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Understanding protein domain-swapping using structure-based
models of protein folding
Nahren Manuel Mascarenhas
1
, Shachi Gosavi
*
Simons Centre for the Study of Living Machines, National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore 560065, India
article info
Article history:
Received 23 July 2016
Received in revised form
5 September 2016
Accepted 26 September 2016
Available online 17 November 2016
Keywords:
Mechanism of domain swapping
Protein topology
Symmetrized structure-based models
Molecular dynamics simulations
abstract
In domain-swapping, two or more identical protein monomers exchange structural elements and fold
into dimers or multimers whose units are structurally similar to the original monomer. Domain-
swapping is of biotechnological interest because inhibiting domain-swapping can reduce disease-
causing fibrillar protein aggregation. To achieve such inhibition, it is important to understand both the
energetics that stabilize the domain-swapped structure and the protein dynamics that enable the
swapping. Structure-based models (SBMs) encode the folded structure of the protein in their potential
energy functions. SBMs have been success fully used to understand diverse aspects of monomer folding.
Symmetrized SBMs model interactions between two identical protein chains using only intra-monomer
interactions. Molecular dynamics simulations of such symmetrized SBMs have been used to correctly
predict the domain-swapped structure and to understand the mechanism of domain-swapping. Here, we
review such models and illustrate that monomer topology determines key aspects of domain-swapping.
However, in some proteins, specifics of local energetic interactions modulate domain-swapping and
these need to be added to the symmetrized SBMs. We then summarize some general principles of the
mechanism of domain-swapping that emerge from the symmetrized SBM simulations. Finally, using our
own results, we explore how symmetrized SBMs could be used to design domain-swapping in proteins.
© 2016 Elsevier Ltd. All rights reserved.
Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .................................................114
1.1. Domain-swapping nomenclature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . .......................114
1.2. Biological consequences of domain swapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .......................114
1.2.1. Aggregation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................114
1.2.2. Modulation of protein function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................115
2. Structure-based models (SBMs) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ............................................115
2.1. SBMs and protein folding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................115
2.2. Symmetrized SBMs and domain-swapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................116
3. Insights gained about domain-swapping from symmetrized SBM simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .....................116
3.1. Monomer topology determines the domain-swapped structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................116
3.2. Mechanistic principles that emerge from MD simulations of domain swapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................116
4. Introducing domain-swapping into proteins that do not swap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .....................117
4.1. Proteins of the monellin-cystatin fold . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................117
4.2. Domain-swapping simulations of monellin variants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................117
4.3. Using symmetrized SBMs to design domain-swapping in proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................118
5. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .................................................119
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .......................119
* Corresponding author.
E-mail address:
shachi@ncbs.res.in (S. Gosavi).
1
Present address: Department of Chemistry, Sacred Heart College (Autonomous),
Tirupattur 635601, Tamilnadu, India.
Contents lists available at ScienceDirect
Progress in Biophysics and Molecular Biology
journal homepage: www.elsevier.com/locate/pbiomolbio
http://dx.doi.org/10.1016/j.pbiomolbio.2016.09.013
0079-6107/© 2016 Elsevier Ltd. All rights reserved.
Progress in Biophysics and Molecular Biology 128 (2017) 113e120
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..................................................119
1. Introduction
Domain-swapping is a process in which two or more identical
protein monomers exchange structural elements and fold into di-
mers or multimers (
Bennett et al., 1994a; Liu and Eisenberg, 2002).
The individual units of such oligomers are structurally similar to the
original monomer (
Fig. 1). The earliest evidence for domain-
swapping was seen in RNase A (
Crestfield et al., 1962) and the
first determination of a domain-swapped structure was that of the
dimeric diphtheria toxin (
Bennett et al., 1994a,b). Since then, it has
become clear that domain-swapping is common, and several
domain-swapped proteins have been crystallized (
Shameer et al.,
2011
). Recent data indicates that RNA structures may also
domain-swap (
Suslov et al., 2015). In this section, we first define
several terms used in the study of domain-swapping (
Liu and
Eisenberg, 2002; Gronenborn, 2009; Rousseau et al., 2012
) and
then summarize the biological consequences of domain-swapping
(
Rousseau et al., 2012; Wodak et al., 2015).
1.1. Domain-swapping nomenclature
In order for a protein to be considered domain-swapped the
structures of both the monomer and the domain-swapped olig-
omer need to be present. If one of the structures is that of a ho-
mologous protein then the protein is said to be quasi-domain
swapped. If only the domain-swapped structure is available then
the protein is considered a candidate for domain-swapping. Several
inter-protein interfaces are formed upon domain-swapping. The
interface whose inter-protein interactions mimic those present in
the monomer is called the primary interface. However, new in-
terfaces which are not present in the monomer can also be formed
and such interfaces are called secondary interfaces. Many proteins
swap only a single secondary structural element and in such cases
this “domain” can be thought of as being swapped. However, there
are proteins where the size of the “swapped” region is similar to
that of the other region. To account for both cases, in this review, we
call both parts of the monomer swapped domains. So, a domain-
swapping protein usually consists of two swapping-domains con-
nected by a peptide segment (of about 4e5 residues) called the
hinge (
Fig.1B and C). The hinge undergoes a conformational change
upon swapping, usually being a loop or a turn in the monomer
(
Fig. 1B) and adopting an extended conformation after domain-
swapping (
Fig. 1C). There are also examples where two different
hinges induce two different modes of domain swapping in the
same protein (
Liu et al., 1998, 2001; Chen et al., 2010). In some
proteins (
Nilsson et al., 2004), one swapped domain is inserted into
the sequence of the other domain and there are two peptide seg-
ments connecting the two domains. Upon swapping, both seg-
ments undergo a conformational change. Given the diversity of
structural hinge types, there have been efforts to understand the
sequence determinants of hinges. Early efforts concentrated on the
proline composition of hinges but although prolines contribute to
domain-swapping in some proteins (
Bergdoll et al., 1997; Rousseau
et al., 2001; Miller et al., 2010
) this is not a universal effect
(
Barrientos et al., 2002; Cho et al., 2005). A recent study analyses
the distribution of all amino acids in the hinge regions of domain
swapping proteins and fi
nds that the amino acid distribution of
hinge residues is similar to that of other loop regions. However,
there are some amino acids such as valine which are more likely to
be found in hinges (
Shingate and Sowdhamini, 2012).
1.2. Biological consequences of domain swapping
1.2.1. Aggregation
Open-ended domain-swapping (
Fig. 1D) can lead to the forma-
tion of large protein aggregates (
Esposito et al., 2010). Such ag-
gregation can lead to the loss of protein function and cause disease
(
Law et al., 2006). Domain-swapping has also been implicated in
the formation of disease-causing fibrillar aggregates (
Chiti and
Dobson, 2006; Herczenik and Gebbink, 2008; Bennett et al., 1995,
2006; Janowski et al., 2005
). For instance, mutants of cystatin-C
with reduced domain-swapping also have reduced fibrillar aggre-
gation (
Nilsson et al., 2004). The question that arises, then, is, “Why
are the amino acids that cause increased domain-swapping
retained through evolution?” In a recent study, we showed that
in stefin-B, residues that increase the propensity of domain-
swapping are part of the protease binding-site and thus, domain-
swapping can be a by-product of the need to conserve protein
Fig. 1. The elements of domain swapping. (A) Two unfolded monomer chains shown
in green and orange. These can either fold to two monomers (B) or exchange structural
elements and fold to a domain-swapped dimer (C). The hinge is the peptide connector
between the two domains in a single protein and is shown in (B). The hinge is in
different conformations in the monomer (B) and the swapped structures (C, D). (D)
Alternate outcomes of domain swapping which could lead to larger aggregates.
N.M. Mascarenhas, S. Gosavi / Progress in Biophysics and Molecular Biology 128 (2017) 113e120114
function (Mascarenhas and Gosavi, 2016). In some proteins,
domain-swapping is itself involved in protein function and we
discuss this next.
1.2.2. Modulation of protein function
Domain-swapping has been implicated in the regulation of
protein function (
Saint-Jean et al., 1998; Vitagliano et al., 1999;
Baxter et al., 2012
). The addition of glutathione converted the
Pseudomonas putida glyoxylase I from an active domain-swapped
dimer with two metal binding sites to a metastable less active
monomer with one metal binding site (
Saint-Jean et al., 1998).
Domain-swapping was also observed to induce allosteric commu-
nication in the N-terminal swapped bovine seminal ribonuclease A
(
Vitagliano et al., 1999). Additionally, domain swapping has been
suggested as a mechanism for the evolution of larger complex folds
when it is followed by gene duplication and fusion (
Bennett et al.,
1995
). Further support for this hypothesis was found in directed
evolution experiments on NF-
k
B p50, where domain-swapping was
able to rescue both structure and function from destabilizing mu-
tations (
Chirgadze et al., 2004). Finally, domain-swapping has been
seen to induce protein self-assembly (
Baker et al., 2016).
In order to understand the consequences of domain-swapping,
it is important not only to be able to predict the final domain-
swapped structure but also to understand the mechanism of
domain-swapping. Here, we review a class of computational pro-
tein models called G
o(
G
o and Taketomi, 1979) or structure-based
models (SBMs) (
Clementi et al., 2000; Whitford et al., 2009).
SBMs use information derived only from the monomeric protein
structure to model domain-swapping (
Ding et al., 2002; Yang et al.,
2004
). Molecular dynamics (MD) simulations of such SBMs have
been able to correctly predict hinge regions and the structure of the
domain-swapped dimers (
Ding et al., 2002; Yang et al., 2004; Cho
et al., 20 05; Ding et al., 2006
). They have also been used to un-
derstand whether swapping starts from a transition-state
ensemble, an intermediate ensemble or an unfolded ensemble
(
Yang et al., 2004; Cho et al., 2005; Ono et al., 2015). We summarize
insights about the mechanism of domain swapping gained from
SBM simulations and then briefly describe how this information
might be used to design domain-swapping in proteins.
2. Structure-based models (SBMs)
2.1. SBMs and protein folding
Despite having a vast conformational space, proteins fold on a
biologically reasonable timescale because of a funnel shaped en-
ergy landscape (
Bryngelson et al., 1995). This funnel shape arises
because the interactions present in the native or the folded struc-
ture of the protein are stabilizing while non-native interactions,
which would need to be broken before further folding, are mostly
destabilizing. SBMs (
Clementi et al., 2000; Hyeon and Thirumalai,
2011; Whitford et al., 2012
) use this funnel shape of the energy
landscape to simplify the potential energy function and make it
easier to sample the conformational space. The potential energy
functions of SBMs encode the structure of the protein and in doing
so, ignore all non-native interactions and assume that only native
interactions contribute to folding. Further, solvation is taken into
account implicitly. Both these simplifications speed up computa-
tion and make it possible to reach folding timescales in a reasonable
amount of computer time. Molecular dynamics (MD) simulations of
SBMs of proteins have been successfully used to describe various
aspects of protein folding such as folding mechanisms, trends in
folding barrier heights, structures of folding intermediate ensem-
bles, etc (
Hyeon and Thirumalai, 2011; Whitford et al., 2012).
SBMs have been reviewed in detail elsewhere (
Hyeon and
Thirumalai, 2011; Whitford et al., 2012; Yadahalli et al., 2014
).
Here, we summarize a few general features of the models. The
protein structure is encoded into different flavours of SBMs in
different ways. For instance, some SBMs are coarse-grained and
represent each residue by only its C
a
(see for example: Clementi
et al., 2000
) or its C
a
and its C
b
atoms (see for example: Cheung
et al., 2005
). In general, in all SBMs, constraints derived from
chemical bonding such as bond distances (
Fig. 2A), angles (Fig. 2B)
or improper dihedrals maintaining chirality are encoded using
strong harmonic potentials which do not allow these terms to
deviate much from their values in the folded structure. Some SBMs
encode a cosine-like dihedral potential which mimics secondary
structure formation (
Fig. 2C). The energetics of tertiary structure is
encoded through Lennard-Jones-like potentials between atoms
which are in “contact” in the folded structure of the protein
(
Fig. 2D). The strength of this contact potential is such that contacts
can break and form (the distance between the atoms in contact is
similar to that in the folded state) allowing the protein to unfold
and fold. Atom pairs which are in contact and have an attractive
interaction potential between them are usually calculated using
one of two recipes. In the first, a contact is said to be present
Fig. 2. A summary of the symmetrized SBM interactions. The two protein chains
which interact to form the domain-swapped dimer are shown in orange and green. (A-
E) show intra-monomer interactions which are present both in the monomer SBM and
the symmetrized SBM. (A, B) These are strong harmonic interactions between bonds
and angles respectively. They preserve the chemical connectivity of the monomer
while it folds or domain-swaps. (C) There are weaker cosine dihedral potentials be-
tween four consecutive beads. (D) Lennard-Jones-like interaction potentials are pre-
sent between all beads which are in contact in the folded state of the protein. Here
such interactions are represented by dashed lines. (E) Intra-protein interactions in the
second monomer are exactly the same as those in the first monomer. (F) Inter-protein
interactions present in the symmetrized SBM are shown as dashed lines. These are
calculated based only on the monomer contacts.
N.M. Mascarenhas, S. Gosavi / Progress in Biophysics and Molecular Biology 128 (2017) 113e120 115
between two atoms if the second atom is within a pre-set cut-off
radius (say 4.5 Å) of the first atom (see for example:
Karanicolas and
Brooks, 2002; Chen and Chan, 2015
). Such contact maps are called
cut-off contact maps. In the second recipe, an additional screening
term is imposed which removes contacts where the contact is
occluded by a third atom. Such screened contact maps (e.g. shadow
(Noel et al., 2012) and CSU (Sobolev et al., 1999)), are advantageous
because they reduce the sensitivity of contact lists to the cut-off
radius. In several coarse-grained SBMs, contacts are calculated us-
ing the atomistic representation of the protein and then projected
onto the coarse-grained representation (
Clementi et al., 2000;
Karanicolas and Brooks, 2002
). Some coarse-grained SBMs weight
the strengths of contacts (see
Yadahalli and Gosavi, 2016 for a
detailed description of several such SBMs) or change the shape of
the contact potential (
Azia and Levy, 2009; Chen and Chan, 2015)to
account for sequence specific effects. Such heterogeneous contacts
can be used to represent salt bridges (
Azia and Levy, 2009), disul-
phide bonds (
Cho et al., 2005), single effective contacts between
large amino acids (
Yadahalli and Gosavi, 2016), etc. Finally,
excluded volume interactions keep atoms which are not in contact
from passing through each other.
2.2. Symmetrized SBMs and domain-swapping
SBMs are computationally efficient and can be used to simulate
long timescales for multiple protein chains. Thus, SBMs can be used
to study domain-swapping. However, SBMs used for protein folding
use only native-like interactions in the potential energy function.
Although such SBMs can be used to understand the mechanism of
domain-swapping using the domain-swapped structure, they
cannot be used for predicting the domain-swapped structure or for
understanding the causes of domain-swapping. In order to address
these issues, symmetrized SBMs, which use information only from
the monomer structure, were invented (
Ding et al., 2002; Yang
et al., 2004
). The potential energy functions of symmetrized SBMs
are constructed as follows: The energy function of each identical
protein chain (say A or B) is derived from the monomer structure in
the same manner as in the folding SBMs. A weak harmonic restraint
of the form k(x-x
0
)
2
is usually applied between the centres of mass
of the two protein chains (A and B) to maintain a given protein
concentration. Additionally, for every pair of intra-molecular con-
tacts between atoms i
A
and j
A
of chain A and i
B
and j
B
of chain B
present in the monomer SBMs, a pair of inter-molecular contacts
(i
A
,j
B
) and (i
B
,j
A
) are introduced into the symmetrized SBM. Thus,
atoms can form the same set of contacts either within their own
chain, which leads to a pair of monomers or with atoms of another
chain, which can lead to a diversity of domain-swapped structures.
However, it was observed that the largest population of dimers
seen in symmetrized SBM simulations had structures which were
similar to the domain-swapped dimer crystal structure (
Yang et al.,
2004; Cho et al., 2005
).
In some proteins, specific features of the amino acid sequence
promote or repress domain-swapping. Such sequence effects can
either be present (as stress) in the hinges (e.g. isomerization of
hinge prolines (
Gronenborn, 2009) or the hydrophobic effect
driving the dihedral angle of valine into disallowed regions of the
Ramachandran plot (
Mascarenhas and Gosavi, 2016)) or elsewhere
in the protein (e.g. energetic heterogeneity created by the presence
of disulphide bonds (
Cho et al., 2005)). Symmetrized SBMs modi-
fied to account for such effects have been able to correctly predict
the structure of the domain-swapped dimers (Mascarenhas and
Gosavi, 2016; Cho et al., 2005).
3. Insights gained about domain-swapping from
symmetrized SBM simulations
3.1. Monomer topology determines the domain-swapped structure
For several proteins, even symmetrized SBMs which include
only a coarse-grained representation can correctly predict the
structure of the domain-swapped dimers (
Yang et al., 2004; Cho
et al., 2005; Ding et al., 2006
). Further, the physical understand-
ing of domain-swapping from symmetrized SBMs has also led to a
method for predicting the unfolding hotspots and hinge regions
using only the monomer structure (
Ding et al., 2006). This method
calculates the difference in contact energies (
D
E) between the fol-
ded structure and an “open” (or domain-swapped) structure of the
monomer which assumes that a particular hinge contributes to the
domain-swapping. The gain in entropy (
D
S) upon going from the
folded structure to the open structure is modelled using polymer
theory. A hinge is predicted to be the likely cause of domain-
swapping if its
D
E/
D
S is the lowest in the protein. This method
was able to correctly predict the hinges for several proteins
including the two different hinges present in RNase-A which give
rise to two different domain-swapped dimers. It was also able to
predict an entirely new domain-swapped structure for the focal
adhesion targeting domain which was subsequently experimen-
tally con firmed. Thus, in general, the structure of the domain-
swapped dimer is determined by the overall topology of the
monomer.
3.2. Mechanistic principles that emerge from MD simulations of
domain swapping
We next discuss potential protein fates that have been seen in
symmetrized SBM simulations and how these fates are determined
by the energetics of the protein structure. At low protein concen-
trations (a low inter-protein interaction force constant, k, and a
high inter-protein mean interaction distance, x
0
in symmetrized
SBM simulations), proteins interact little and mainly fold to
monomers. At higher protein concentrations (a larger inter-protein
interaction force constant, k and a small mean interaction distance,
x
0
), there is a competition between folding to a monomer structure
and domain-swapping (
Yang et al., 2005). In simulations of proteins
which do not domain-swap and have a high barrier to folding (e.g.
WT CI2 (
Yang et al., 2004; Cho et al., 2005)), a high protein con-
centration promotes domain-swapping but induces a diversity of
swapped structures with no particular structure being given a
preference (
Yang et al., 2004; Cho et al., 2005). In high concentra-
tion simulations of proteins which domain-swap, the correct
domain-swapped structure is predominant (
Yang et al., 2004; Cho
et al., 2005; Ding et al., 2006
). It has also been observed that
“hotspots” of unfolding are present around the hinge region (
Ding
et al., 2006; Dehouck et al., 2003
). Such hotspots can promote
domain-swapping from the unfolded state by remaining unfolded
while the rest of the protein folds (
Yang et al., 2004; Ding et al.,
2006; Liu and Huang, 2013
).
In some proteins, the free energy barrier to folding is low
potentially due to the formation of folding intermediates
(
Tsytlonok and Itzhaki, 2013). In such cases, partial monomer
folding can still occur even at high protein concentrations. The
structure of the intermediate (or possibly the folding transition
state (
Moschen and Tollinger, 2014)) then determines the structure
of the domain-swapped dimers with the intermediate (or the
transition state) being mostly identical to one of swapped regions
in the domain-swapped structure (
O'Neill et al., 2001; Kim et al.,
2000; Moschen and Tollinger, 2014; Rousseau et al., 2012;
Mascarenhas and Gosavi, 2016). Further, we find that if the
N.M. Mascarenhas, S. Gosavi / Progress in Biophysics and Molecular Biology 128 (2017) 113e120116