Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction...

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Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A T I V E B I O I N F O R M A T I C S V U E
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Transcript of Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction...

Page 1: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Experimentally solving protein structures and protein-protein

interactions

Lecture 21

Introduction to Bioinformatics2007

CENTR

FORINTEGRATIVE

BIOINFORMATICSVU

E

Page 2: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Today’s lecture

1. Experimental techniques for determining protein tertiary structure

2. Protein interaction and dockingi. Ribosome example

ii. Zdock method

3. Molecular motion simulated by molecular mechanics

Page 3: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

If you throw up a stone, it is Physics.

Page 4: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

If you throw up a stone, it is Physics. If it lands on your head, it is Biophysics.

Page 5: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

If you throw up a stone, it is Physics. If it lands on your head, it is Biophysics.

If you write a computer program, it is Informatics.

Page 6: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

If you throw up a stone, it is Physics. If it lands on your head, it is Biophysics.

If you write a computer program, it is Informatics. If there is a bug in it, it is Bioinformatics

Page 7: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Experimentally solving protein structures

Two basic techniques:

1. X-ray crystallography

2. Nuclear Magnetic Resonance (NMR) tchniques

Page 8: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

1. X-ray crystallography

Purified protein

Crystal

X-ray Diffraction

Electron density

3D structureBiological interpretation

Crystallization

Phase problem

Page 9: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Protein crystals• Regular arrays of protein molecules

• ‘Wet’: 20-80% solvent• Few crystal contacts

• Protein crystals contain active protein• Enzyme turnover• Ligand binding

Example of crystal packing

Page 10: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Examples of crystal packing

2 Glycoprotein I~90% solvent (extremely high!)

Acetylcholinesterase~68% solvent

Page 11: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Problematic proteins (no crystallisation)

• Multiple domains

• Similarly, floppy ends may hamper crystallization: change construct

• Membrane proteins

• Glycoproteins

Flexible

Lipid bilayer

hydrophilic

hydrophilic

hydrophobic

Flexible and heterogeneous!!

Page 12: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Experimental set-up• Options for wavelength:

– monochromatic, polychromatic – variable wavelength

Liq.N2 gas stream

X-ray source

detector

goniometer

beam stop

Page 13: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Diffraction imageDiffraction image

Water ring

Diffuse scattering (from the fibre loop)

reciprocal lattice reciprocal lattice (this case hexagonal)(this case hexagonal)

Beam stop

Increasing resolution

Direct beam

ReflectionsReflections ( (h,k,lh,k,l) ) withwith I( I(h,k,lh,k,l))

Page 14: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

The rules for diffraction: Bragg’s law

• Scattered X-rays reinforce each other only when Bragg’s law holds:

Bragg’s law: 2dhkl sin = n

Page 15: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Phase Problem

• Determining the structure of a molecule in a crystalline sample requires knowing both the amplitude and the phase of the photon wave being diffracted from the sample

• X-rays which are emitted start out with dispersed phases, and so the phases get lost

• Unfortunately, phases contribute more to the informational content of a X-ray diffraction pattern than do amplitudes. It is common to refer to phaseless X-ray data as having "lost phases“

• Luckily, several ways to recover the lost phases have been developed

Page 16: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Building a protein model• Find structural elements:

-helices, -strands• Fit amino-acid sequence

Page 17: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Building a protein model• Find structural elements:

-helices, -strands• Fit amino-acid sequence

Page 18: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Effects of resolution on electron density

Note: map calculated with perfect phases

d = 4 Å

Page 19: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

d = 3 Å

Effects of resolution on electron density

Note: map calculated with perfect phases

Page 20: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

d = 2 Å

Effects of resolution on electron density

Note: map calculated with perfect phases

Page 21: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

d = 1 Å

Effects of resolution on electron density

Note: map calculated with perfect phases

Page 22: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Refinement process

• Bad phases poor electron density map

errors in the protein model

• Interpretation of the electron density map improved model

improved phases improved map

even better model

… iterative process of refinement

Page 23: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Validation

• Free R-factor (cross validation)– Number of parameters/

observations• Ramachandran plot • Chemically likely (WhatCheck)

– Hydrophobic inside, hydrophilic outside

– Binding sites of ligands, metals, ions

– Hydrogen-bonds satisfied– Chemistry in order

• Final B-factor (temperature) values

Page 24: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

2. Nuclear Magnetic Resonance (NMR)

800 MHz NMR spectrometer

Page 25: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Nuclear Magnetic Resonance (NMR)

• Pioneered by Richard R. Ernst, who won a Nobel Prize in chemistry in 1991, FT-NMR works by irradiating the sample, held in a static external magnetic field, with a short square pulse of radio-frequency energy containing all the frequencies in a given range of interest.

• The polarized magnets of the nuclei begin to spin together, creating a radio frequency (RF) that is observable. Because the signals decays over time, this time-dependent pattern can be converted into a frequency-dependent pattern of nuclear resonances using a mathematical function known as a Fourier transformation, revealing the nuclear magnetic resonance spectrum.

• The use of pulses of different shapes, frequencies and durations in specifically-designed patterns or pulse sequences allows the spectroscopist to extract many different types of information about the molecule.

Page 26: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Nuclear Magnetic Resonance (NMR)• Time intervals between pulses allow—among other things—magnetization

transfer between nuclei and, therefore, the detection of the kinds of nuclear-nuclear interactions that allowed for the magnetization transfer.

• Interactions that can be detected are usually classified into two kinds. There are through-bond interactions and through-space interactions. The latter usually being a consequence of the so-called nuclear Overhauser effect (NOE). Experiments of the nuclear-Overhauser variety may establish distances between atoms.

• These distances are subjected to a technique called Distance Geometry which normally results in an ensemble of possible structures that are all relatively consistent with the observed distance restraints (NOEs).

• Richard Ernst and Kurt Wüthrich —in addition to many others— developed 2-dimensional and multidimensional FT-NMR into a powerful technique for the determination of the structure of biopolymers such as proteins or even small nucleic acids.

• This is used in protein nuclear magnetic resonance spectroscopy. Wüthrich shared the 2002 Nobel Prize in Chemistry for this work.

Page 27: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Gly

Gly

AspAsn

Asp

Phe

ThrSer

Leu

Val

2D NOESY spectrum

• Peptide sequence (N-terminal NH not observed)• Arg-Gly-Asp-Val-Asn-Ser-Leu-Phe-Asp-Thr-Gly

Page 28: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

NMR structure determination: hen lysozyme

• 129 residues– ~1000 heavy atoms– ~800 protons

• NMR data set– 1632 distance restraints– 110 torsion restraints– 60 H-bond restraints

• 80 structures calculated• 30 low energy

structures used 0

2000

4000

6000

8000

1 10 4

1.2 10 4

10 20 30 40 50 60 70

Tot

al e

nerg

y

Structure number

Page 29: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Solution Structure Ensemble

• Disorder in NMR ensemble– lack of data ?– or protein dynamics ?

Page 30: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Problems with NMR

• Protein concentration in sample needs to be high (multimilligram samples)

• Restricted to smaller sized proteins (although magnets get stronger)

• Uncertainties in NOEs introduced by internal motions in molecules (preceding slide)

Page 31: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

X-ray and NMRsummary

• Are experimental techniques to solve protein structures (although they both need a lot of computation)

• Nowadays typically contain many refinement and energy-minimisation steps to optimise the structure (next topic)

Page 32: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

X-ray and NMRsummary (Cntd.)

• X-ray diffraction– From crystallised protein sample to electron

density map• Structure descriptors: resolution, R-factor, B-factor

• Nuclear magnetic resonance (NMR)– Based on atomic nuclear spin – Produces set of distances between residues

(distance restraints)– Distances are used to build protein model using

Distance Geometry (a technique to build a protein structure using a set of inter-residue distances)

Page 33: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Protein binding and protein-protein interactions

• Complexity:– Multibody interaction

• Diversity:– Various interaction types

• Specificity:– Complementarity in shape and binding

properties

Page 34: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Protein-protein interactions• Many proteins interact through

hydrophobic patches

• Hydrophobic patches often have a hydrophilic rim

• The patch-rim combination is believed to be important in providing binding specificity

hydrophobic

very hydrophilic

hydrophilic

Page 35: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

PPI Characteristics• Universal

– Cell functionality based on protein-protein interactions• Cyto-skeleton• Ribosome• RNA polymerase

• Numerous– Yeast:

• ~6.000 proteins• at least 3 interactions each~18.000 interactions

– Human:• estimated ~100.000 interactions

• Network– simplest: homodimer (two)– common: hetero-oligomer (more)– holistic: protein network (all)

Page 36: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Interface Area• Contact area

– usually >1100 Å2

– each partner >550 Å2

• each partner loses ~800 Å2 of solvent accessible surface area– ~20 amino acids lose ~40 Å2

– ~100-200 J per Å2

• Average buried accessible surface area:– 12% for dimers– 17% for trimers– 21% for tetramers

• 83-84% of all interfaces are flat• Secondary structure:

– 50% -helix– 20% -sheet– 20% coil– 10% mixed

• Less hydrophobic than core, more hydrophobic than exterior

Page 37: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Complexation Reaction

• A + B AB

– Ka = [AB]/[A]•[B] association

– Kd = [A]•[B]/[AB] dissociation

Page 38: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Experimental Methods for determining PPI• 2D (poly-acrylamide) gel electrophoresis mass spectrometry• Liquid chromatography

– e.g. gel permeation chromatography• Binding study with one immobilized partner

– e.g. surface plasmon resonance• In vivo by two-hybrid systems or FRET• Binding constants by ultra-centrifugation, micro-calorimetry or

competition• Experiments with labelled ligand

– e.g. fluorescence, radioactivity• Role of individual amino acids by site directed mutagenesis• Structural studies

– e.g. NMR or X-ray

Page 39: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

PPI Network

http://www.phy.auckland.ac.nz/staff/prw/biocomplexity/protein_network.htm

Page 40: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Binding vs. Localization

Obligateoligomers

Non-obligateweak transient

Non-obligatetriggered transient

e.g. GTP•PO4-

Non-obligateco-localised

e.g. in membrane

Non-obligatepermanent

e.g. antibody-antigen

strong

weak

co-expressedand at same place

different places

Page 41: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Some terminology

• Transient interactions:– Associate and dissociate in vivo

• Weak transient:– dynamic oligomeric equilibrium

• Strong transient:– require a molecular trigger to shift the equilibrium

• Obligate PPI:– protomers no stable structures on their own (i.e. they

need to interact in complexes)– (functionally obligate)

Page 42: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Analysis of 122 Homodimers

• 70 interfaces single patched

• 35 have two patches

• 17 have three or more

Page 43: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Interfaces

• ~30% polar

• ~70% non-polar

Page 44: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Interface• Rim is water accessible

riminterface

Page 45: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Interface composition

• Composition of interface essentially the same as core

• But % surface area can be quite different!

= different surface/interface areas

Page 46: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Some preferences

prefer

avoid

Page 47: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Ribosome structure• In the nucleolus, ribosomal RNA is

transcribed, processed, and assembled with ribosomal proteins to produce ribosomal subunits

• At least 40 ribosomes must be made every second in a yeast cell with a 90-min generation time (Tollervey et al. 1991). On average, this represents the nuclear import of 3100 ribosomal proteins every second and the export of 80 ribosomal subunits out of the nucleus every second. Thus, a significant fraction of nuclear trafficking is used in the production of ribosomes.

• Ribosomes are made of a small and a large subunit

Large (1) and small (2) subunit fit together (note this figure mislabels angstroms as nanometers)

Page 48: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Ribosome structure• The ribosomal subunits of prokaryotes and eukaryotes are quite similar

but display some important differences.• Prokaryotes have 70S ribosomes, each consisting of a (small) 30S and a

(large) 50S subunit, whereas eukaryotes have 80S ribosomes, each consisting of a (small) 40S and a bound (large) 60S subunit.

• However, the ribosomes found in chloroplasts and mitochondria of eukaryotes are 70S, this being but one of the observations supporting the endosymbiotic theory.

• "S" means Svedberg units, a measure of the rate of sedimentation of a particle in a centrifuge, where the sedimentation rate is associated with the size of the particle. Note that Svedberg units are not additive.

• Each subunit consists of one or two very large RNA molecules (known as ribosomal RNA or rRNA) and multiple smaller protein molecules. Crystallographic work has shown that there are no ribosomal proteins close to the reaction site for polypeptide synthesis. This suggests that the protein components of ribosomes act as a scaffold that may enhance the ability of rRNA to synthesise protein rather than directly participating in catalysis.

• The differences between the prokaryotic and eukaryotic ribosomes are exploited by humans since the 70S ribosomes are vulnerable to some antibiotics that the 80S ribosomes are not. This helps pharmaceutical companies create drugs that can destroy a bacterial infection without harming the animal/human host's cells!

Page 49: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

70S structure at 5.5 Å

(Noller et al. Science 2001)

Page 50: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

70S structure

Page 51: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

30S-50S interface• Overall buried surface area ~8500 Å2

< 37.5 Å2

37.5 Å2 – 75 Å2

> 75 Å2

Page 52: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Protein-nucleic acid Interactions

Page 53: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Interactions in the Ribosome

Page 54: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Calculating interface areas

Given a complex AB:

1. Calculate Solvent Accesible Surface Area (SASA) of A, of B, and of AB

1. SASA lost upon complex formation is

SASA(A)+SASA(B)-SASA(AB)

3. Interface area of A and of B is

(SASA(A)+SASA(B)-SASA(AB))/2

Page 55: Experimentally solving protein structures and protein-protein interactions Lecture 21 Introduction to Bioinformatics 2007 C E N T R F O R I N T E G R A.

Summary protein(-protein) interactions

• Different binding modes (transient, obligate, also depending on (co)localisation, etc.)

• Hydrophobic patch/hydrophilic rim conferring binding specificity

• Interfaces are physico-chemically positioned in between surface and protein core (amino acid composition, etc.)

• Ribosomes– Small/large subunits, mixture of RNA and protein,

different between prokyarotic and eukaryotic cells (exploited by administering antibiotics), ribosomal protein complexes, protein-RNA binding