Bioinformatics and Molecular Modeling studies of Membrane

Proteins

Shiva Amiri

Problem: Difficult to obtain high resolution crystallographic images of membrane proteins

Structure Determination

Unwin et.al, Nature, 26 June 2003

Getting there?

Some success using cryo-electron microscopy coupled with Fourier Transforms, i.e. Unwin’s 4 Å image of the TM region.

But still no full structure

Unwin et al., Nature, 26 June 2003

My Project

To design structure determination

software for Ligand Gated Ion Channels

(LGICs) i.e. nAChR, GABAA and GABAC receptors, 5HT3 receptor, Glycine receptor

Main focus so far:

The α-7 Nicotinic Acetylcholine Receptor (nAChR)

cationic channel homopentamer four transmembrane regions (M1-M4)

Transmembrane Domain Alignment

Homology modeling – Transmembrane domain

Homology modeling – Transmembrane domain

The homology model of the TM region with the Torpedo Marmorata structure

(PDB: 1OED - 4 Å) and the Chick α-7 sequence using MODELLER

Ligand Binding Domain Alignment

Homology Modeling – Ligand Binding domain

Homology Modeling – Ligand Binding domain

The homology model of the LBD with

Acetylcholine Binding Protein (AChBP) as the structure (PDB: 1I9B – 2.7 Å) and the Chick α-7 sequence using MODELLER

The software …

Combining the Transmembrane domain with the Ligand Binding domain

Failed first attempt: Minimizing distances between target residues in the LBD and the TM domains - 6 degrees of freedom (rotations and translations on all three axes)

- Models were not straight

Second attempt …

New algorithm:

z-axis

b. Align each domain onto the z-axis

a. straighten each domain with respect to the z-axis

c. Rotate and translate about z-axis- angle of rotation and steps of translations are

user- defined

z-axis

Theta (angle of rotation)

Second Attempt continued…

At each rotation and for each translation the Unwin distance, the Termini distance the number of bad contacts is calculated

Scoring Functions

1. Unwin Distance – the distance between residues from the TM domain and the LB domain that are meant to come into close proximity

2. Termini Distance – the distance between the C-terminus of the LB domain and the N-terminus of the TM domain

Scoring Functions continued …

3. Bad Contacts – Number of residues that are closer than a certain cut-off distance (user-defined), currently set to 5 Å

Scoring Functions continued…

Plots of Scoring FunctionsUnwin Distance Termini Distance

Bad contacts

Linear Combinations of Scoring Functions

Unwin + Termini Unwin + Termini + Bad contacts

Choosing the Best Model

Model chosen based on scoring function data

Once a good model was decided on, energy minimization using GROMACS was carried out to ensure the electrochemical legitimacy of the model

Model of the α-7 nAChR

Gaussian Network Model (GNM) Analysis

A course-grained model to approximate molecular motions of proteins

Current code cannot allocate memory for the 1660 residues of the α-7 nAChR

Analysis has been done using the TM domain and the LB domain separately

GNM was also run on one subunit of the model B-values generally in agreement with crystallographic

data but modeled structures are difficult to analyze using present code

AChBP – one subunit

0

20

40

60

80

100

120

140

160

1 16 31 46 61 76 91 106 121 136 151 166 181 196

Number of Residues

B-V

alu

e Series1

Series2

α-7 nAChR Transmembrane

0

50

100

150

200

250

300

350

1 39 77 115 153 191 229 267 305 343 381 419 457 495 533 571 609

Number of Residues

B-v

alu

es

Series1

Series2

α-7 nAChR model – 2 subunits

0

20

40

60

80

100

120

1 43 85 127 169 211 253 295 337 379 421 463 505 547 589 631

Number of Residues

B-v

alu

e

Series1

Series2

CONCOORD Analysis

Generates protein conformations around a given structure based on distance restrictions

Principal Component Analysis (PCA) is applied on the 500 resulting structures from CONCOORD

First eigenvector shows opening and closing of the pore as the subunits rotate

First eigenvector

Eigenvector Plot Covariance lines

Future work… Looking at the hydrophobic girdle (M2) of LGICs to study

patterns of conservation and the behaviour of these residues during gating

Further verification and analysis of models Other models of LGICs

Summary

Software designed to determine structure of LGICs

Structure of α-7 nAChR

Used various methods (GNM, CONCOORD) to look at possible motions using the hypothesized structure

Thanks to:

Prof. Mark S.P. Sansom Sundeep DeolDr. Phil Biggin Yalini PathyDr. Kaihsu Tai Jonathan CuthbertsonDr. Paul Barrett Pete Bond

Jeff CampbellDr. Alessandro Grotessi Katherine CoxDr. Daniele Bemporad Jennifer JohnstonDr. Jorge Pikunic Robert D’RozarioDr. Shozeb Haider Loredana VaccaroDr. Andy Hung John HolyoakeDr. Bing Wu Tony IvetacOliver Beckstein Sylvanna HoSyma Khalid Samantha KayeZara Sands George Patargias

Hydrophobic girdle

M2 alignment

b. Align each domain onto the z-axis

c. Rotate and translate about z-axis- angle of rotation and steps of translations are

user- defined

α-7 nAChR LBD – 3 subunits

0

50

100

150

200

250

300

350

1 37 73 109 145 181 217 253 289 325 361 397 433 469 505 541 577 613

Number of residues

B-v

alu

e Series1

Series2