MINIREVIEW
Computational approaches to understand a-conotoxin interactions
at neuronal nicotinic receptors
Se
´
bastien Dutertre and Richard J. Lewis
Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
Recent and increasing use of computational tools in the field
of nicotinic receptors has led to the publication of several
models of ligand–receptor interactions. These models are all
based on the crystal structure at 2.7 A
˚
resolution of a protein
related to the extracellular N-terminus of nicotinic acetyl-
choline receptors (nAChRs), the acetylcholine binding pro-
tein. In the absence of any X-ray or NMR information on
nAChRs, this new structure has provided a reliable alter-
native to study the nAChR structure. We are now able to
build homology models of the binding domain of any
nAChR subtype and fit in different ligands using docking
programs. This strategy has already been performed suc-
cessfully for the docking of several nAChR agonists and
antagonists. This minireview focuses on the interaction of
a-conotoxins with neuronal nicotinic receptors in light of our
new understanding of the receptor structure. Computational
tools are expected to reveal the molecular recognition
mechanisms that govern the interaction between a-cono-
toxins and neuronal nAChRs at the molecular level. An
accurate determination of their binding modes on the
neuronal nAChR may allow the rational design of a-cono-
toxin-based ligands with novel nAChR selectivity.

with the neuronal nAChR using homology modeling and
docking simulations is expected to provide new information
into how these small peptides achieve their remarkable
selectivity. Several NMR and X-ray structures of a-cono-
toxins are available, and for some of them, identified pairwise
interactions can guide the docking process and lead to an
accurate solution. Their docking modes on nAChR homol-
ogy models will also help to distinguish between distinct
toxin binding sites and identify how they acheive their unique
selectivity. From experimental data, four microsites have
already emerged for the nAChRs: one common a-neuro-
toxin microsite and several distinct a-conotoxin microsites.
Such distinctions in nAChR binding modes are particularly
important as they could represent the specific targets
required to produce highly subtype selective drugs with
fewer side-effects [3]. a-Conotoxins that bind to nAChRs
with very high affinity and selectivity could be used as natural
scaffolds in the design of new therapeutic agents based on
the structure of neuronal nAChR homology models.
Structure of nAChRs
Pre-AChBP view of nAChR structure
In the past half-century, nAChRs, which are the proto-
typical receptors of the ligand-gated ion channel super-
family, have led to an impressive number of physiological,
Correspondence to R. J. Lewis, Institute for Molecular Bioscience,
University of Queensland, Brisbane, Queensland 4072, Australia.
Fax: + 61 73346 2101, Tel.: + 61 73346 2984,
E-mail: [email protected]
Abbreviations: ACh, acetylcholine; AChBP, acetylcholine binding
protein; nAChR, nicotinic acetylcholine receptor; SAR, structure-

been identified. There is a binding site for positive
allosteric modulators (increased neuronal nAChR-medi-
ated ion conductance), two binding sites for noncompet-
itive blockers or negative allosteric modulators, and a
steroid binding site [8].
Fluorescence measurements using labelled a-neurotoxin
first revealed the localization of the competitive binding site
close to the outer perimeter of the muscle nAChR at a
distance of 39–45 A
˚
from the membrane surface [9]. This
was later confirmed by the electron microscopy of the
Torpedo receptor at 4.6 A
˚
resolution, showing the location
of the putative ACh binding site cavities  30 A
˚
away from
the membrane [10]. Intensive mutagenesis studies have
shown that competitive agonists and antagonists bind at the
interface between a–a or a–b subunits, identifying a vicinal
disulfide and several conserved aromatic residues located on
six segments (or loops) A–F [4]. Segments A, B and C are
part of the principal component (subunits a
1
for muscle and
a(+) for the neuronal subtypes), while segments D, E and F
are part of the complementary component (c, d or e for
muscle and a(–) or b for the neuronal subtypes) [11].
Acetylcholine binding protein

Homology models of the neuronal nAChR
ligand binding domain
The template: a high resolution structure of AChBP
AChBP is not an ion channel (it is a soluble protein that
lacks the transmembrane/intracellular parts compared to
nAChRs), but importantly displays many nAChR prop-
erties, including binding of nAChR ligands [13] and a
conformational change in response to agonist binding [14].
Interestingly, the highest percentage of identity (26.5%)
has been found with the ligand binding domain of the a7
neuronal nAChR subtype (Fig. 1). This percentage increa-
ses dramatically when considering only the loops forming
the ACh binding pocket (40–60%), as expected given
the functional homology [15]. The sequence alignment
between the rat nAChR subunit and AChBP sequences
revealed a very good fit with only few gaps of one or two
residues (Fig. 3). A misaligned domain resulting in a gap
Table 1. a-Conotoxins active on neuronal nAChR subtypes. *, C-terminal amidation; O, hydroxyproline; Ys, sulfated tyrosine; c, c-carboxyglutamic
acid. Conserved residues shaded.
2328 S. Dutertre and R. J. Lewis (Eur. J. Biochem. 271) Ó FEBS 2004
of four residues occurs in loop C for the b subunits,
which lack the vicinal disulfide found in AChBP and the
a subunits. This effect on structure is not an issue for the
analysis of the ACh binding site (and the docking
simulation of ligands) because loop C of the b subunit
is not involved in the competitive binding site [16]. Finally,
the important residues for the binding of ACh and other
competitive ligands are conserved in the AChBP sequence,
explaining why AChBP also binds nicotine, epibatine,
(+)-tubocurarine and a-bungarotoxin [5]. Therefore,

MODEL
is a server devoted to this task and is available free
of charge at the ExPASY site (http://www.expasy.org/
swissmod/).
These methods or derivatives of these have led to the
publication of a number of modelled nAChR structures,
including: muscle nAChR subtype of human [18], human
D
-tubocurarine–metocurine complex [19], mouse [20],
mouse
D
-tubocurarine complex [21], torpedo ray [22,23],
torpedo a-bungarotoxin complex [24], nAChR DEG-3
mutant [25], a7 nAChR neuronal subtype of human [26],
chick [23], chick a-cobratoxin complex [15], a4b2 nAChR
neuronal subtype of human [26], rat [23], and a3b2 and
a4b4 nAChR neuronal subtype of human [26].
Fig. 2. AChBP subunit structure.
Fig. 1. AChBP three-dimensional structure (PDB:1I9B). (A) Side view.
(B) Top view. (+)W143, (+)Y89, (+)Y185, (–)W53, (–)Y164 and
(+)Y192 are in ball and stick representation. Figures were prepared
using the program
PYMOL
(http://pymol.sourceforge.net/).
Ó FEBS 2004 Modeling a-conotoxin–nAChR interactions (Eur. J. Biochem. 271) 2329
Exploration at the molecular level of models
of the neuronal nAChRs
As neuronal nAChRs are attractive targets for treating many
diseases such as cognitive dysfunction, neurodegeneration
and other central nervous system pathologies [3,8],

imagine it as a flexible loop that could allow a more open
binding site in the physiological resting state than that
shown in the crystal. However, the most likely access routes
to the ligand binding site are from above or below the
double cysteine-containing loop C. Indeed, we can identify
two cavities at the interface between adjacent subunits from
visual inspection of the molecular surface of AChBP and
nAChR homology models (Fig. 4). For instance, on an a7
nAChR model, a large cavity appears below the b9/b10
hairpin and is made of loop C (+), the C-terminus of loop F
(–), loop A (+) and the C-terminus of the b6 (–) strand
while a narrower one exists above, with contributions from
loop C (+), loop B (+), loop E (–), the N-terminus of the
b6(–)andb1 (–) strands and the C-terminus of the b2 (–)
strand. In addition to these observations, several lines of
experimental evidence reinforce these cavities as the obvious
access routes for the binding of competitive ligands. First,
a-neurotoxin docking based on double-mutant cycle ana-
lysis and NMR data show that they achieve their antagonist
activity by targeting the larger cavity. Indeed, they insert the
tip of their loop II into the ACh binding pocket from below
the b9/b10 hairpin to occupy the binding pocket [15,28].
Secondly, residues that confer selectivity for smaller antag-
onists like the Waglerin have been mapped in the small
Fig. 3. Sequence alignment between AChBP and the N-terminal binding domain of rat nAChR subunits. Secondary structures of AChBP (a, a helices;
b, b sheet) and previously identified nAChR loops are indicated above the alignment. Dark grey, residues common to AChBP and the nAChR
sequences; light grey, residues common only to the nAChR subunits; squares, residues involved in the a-conotoxin binding site.
2330 S. Dutertre and R. J. Lewis (Eur. J. Biochem. 271) Ó FEBS 2004
cavity above the b9/b10 hairpin [20]. Finally, recent docking
of metocurine and

˚
hydrophobic
Fig. 5. a-Conotoxin structures. The right panel is rotated 90° around
the y-axis from the left panel. The figures were prepared using
SWISS
-
PDBVIEWER
[50].
Fig. 4. a7 and a3b2 nAChR homology models showing determinants
influencing a-conotoxin binding identified by mutagenesis. AChR side-
chainsaffecting.ImI,darkblue;PnIB,green;PnIA,pinkandMII,
turquoise are indicated. ImI and PnIB share W147 and Y193, while
PnIA and MII share I186. The small and large shaded regions repre-
sent the location of the small and large cavities, respectively.
Ó FEBS 2004 Modeling a-conotoxin–nAChR interactions (Eur. J. Biochem. 271) 2331
pocket. However, as conotoxins represent a larger volume,
they must use different subdomains outside the ACh
binding site to accommodate their bulky side chains [31].
a-Conotoxin subtype selectivity could therefore arise from
the amino acid composition and geometric conformation
of these microsites. The microsite hypothesis is supported
by different a-conotoxin sequences (Table 1), different
a-conotoxin kinetics [32–35], and finally, the involvement
of different nAChR residues from different regions of
nAChR subunit sequences (Table 2, Figs 4 and 5).
ImI, which has provided the most complete SAR with
regards to the a7 nAChR subtype, where it delineates a
discrete binding site above loop C. From the pairwise
interactions identified, the toxin must enter into the ACh
pocket with its N-terminus, placing the triad D5-P6-R7 in

mation and thereby affect the binding of PnIA indirectly
[36]. Similarly, three determinants of MII sensitivity have
been reported [37], but once again, a distance of 25 A
˚
has
been measured between two of them. With the exception
of K183, which is on the b9b10 hairpin, I186 and T57 are
in, or close to, the ACh binding site. In this view, the MII
binding site resembles the PnIB binding site.
The binding sites of ImII and ImI exhibit little if any
overlap and ImII shows a noticeably slower off-rate despite
having nine out of 12 amino acids in common with ImI [35].
Even if ImII appears to be an enigma in terms of its binding
site, we can exclude its location in the large cavity as it does
not inhibit a-bungarotoxin. Therefore, it probably binds the
ACh pocket from a new distinct microsite but still from
above the b9b10 hairpin. The binding sites of AuIB, AuIA,
AuIC, EpI, GIC and GID remain uncertain, as no SAR has
yet been published. Docking studies of these peptides would
allow the development of hypotheses that could be tested
experimentally.
Docking strategy
Toxins bind with higher affinity than endogenous ligands,
hence their toxicity. This important biological function
depends on a very accurate molecular recognition, mostly
based on complementary surface shape and electrostatic/
hydrophobic interactions. Therefore, an accurate predic-
tion of their binding mode can also provide insight into
designing possible leads for drug design. Docking pro-
grams can be invaluable tools in the rational drug design

(+) ()) PnIB PnIB/a7
W147 S34 S4 L10/W147 [48,49]
Y91 P6 P6/W147
R184 P7 P7/Y91
Y186 A9
Y193 L10
a3b2
a3 b2 PnIA PnIA/a3b2
P180 ND A10 ND [31,36]
I186 N11
Q196
a3b2
a3 b2 MII MII/a3b2
K183 T57 ND ND [37]
I186
a
T75 (human) residue is replaced by N75 in the rat sequence.
2332 S. Dutertre and R. J. Lewis (Eur. J. Biochem. 271) Ó FEBS 2004
tational docking of ImI and PnIB, and to a certain extent
PnIA and MII, using homology models of neuronal
nAChRs would probably produce a reasonable solution
as pairwise interactions and determinants can efficiently
guide the scoring function. However, docking of other
a-conotoxins in the absence of restraints could lead to a
number of docking solutions being found within the ACh
pocket. Mutagenesis experiments designed from these
models could help to discriminate in favour of one
conformation. These docking simulations may subsequently
be used to guide virtual screening for new a-conotoxin
analogues with tailored selectivity.

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