccorrugation of the gold surface.

• Protein+hydration layer creates an object withwell-defined geometric properties

Small charge transfer to AuSmall charge transfer to Au

e- population per Au atom(superpos. of all Au at all snapshots)

e- popul. per Ser side chain O(superpos. of all O at all snapshots)

öw

din

po

p.

öw

din

po

p.

External Au layers haveexcess negative charge

Lö

wd

inp

op

.

Lö

wd

inp

op

.

Small charge transfer to AuSmall charge transfer to Au

e- population per Au atom(superpos. of all Au at all snapshots)

e- popul. per water O atom(superpos. of all O at all snapshots)

öw

din

po

p.

öw

din

po

p.

External Au layers haveexcess negative charge

Lö

wd

inp

op

.

Lö

wd

inp

op

.

Orbital mixing?Orbital mixing?

Non-interacting

Projected density of states for serineP

DO

S(a

.u.)

Interacting

red Oblack tot

occupied virtualenergy (eV)

PD

OS

(a.u

.)

Simplifying the system: a singleSimplifying the system: a singlemethanol molecule on Au(111)methanol molecule on Au(111)

occupied virtual

side chain model

Eint= -12 kJ/mol

• Small but detectable O-to-Au charge transfer

• Small but detectable perturbation of PDOS.

• However, interaction is weak, as in experiments*

(small interaction energy; protein and water slide onthe surface)

*water: Kay et al., JCP 1989serine: Peelle et al. Langmuir 2005

How to describe relative AuHow to describe relative Au--OOpositions?positions?

1

( )AuO O AuAu OAu O

gN N

In-plane pair distribution function:

Au OAu O

Meaning: where atoms O sit w.r.t. an atom Au, averaged onall the Au atom and projected on the surface plane.

gAuO averages over the exposed Au and O atoms -> takesadvantage of the redundancy in our system

color scale: gAuOser(x,y):where Oser sits w.r.t. Au atom,

averaged on Au atoms andprojected on the surface

max

The protein recognizes the atomicThe protein recognizes the atomicstructure of the gold surfacestructure of the gold surface

Oser prefers one adsorption site over the others

0

The same for water...The same for water...

max

Owat prefer one adsorption site over the others

0

• Polyser and water “are aware” of the atomicstructure of the surface.

• Oser localize in bridge sites; Owat localize ontop sites

O watO ser

Effects of missing longEffects of missing long--rangerangedispersion?dispersion?

• GGA xc functionals do not correctly describe long-range dispersion

• No direct estimate of effects of long-range dispersion• No direct estimate of effects of long-range dispersionin our system

• However: for related systems (rare gases on metals):– on-top is the preferred adsorption site

– for tested cases, adsorption site preferences are notmodified by adding dispersion

Effects of dispersion on adsorptionEffects of dispersion on adsorptiongeometries of rare gases on metalsgeometries of rare gases on metals

•Calc

•Exp

top and bridge

Bruch et al.Rev. Mod. Phys. 2007

Profiles of atomic densitiesProfiles of atomic densities

Profiles of atomic densitiesProfiles of atomic densities

The solvent andgold exposedprotein surfacesprotein surfacesinclude a solventlayer

Hydration layersHydration layers

•Hydration layer exchanges with the solution•Hydration water is structured

The surfaces of the hydrated proteinThe surfaces of the hydrated protein

density map of WAT Oxygen in the hydration layers

max

0

The surfaces of the hydrated proteinThe surfaces of the hydrated protein

SER Oxygens not distinguishable by Water Oxygens

max

0

• Protein and water recognize the surface

• Hydration water is (dynamically) bound to theprotein in well-defined positions (similar toantifreeze proteins )antifreeze proteins Nuts et al. JACS 2008)

• In spatial matching between the protein andthe surface, hydration water may play a role

SummarySummary

• Specific protein-inorganic surface interactions arepromising for several nanobiotechnology applications

• Basic principles regulating such interactions are notunderstood; High level calculations can shed light onthemthem

• Main results of ab initio simulation:1. Polyser and water do not chemisorb on Au(111). However, a

weak interaction is indeed present.

2. Protein and water recognize the atomic corrugation of the goldsurface.

3. Protein+hydration layer creates an object with well-definedgeometric properties

AcknowledgmentsAcknowledgments

Exp

validation

G. Schreiber

E. Molinari, F. Iori, M. Siwko, F. DeRienzo, A. Calzolari, A. Catellani, R. DiFelice@MODENA: QM

K. Gottschalk, M. Hoefling @LMU:Classical MD


validation

validation

G. SchreiberO. CohaviD. Reichman

A. VaskevitchI. RubinsteinA. B. TeslerO. Kedem

T. Karakouz

@WEIZMANN

R. Wade, B.Huang, D.Kokh,P. Winn@EML: BD

Classical MD

SIXTH FRAMEWORKPROGRAMME


• Computational time and assistance with calculations

• Funding: SIXTH FRAMEWORKPROGRAMME


• Computational time and assistance with calculations

• Funding: SIXTH FRAMEWORKPROGRAMME

Thank you for your attention!

The same for water...The same for water...

max

Owat prefer one adsorption site over the others

0

on-top site

hollow site

bridge site

AuAu--O distribution functions:O distribution functions:Classical system setClassical system set--up vs ab initio runup vs ab initio run

Duringsystemset up

Ab initiorun

SER Oxygen WAT Oxygen

Effects of missing van der Waals onEffects of missing van der Waals onadsorption geometryadsorption geometry

•Calc

•Exp

top and bridge

Bruch et al.Rev. Mod. Phys. 2007

The trajectoryThe trajectory

Only water molecules between the protein and the surface are shown

A single water molecule on Au(111)A single water molecule on Au(111)

HOMO at Goccupied virtual

Modelling protein Modelling protein-surface interactions: a surface ...

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