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Molecular Modelling Studies of the Nicotinic Acetylcholine Receptor. Shiva Amiri Professor Mark S. P. Sansom and Dr. Philip C. Biggin D. Phil. Symposium, October 6, 2005. Ligand binding domain (LB) core of 10 β -strands, forming a β -sandwich

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molecular modelling studies of the nicotinic acetylcholine receptor

Molecular Modelling Studies of the Nicotinic Acetylcholine Receptor

Shiva Amiri

Professor Mark S. P. Sansom and Dr. Philip C. Biggin

D. Phil. Symposium, October 6, 2005

the nicotinic acetylcholine receptor nachr
Ligand binding domain (LB)
  • core of 10 β-strands, forming a β-sandwich
  • an N-terminal α-helix, two short 310 helices
  • Transmembrane domain (TM)
  • 4 α-helices in each subunit (M1-M4)
  • Intracellular domain (IC)
  • α-helical, some residues still missing

Unwin, Journal of Molecular Biology, March, 2005

The Nicotinic Acetylcholine Receptor (nAChR)
  • a ligand gated ion channel (LGIC) found in central and peripheral nervous system
  • endogenous ligand is acetylcholine (ACh) but reactive to many compounds such as nicotine, alcohol, and toxins
  • mutations lead to various diseases such as epilepsy, myasthenic syndromes, etc.
  • implicated in Alzheimer’s disease and Parkinson’s disease (not well understood)
  • mediates nicotine addiction
computational methods to study membrane proteins
Computational methods to study membrane proteins
  • There are very few crystal structures available for membrane proteins
    • can build structures and use them to perform a range of studies such as electrostatics, pore profiling, ligand docking, Molecular Dynamics simulations etc.
  • Studying the movement of proteins to gain insight into their function
    • various methods of using a structure to look at the dynamics of the protein
  • Docking of ligands onto receptors
    • drug design
generating structures
chosen {θ, z}

theta (radians)

z translation (Å)

Scoring criteria

x

Possible gate region

Generating Structures

O. Beckstein, K. Tai

Amiri et al., Mol. Mem. Biol, 2005

motion analysis
Atomistic Molecular Dynamics Simulations with GROMACS

Coarse-grainGrouping of atoms

Water

Looking at the behaviour of water in the binding pocket

Ligand Docking

Docking Nicotine and other ligands onto various frames of trajectories

In-house methodsGrouping data to simplify MD output

CONCOORD

Generating random structures from a given structure within distant constraints

Gaussian Network Model (GNM)Assessing the flexibility of structures depending on the number of neighbouring residues

Motion Analysis
coarse grain methods 1
ligand binding siteCoarse-grain methods (1)
  • Gaussian Network Model (GNM)
  • A coarse-grained method to approximate fluctuations of residues based on the number of neighbours within a cut-off radius
  • Information on the flexibility of the receptor, may outline functionally important regions of the protein
coarse grain methods 2
SUB1

SUB2

SUB3

SUB4

SUB5

SUB1

SUB2

SUB3

SUB4

SUB5

Covariance matrix showing which part of the protein moves together. The red parts show highest covariance and the blue indicates negative covariance (move in opposite directions)

Porcupine plot showing the nAChR’s two domains rotating in opposite directions. Suggests motions that could be involved in the gating mechanism

http://s12-ap550.biop.ox.ac.uk:8078/dynamite_html/index.html (Barrett et al., 2004)

Coarse-grain methods (2)

CONCOORD

  • Generates n number of structures that meet distance constraints
  • very quick: one run takes a few minutes
  • Output used in Principle Component Analysis (PCA) to describe major modes of motion
molecular dynamics simulations
Covariance lines show which sections of the receptor are moving together

http://s12-ap550.biop.ox.ac.uk:8078/dynamite_html/index.html (Barrett et al., 2004)

Molecular Dynamics Simulations
  • A method to study conformational changes at an atomistic level
  • MD of ligand binding domain of nAChR homologue, AChBP (Celie et al., 2004)
  • several simulations are being carried out for AChBP:
  • i) non-liganded simulations
  • ii) with various ligands: nicotine, carbamylcholine, HEPES
  • One nanosecond takes ~ 5 days for this system
  • Actual gating of this receptor happens on a millisecond time-scale
molecular dynamics simulations continued
Molecular Dynamics Simulations continued …

A simulation of AChBP with Nicotine in all 5 binding sites.

the binding pocket
TRP 144

LEU 103

MET 115

THR 145

CYS 189

CYS 188

The important residues in the binding pocket are shown. These residues are thought to have key interactions with the ligand.

Two subunits of the nAChR are shown with Nicotine inside the binding pocket

The Binding Pocket
  • Studying structural changes which occur in the binding pocket to better understand how binding of a ligand results in the functioning of the ion channel
  • looking at distances, dihedrals of surrounding residues, and the behaviour of water in the binding pocket
water in the binding pocket
Zone 2

Zone 1

Zone 4

Zone 5

Zone 3

Water in the Binding Pocket
  • Bridging waters form hydrogen bonds between the ligand and surrounding residues (shown using Ligplot)
  • Water seems to play an important role in ligand binding. There are various zones in the binding pocket where waters are frequently present
water in the binding pocket1
Water in the Binding Pocket

Water molecules which remain in their position in the Binding Pocket

docking
Docking
  • Docking various ligands such as nicotine, acetylcholine, imidacloprid (an insecticide) onto AChBP and the α7 nAChR to look at possible binding modes
  • An automated docking program docks ligands onto hundreds of frames from a trajectory

Nicotine docked onto the AChBP binding site

Nicotine

Carbamylcholine

HEPES

results
Results
  • Structure Generation:

Developed a method to generate protein structures from their separate domains

  • Molecular Dynamics:
    • MD studies of AChBP with Nicotine, Carbamylcholine, and HEPES
    • Studying the role of water in the binding pocket
    • MD of α7 nAChR mutants
  • Coarse-graining:
    • GNM
    • CONCOORD
    • Grouping of information from MD trajectories
  • Automated Docking:

Automated docking of ligands (Nicotine, acetylcholine, carbamylcholine, insecticides) onto AChBP and nAChR (and its mutants) along a trajectory

slide15
Prof. Mark S. P. Sansom

Dr. Philip C. Biggin

Dr. Alessandro Grottesi

Dr. Kaihsu Tai

Dr. Zara Sands

Dr. Oliver Beckstein

Dr. Daniele Bemporad

Dr. Jorge Pikunic

Dr. Andy Hung

Dr. Shozeb Haider

Dr. Syma Khalid

Dr. Pete Bond

Dr. Kia Balali-Mood

Dr. Hiunji Kim

Dr. Bing Wu

Sundeep Deol

Yalini Pathy

Jonathan Cuthbertson

Jennifer Johnston

Katherine Cox

Robert D’Rozario

Jeff Campbell

Loredana Vaccaro

John Holyoake

Tony Ivetac

Samantha Kaye

Sylvanna Ho

Benjamin Hall

Emi Psachoulia

Chze Ling Wee

Thanks to…

future work
Future Work
  • Further investigation of the role of water in the binding pocket
  • Analysis of simulations of α7 nAChR mutants and docking along their trajectories
  • Development of further methods for understanding the motion of proteins from the limited structural data available
  • Combining coarse-grained and MD data…. i.e. Running GNM on various frames of a trajectory
coarse grain methods 3
Coarse-grain methods (3)

Grouping eigenvectors

  • simplifying Molecular dynamics data by grouping the eigenvectors from the resulting trajectory.
the binding pocket1
TRP 144

LEU 103

MET 115

THR 145

CYS 189

CYS 188

The Binding Pocket
  • Studying structural changes which occur in the binding pocket to better understand how binding of a ligand results in the functioning of the ion channel
  • looking at distances, dihedrals of surrounding residues, and the behaviour of water in the binding pocket

The important residues in the binding pocket are shown. These residues have been shown to interact with the ligand.

slide21
Using computational techniques to study the most flexible regions of the nAChR. These residues could play a key role in the gating of the receptor. Red shows the most flexibility, with blue showing least movement.
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