Circular Dichroism Most protein secondary structure studies use CD - - PowerPoint PPT Presentation

Circular Dichroism

• Most protein secondary structure studies

use CD

• Method is bandshape dependent. Need a

different analysis

• Transitions fully overlap, peptide models

are similar but not quantitative

• Length effects left out, also solvent shifts
• Comparison revert to libraries of proteins
• None are pure, all mixed

UV-vis Circular Dichroism Spectrometer

JASCO–quartz prisms disperse and linearly polarize light Xe arc source Double prism Monochromator (inc. dispersion,

• dec. scatter, important in uv)

PEM quartz PMT Sample Slits

This is shown to provide a comparison to VCD and ROA instruments

poly-L-glu(α,____), poly-L-(lys-leu)(β,- − - −), L-ala2-gly2(turn, . . . . . )

Polypeptide Circular Dichroism

• rdered secondary structure types

Δε λ

Critical issue in CD structure studies is SHAPE of the Δε pattern α-helix β-sheet turn

Brahms et al. PNAS, 1977

Protein Circular Dichroism

Myoglobin-high helix (_______), Immunoglobin high sheet (_______) Lysozyme, a+b (_______), Casein, “unordered” (_______),

ΔA

UIC Basis set - 22 proteins ECD

Wavelength [nm]

180 200 220 240 260

Δε

10

α

W a v e l e n g t h [ n m ] 1 8 0 2 0 0 2 2 0 2 4 0 2 6 0 correlation coefficient r

3D surface obtained by fitting the set of ECD spectra with polynomial Correlation coefficients of the polynomial fit of the ECD spectral intensity as the function of α-helical FC .

2D CORRELATION SPECTRA 2D CORRELATION SPECTRA -

• ECD

ECD

2D CORRELATION SPECTRA 2D CORRELATION SPECTRA -

• ECD

ECD

Synchronous correlation map of the protein ECD spectra with respect to α-helix FC perturbation. Positive contours : blue/cyan, negative contours: red/pink.

Simplest Analyses – Single Frequency Response

Basis in analytical chemistry Beer’s law response if isolated Protein treated as a solution % helix, etc. is the unknown

Standard in IR and Raman,

Method: deconvolve to get components Problem – must assign component transitions, overlap

• secondary structure components disperse freq.

Alternate: uv CD - helix correlate to negative intensity at

222 nm, CD spectra in far-UV dominated by helical contribution Problem - limited to one factor,

• interference by chromophores]

Single frequency correlation of Δε with FC helix

FC helix [%]

20 40 60 80

Δε at 222nm/193 nm

10

θ(222 nm) vs FC helix θ(193 nm) vs FC helix

BETA-LACTOGLOBULIN

• Mw 18,400 Da, 162 residues
• Primarily β-sheet (42% sheet, 16% helix)
• High propensity for helical conformation
• Structural homolgy to retinol binding protein

wavelength (nm)

180 200 220 240 260

• 6
• 4
• 2

2 4 6 8

Δε (M-1cm-1)

0 mM 3 mM

} 5 - 50 mM Far-UVCD spectra of BLG titrated with SDS (0-50 mM)

wavelength (nm)

260 280 300 320

Δε (M-1cm-1)

• 0.0020
• 0.0015
• 0.0010
• 0.0005

0.0000 0.0005 0 mM 0.1 mM 1.0 mM 3, 5 mM

Near-UVCD spectra of BLG titrated with SDS

[SDS] (mM)

10 20 30 40 50

Secondary Structure (%)

10 15 20 25 30 35 40 sheet helix Critical Micelle Concentration (8.2 mM)

PC/FA determined secondary structure change

Problem of Secondary Structure Definition

• where do segments begin and end
• what are turns, bends, etc.
• what is basis for helix or sheet -

φ,ψ or H-bond pattern?

• sources:

X-ray report - non-uniform (visual) Levitt-Greer - Cα relationships dominate Kabsch-Sander - H-bond patterns dominate (DSSP) Frishman-Argos - “knowledge-based” (STRIDE) King-Johnson - CD oriented

Problem of secondary structure definition No pure states for calibration purposes

? ? ? ?

helix sheet

Where do segments begin and end?

Need definition:

Kabsh-Sander (DSSP)

20 40 60 80

KJ or AF

20 40 60 80

Kabsh-Sander (DSSP)

20 40

KJ or AF

20 40

Kabsh-Sander (DSSP)

5 10 15 20 25 30

KJ or AF

20 40

Kabsh-Sander (DSSP)

20 40 60

KJ or AF

20 40 60

King-Johnson Frishman-Argos (STRIDE)

Helix Turn Sheet Other

Comparison of secondary structure definitions:

Comparison with DSSP (Kabsh-Sander):

Next step - project onto model spectra –Band shape analysis

Peptides as models

• fine for α-helix,
• problematic for β-sheet or turns - solubility and stability
• old method:Greenfield - Fasman --poly-L-lysine, vary pH

θi = aiφα +biφβ + ciφc

• -Modelled on multivariate analyses

Proteins as models - need to decompose spectra

• structures reflect environment of protein
• spectra reflect proteins used as models

Basis set (protein spectra) size and form - major issue

Freedom from model spectra

Series of methods developed assuming:

• spectral response was (fully) related to the secondary structure
• sampling structures with sufficient proteins creates a spectral basis

Milestones:

• Provencher - Glockner --(CONTIN) - ridge regression, no intermediate
• Hennessey - Johnson -- Single value decomposition (SVD)

initial step is same as principle component or Factor analysis simplifies spectral variation - monitor component loadings 5 factors (independent component spectra) Fractional structure from (total)inversion of SVD result A = USVT F = XA X = F(VS’UT) Modifications: Project out model spectra (Compton -Johnson) Variable selection - optimize basis (Manavalan-Johnson) permits analysis of why proteins are outliers.

Variations on a Theme

• Self-consistent methods - Sreerama - Woody - (SELCON) –

probably the most widely used now, Web site connect

• Restricted multiple regression (RMR) of Factor Analysis loadings

Pancoska - Keiderling (et al.) applied to many spectral types

• Factor analysis is general - same as SVD

build correlation matrix of all experimental spectra, diagonalize to get eigenvalues, eigenvectors yielding weights (singular values), loadings and components Useful for analysis of spectral variation with structural variation

• Quantitative Secondary Structure application:

Spectral shape and intensity is influenced by many factors

• eg. solvent, pH, sequence, secondary structure, chromophore

RMR idea is to find spectral components sensitive to structure

Factor Analysis Method

Decomposition of an experimental spectrum θ(λ) into linear combination of independent component spectra φj(λ):

∑ ∑

= =

= =

p j j ij i p j j ij i

c A C

1 1

) ( ) ( ) ( λ φ λ φ λ θ

where

∫

=

2 1

) (

2 λ λ

λ λ θ d A

i i

ij ij c

C /

“norm”

) (λ φj

“loadings (expansion coefficients)” “component spectra”

• 1. Construct Correlation Matrix [R]:

)] ( [ )] ( [ ] [ λ λ

i T i

w w R =

, where

∑

=

= =

p j j ij i i i

c A w

1

) ( ) ( 1 ) ( λ φ λ θ λ

Factor Analysis Method

• 2. Diagonalize [R] to obtain Principal Components:

(normalized spectral data)

] [ ] ][ [ ] [

ij ij T

q R q δ Λ =

• 3. Calculate component spectra and corresponding loadings (coefficients):

] )][ ( [ )] ( [ q wj

j

λ λ φ =

T ij

q c ] [ ] [ =

and

FA component spectra - 22 proteins ECD

Wavelength [nm]

180 200 220 240 260

Δεnormalized

φ1 φ2 φ3 φ4 φ5

Factor (Principle Component) Analysis

• Approach is functionally equivalent to Principle Component

Analysis - Singular Value Decomposition – No curve fitting is necessary – Band assignments are not necessary – Method is general - any technique

• Method:

– treat set of protein spectra as basis set of functions, [φ] – Diagonalize the co-variance matrix to

• find most common elements- ψ1
• find most common deviation - ψ2
• continue

– Reconstruct Spectra: [φ] = [ψ][α], where [α] is a matrix of coefficients, cij for ith protein and jth subspectrum – Use vector of cij for protein i to characterize protein. Note ψi depends on training set, construct to be orthogonal

• 6 β

β sheet , 2 )

Tyr97 Tyr25 Tyr92 H1 H3 H2 Tyr76 Tyr115 Tyr73

• 124 amino acid residues, 1 domain, MW= 13.7 KDa
• 3 α-helices
• 6 β-strands in an AP β-sheet
• 6 Tyr residues (no Trp), 4 Pro residues (2 cis, 2 trans)

Ribonuclease A combined uv-CD and FTIR study

W a v e l e n g t h ( n m )

2 6 0 2 8 0 3 0 0 3 2 0

Ellipticity (mdeg)

• 1 6
• 1 4
• 1 2
• 1 0
• 8
• 6
• 4
• 2

N e a r - U V C D

W a v e n u m b e r ( c m

• 1 )

1 6 0 0 1 6 2 0 1 6 4 0 1 6 6 0 1 6 8 0 1 7 0 0 1 7 2 0

Absorbance

0 . 0 0 0 . 0 1 0 . 0 2 0 . 0 3 0 . 0 4 0 . 0 5 0 . 0 6

F T I R

W a v e l e n g t h ( n m )

1 9 0 2 0 0 2 1 0 2 2 0 2 3 0 2 4 0 2 5 0

Ellipticity (mdeg)

• 1 5
• 1 0
• 5

5

F a r - U V C D

Temperature 10-70oC

FTIR—amide I

Loss of β-sheet

RibonucleaseA

Far-uv CD

Loss of α-helix

Near –uv CD

Loss of tertiary structure Spectral Change

Stelea, et al. Prot. Sci. 2001

C

i1 (x10 2)

• 8 . 0
• 7 . 6
• 7 . 2
• 6 . 8
• 6 . 4
• 1 . 0
• 0 . 5

0 . 0 0 . 5 1 . 0

F T I R

C

i1

• 1 7
• 1 5
• 1 3
• 1 1
• 9
• 7
• 5

C

i2

• 1 5
• 1 0
• 5

5 1 0

N e a r - U V C D

2 0 4 0 6 0 8 0 1 0 0

C

i1

• 1 3
• 1 2
• 1 1
• 1 0

C

i2

• 3 0
• 2 5
• 2 0
• 1 5
• 1 0
• 5

5

F a r - U V C D

Ribonuclease A

PC/FA loadings

• Temp. variation

FTIR (α,β) Near-uv CD (tertiary) Far-uv CD (α-helix)

Pre-transition - far-uv CD and FTIR, not near-uv Temperature

Stelea, et al.

• Prot. Sci. 2001

Changing protein conformational order by organic solvent

TFE and MeOH often used to induce helix formation

• -sometimes thought to mimic membrane
• -reported that the consequent unfolding can lead to

aggregation and fibril formation in selected cases Examples presented show solvent perturbation of dominantly β-sheet proteins TFE and MeOH behave differently thermal stability key to differentiating states indicates residual partial order

β-lactoglobulin--pH and TFE , MeOH

TFE and MeOH both induce helix at both pH 7 and 2

FTIR vs. time MeOH mix

Factor analysis - 2nd component loading shows loss of sheet with time, double exp.

Xu&Keiderling, Adv.Prot.Chem.2002

Concanavalin A pH, TFE and MeOH

native TFE MeOH normalizes β-sheet ECD, FTIR indicates aggregated TFE induces helix

Xu&Keiderling, Biochem, 2005

Lipid-induced Conformational Transition of β-Lactoglobulin: Equilibrium and Kinetic Studies

Globular protein with 9-stranded sheet (flattened β-barrel) and one helical segment Terminal segments have high helical propensity Good model for β-to-α conversion Binding to lipid vesicle acts as perturbation—cell model

Xiuqi Zhang, Ning Ge,TAK Biochemistry 2006/2007

1 2 3 4 5 0.1 0.2 0.3 0.4 0.5

B

pH 6.8

β-Sheet α-Helix

Unordered

Fractional secondary structure DMPG / mM

BLG Binding to DMPG at pH 6.8: Circular Dichroism

• β-sheet to α–helix transition, dependence on DMPG

Secondary structure: Binding DMPG at pH6.8, causes BLG conformational change. The α–helix formed with loss of β-sheet. 2nd struct. analyses

190 200 210 220 230 240 250

• 15
• 10
• 5

5 10 15 20 25

pH 6.8

DMPG/mM

[θ]×10-3/deg.cm2.dmol-1 Wavelength/nm

2 4 6 8 10

• 12
• 10
• 8
• 6
• 4

A

[θ]222nm×10-3/deg.cm2.dmol-1

0.0 0.1 0.2 0.3 0.4

• 11
• 10
• 9
• 8
• 7
• 6
• 5

Effect

• f

Charge: Addition of neutral lipid (DMPC) decreases lipid charge and α–helix in BLG:DMPG mixture (left). So negative charge

• f lipid is necessary for

the formation of α–helix (right).

20 40 60 80 100

0.1 0.2 0.3 0.4 0.5

pH6.8

Unordered

β-sheet α-Helix

Second structural fraction DMPG / (DMPC+DMPG) / %

BLG in varying DMPG / DMPC mixture

Effect of lipid charge:

• How does the charge of lipid affect protein binding?
• Const. Lipidtotal=1.8mM

vary charge

(-)

Xiuqi Zhang, TAK Biochemistry 2006

Orientation of BLG into lipid membrane:

• Polarized ATR-FTIR spectra of DMPG-bound BLG

3 0 0 0 2 9 0 0 1 8 0 0 1 7 0 0 1 6 0 0 1 5 0 0 1 4 0 0 1 3 0 0

helix sheet

CH2 str

CH2 scis

amide I

Summary βLG: Orientation of protein segments

Some portions of BLG inserted into bilayer. The positive amide I peaks at 1654 and 1637 cm-1 suggest that α-helices have a preferred orientation perpendicular to the membrane surface, and β-sheets are probably not inserted, at both pHs. Current studies – Ning Ge various membrane systems

Dynamics--Scheme of Stopped-flow System

Denatured protein solution Refolding buffer solution

• add dynamics to experiment

Stopped-flow ECD and Fluorescence of acid denatured Cyt c refolding by neutralization with phosphate buffer

Without salt With 0.5M salt

Log plot--Three components One component Fluores ECD

Xu & Keiderling, Proteins 2006

T = 15oC

VIBRATIONAL OPTICAL ACTIVITY VIBRATIONAL OPTICAL ACTIVITY

Differential Interaction of a Chiral Molecule with Left and Right Circularly Polarized Radiation During Vibrational Excitation

VIBRATIONAL CIRCULAR DICHROISM RAMAN OPTICAL ACTIVITY

Differential Absorption of Left and Right Differential Raman Scattering of Left Circularly Polarized Infrared Radiation and Right Incident and/or Scattered Radiation

Combining Techniques: Vibrational CD

“CD” in the infrared region

Probe chirality of vibrations goal stereochemistry Many transitions / Spectrally resolved / Local probes Technology in place -- separate talk Weak phenomenon - limits S/N / Difficult < 700 cm-1 Same transitions as IR same frequencies, same resolution Band Shape from spatial relationships neighboring amides in peptides/proteins Relatively short length dependence AAn oligomers VCD have ΔA/A ~ const with n vibrational (Force Field) coupling plus dipole coupling Development -- structure-spectra relationships Small molecules – theory / Biomolecules -- empirical, Recent—peptide VCD can be simulated theoretically

G C F M2 S M1 PEM P SC L D

D Pre- Amp Dynamic Normalization Tuned Filter ωΜ Lock-in ωC Lock-in Chopper ref. ωC PEM ref. ωM Transmission Feedback Lock-in A/D Interface Computer Interface Monochromator

UIC Dispersive VCD Schematic

Electronics Optics and Sampling

Yes it still exists and measures VCD!

UIC FT-VCD

Schematic

(designed for magnetic VCD commercial

• nes simpler)

Electronics Optics FTIR

Separate VCD Bench

Polarizer PEM (ZnSe) Sample Detector (MCT)

Optional magnet

lock-in amp filter PEM ref detector FT-computer

Large electric dipole transitions can couple over longer ranges to sense extended conformation

Simplest representation is coupled oscillator

Tab μa μb

Real systems - more complex interactions

• but pattern is often consistent

( )

b a ab

T c μ μ ν r r r m × ⋅ ⎟ ⎠ ⎞ ⎜ ⎝ ⎛ =

±

2 π R

Dipole coupling results in a derivative shaped circular dichroism

Δε = εL−εR λ

Selected model Peptide VCD, aqueous solution

W a v e n u m b e r s ( c m - 1 )

1 4 5 0 1 5 0 0 1 5 5 0 1 6 0 0 1 6 5 0 1 7 0 0 1 7 5 0

VCD (A. U.)

• 1 0

1 0 2 0 3 0 h e l i x β - s t r u c t u r e r a n d o m c o i l

Amide I Amide II α β coil ΔA

VCD Example: α- vs. the 310-Helix

i, i+4 ← H-bonding → i, i+3 3.6 ← Res./Turn → 3.0 2.00 ← Trans./Res (Å) → 1.50

α-Helix 310-Helix

Wavenumbers (cm-1) 1400 1600 1800 Absorbance 1 2 3 4 Wavenumbers (cm-1) 140 1600 1800 ΔA (A.U.)

• 100

100 200 300 400 500

α-helical (Aib-Ala)6 Ala(AibAla)3 310-helical

The VCD success example: 3 The VCD success example: 310

10-

• helix vs.

helix vs. α α-

• helix

helix

Relative shapes of multiple bands distinguish these similar helices

Aib2LeuAib5 (Met2Leu)6

α 310 mixed i−>i+3 i−>i+4

Silva et al. Biopolymers 2002

Biphenyl bridged residues ( Biphenyl bridged residues (Bip Bip) )

CD and IR difficult to get structure CD and IR difficult to get structure

CD—all biphenyl Amide A shows H-bond form

Toniolo, co-workers JACS 2004

Biphenyl bridged residues (Bip) show inversion

Figure 1 VCD (upper frame) and IR absorption (lower frame) spectra of Ac-(Bip)3-L-Val-OMe (full lines) and Boc-L-Val-(Bip)4-OtBu (dashed lines). Spectra of Ac-(Bip)3-L-Val- OMe were measured in 46/11 (v/v) CDCl3/TFE-OH and Boc-L-Val- (Bip)4-OtBu in CDCl3 solution using the cell pathlength 500 μm and peptide concentration of 9.5 and 8.6 g/L, respectively.

Ac-(Bip)3-L-Val-OMe (_________) left-handed Boc-L-Val-(Bip)4-OtBu (-------) right-handed (310-helix)

Toniolo, co-workers JACS 2004

Vibrational spectrum separates aromatic and amide transitions

Tiffany and Krimm in 1968 noted similarity of Proline II and poly-lysine ECD and suggested “extended coil” Problem -- CD has local sensitivity to chiral site

• -IR not very discriminating

Nature of the peptide random coil form

Dukor and Keiderling 1991 with ECD, VCD, and IR showed Pron oligomers to have characteristic random coil spectra Suggests -- local order, left-handed turn character

• - no long range order in random coil form

Same spectral shape found in denatured proteins, short

• ligopeptides, and transient forms

Dukor, Keiderling - Biopoly 1991

Reference: Poly(Lys)

• coil, pH 7

ECD of Pron oligomers

Greenfield & Fasman 1969

Builds up to Poly-Pro II

frequency --> tertiary amide helix sheet

coil

Single amide

Dukor, Keiderling - Biopoly 1991

Relationship to “random coil” - compare Pron and Glun

IR ~ same, VCD - same shape, half size -- partially ordered

Thermally unfolding “random coil” poly-L-Glu -IR, VCD T = 5oC (___) 25oC (- - -) 75oC (-.-.-) VCD loses magnitude IR shifts frequency “random coil” must have local order

• Keiderling. . . Dukor, Bioorg-MedChem 1999

ΔA (x105)

• 8
• 4

4 1580 1620 1660

ΔA (x105)

• 8
• 4

4 1580 1620 1660

5 deg 10 deg 15 deg 20 deg 25 deg 30 deg 35 deg 40 deg 45 deg 50 deg 55 deg 60 deg

Wavenumber [cm-1]

Unlabeled C-terminus N-terminus Middle (N)

Temperature dependent amide I’ VCD of labeled peptides characteristic of site-dependent helix-coil transition. Temperature dependent amide I’ VCD of labeled peptides characteristic of site-dependent helix-coil transition.

Temperature [oC]

10 20 30 40 50 60

Frequency [cm-1]

1643 1645 1647 1649 1651 1653

C-terminus N-terminus Unlabeled

Temperature [oC]

10 20 30 40 50 60

Unlabeled Middle (C) Middle (N)

a b

Frequency shift of 12C amide I’ VCD band minimum with temperature: a) terminal, b) middle labeled. Unlabeled added for comparison. Frequency shift of 12C amide I’ VCD band minimum with temperature: a) terminal, b) middle labeled. Unlabeled added for comparison.

Relative position of isotope labels

Ala-rich peptides (25 mer) with a high propensity for helix formation were synthesized and purified at Mount Holyoke.

13C-labels (on the amide C=O) were incorporated into the

peptide as follows: (red refers to labeled residues)

Unlabel: Ac-AAAAKAAAAKAAAAKAAAAKAAAAY-NH2 2LT: Ac-AAAAKAAAAKAAAAKAAAAKAAAAY-NH2 2L1S: Ac-AAAAKAAAAKAAAAKAAAAKAAAAY-NH2 2L2S: Ac-AAAAKAAAAKAAAAKAAAAKAAAAY-NH2 2L3S: Ac-AAAAKAAAAKAAAAKAAAAKAAAAY-NH2 3LT: Ac-AAAAKAAAAKAAAAKAAAAKAAAAY-NH2 3L1S: Ac-AAAAKAAAAKAAAAKAAAAKAAAAY-NH2 4LT: Ac-AAAAKAAAAKAAAAKAAAAKAAAAY-NH2 4L1S: Ac-AAAAKAAAAKAAAAKAAAAKAAAAY-NH2

An examination of amide coupling

Isotopic labeling-- experiment and theory

Two sequential labels have higher IR freq. due to coupling (intensity in high ν mode), VCD : sequential (2LT) - same sign 12C and 13C, but opposite sign if separated (2L1S) * since exp. in D2O a (-)VCD band develops the amide I, not modeled without solvent

IR VCD

*

13C 13C 13C 13C A*A* vs. A*AA* A*A* vs. A*AA*

Nucleic Acid VCD

• Wieser and co-workers (Calgary) have

made much progress with model systems, including metal interactions and drug binding

• Here give examples of basic spectral

response

• 1

base deformations sym PO2- stretches

VCD of DNA, vary A-T to G-C ratio

big variation little effect

A

Z B

B

B, A Z

DNA VCD of PO2

• modes in B- to Z-form transition

Experimental Theoretical

Triplex DNA, RNA form by adding third strand

to major groove with Hoogsteen base pairing

• 20

CGC+ Wavenumber (cm-1)

VCD of Triplex formation—base modes

Protein VCD

• Protein CD has been used to develop

secondary stucture algorithms (Pancoska et al.) and to follow folding and unfolding processes.

• Due to complexity of the structue and S/N

limitations, more quantiative work has been done with peptides

A

1 5 0 0 1 5 5 0 1 6 0 0 1 6 5 0 1 7 0 0

H E M L Y S C O N

ΔA CON

Wavenumbers (cm -1) 1500 1550 1600 1650 1700 HEM LYS

VCD in H2O FTIR in H2O

Wavenumbers (cm-1)

α β α/β

Comparison of Protein VCD and IR

VCD of amide I’, I+II an III regions in selected proteins

High helix High sheet Mixed CAS- unstructured

VCD Example: α-Lactalbumin and Lysozyme

• Homologous

proteins

• Similar crystal

structures

• Lysozyme VCD

spectra is not the same as that of α-Lac ฀α-Lac stabilize by Ca+2 needs to bind a co- protein, so flexible (d ) α-Lactalbumin Lysozyme