# A synthetic T-cell receptor-like protein behaves as a Janus particle in
solution

Emily Sakamoto-Rablah  [  Jordan Bye  [  Arghya Modak  [  Andrew Hooker  [
Shahid Uddin  [  Jennifer J McManus<EMAIL_ADDRESS>[

###### Abstract

Protein engineering enables the creation of tailor-made proteins for an array
of applications. ImmTACs stand out as promising therapeutics for cancer and
other treatments, while also presenting unique challenges for stability,
formulation and delivery. We have shown that ImmTACs behave as Janus particles
in solution, leading to self-association at low concentrations, even when the
averaged protein-protein interactions suggest that the molecule should be
stable. The formation of small but stable oligomers has been confirmed by
static and dynamic light scattering and analytical ultracentrifugation.
Modelling of the structure using Alphafold leads to a rational explanation for
this behaviour, consistent with the Janus particle assembly observed for
inverse patchy particles.

1] HH Wills Physics Laboratory, University of Bristol, BS8 1TL, United Kingdom
2] Immunocore Limited, 92 Milton Park, Abingdon OX14 4RY, United Kingdom 2]
Immunocore Limited, 92 Milton Park, Abingdon OX14 4RY, United Kingdom 2]
Immunocore Limited, 92 Milton Park, Abingdon OX14 4RY, United Kingdom 2]
Immunocore Limited, 92 Milton Park, Abingdon OX14 4RY, United Kingdom 1] HH
Wills Physics Laboratory, University of Bristol, BS8 1TL, United Kingdom
[3]Bristol Biodesign Institute, University of Bristol, BS8 1QU, United Kingdom

##  1 Introduction

Recent advances in protein engineering have allowed for tailor-made proteins
with high selectivity to be developed as therapeutic products 1. This
technological advancement holds promise for numerous novel applications,
including the design of artificial organelles with custom functions, creating
new bio-based materials, or developing new pharmaceutical molecules. Among the
latter, one such class of therapeutic molecules is the immune mobilizing
monoclonal T-cell receptor against cancer (ImmTAC) 2. ImmTACs target cancerous
cells with high specificity by design, while harnessing the body’s own immune
response and are unique molecules in the biopharmaceutical space.

ImmTAC molecules consist of an affinity enhanced T-cell receptor (TCR) joined
by a flexible linker to an anti-CD3 single chain variable fragment (scFv) 3,
4. The TCR region binds to cancer cells with high affinity while the scFv
component mobilizes T-cells within the body. This innovative approach holds
tremendous potential to deliver life-saving treatments to cancer patients; one
ImmTAC molecule (tebentafusp) has FDA approval as a treatment for metastatic
uveal melanoma, an aggressive form of eye cancer with previously limited
treatment options. As research into ImmTACs (and other synthetic proteins)
continues, more options for previously hard-to-treat diseases now seem
tractable.

The ability to create proteins not found in nature has profound implications
for their solution stability. Natural proteins have been finely tuned by
evolution to be structurally and colloidally stable under physiological
conditions, maintaining a delicate balance between solubility and aggregation
to ensure proper cellular function. In contrast, synthetic proteins such as
ImmTACs offer a unique opportunity to explore the effects of deliberate design
modifications optimised for function, and the consequences for solution
stability and therefore formulation and delivery. These modifications, aimed
at enhancing target specificity and immune activation, may also impact the
protein phase behaviour and self-assembly.

Understanding weak, nonspecific protein-protein interactions (PPIs) and self
assembly to select formulation conditions is central to realising the
transformative potential of these molecules. Ensuring colloidal and structural
stability is a crucial aspect of producing safe and effective drug products 5,
6, 7. Colloidal stability is highly dependent on weak, nonspecific PPIs as
well as interactions of the protein with solvent and co-solutes. Current
manufacturers of biotherapetics often rely on previously successful
formulations or use expensive and time-consuming trial-and-error approaches,
due to the complex nature of protein intermolecular interactions which has
consequences for their phase behaviour. As more novel and innovative
biotherapeutics such as ImmTACs are developed for which prior formulation
strategies do not exist, established techniques for selecting solution
conditions and excipients as routes to formulation need re-evaluation and
bringing them to market will require a shift to more rational approaches.

Here we demonstrate that the design of a single ImmTAC (referred to henceforth
as ImmTAC1) for biologically optimised function produces a highly anisotropic
surface charge distribution, resulting in the unexpected formation of
noncovalent oligomers.

##  2 Results and Discussion

Figure 1: a) Predicted structure of ImmTAC1 generated by Alphafold, coloured
by confidence metric pLDDT. b) Alphafold structure (magenta) overlaid with
crystal structure of TCR (PDB 2P5E) (green) and anti-CD3 (PDB 1XIW) (blue). c)
Front and back view of predicted ImmTAC surface coloured by charge at pH 7.0.
Visualisations performed using UCSF ChimeraX 8. d) Estimated total
electrostatic charge on ImmTAC, TCR and anti-CD3 regions. Calculated using
Prot-pi tool 9

###  2.1 ImmTAC structure and structural stability

Since the stucture of ImmTAC1 has not yet been successfully obtained by
crystallography or cryo-EM methods, Alphafold 10 was utilised to generate a
predicted structure. Based on the amino acid sequence, five predicted
structures were generated. Among these, the structure which ranked highest by
predicted local distance difference test (pLDDT) is shown in Figure 1(a). The
pLDDT is a per-residue confidence metric which estimates how well the
prediction would match the real structure based on the local distance
difference test 11. The highest ranking structure has a total average pLDDT of
86.9%. As illustrated in Figure 1(a), most lower pLDDT regions are those in
which we expect structural disorder such as the linkers within the scFv
portion, and between the TCR and scFv, rather than areas with significant
secondary structure. To further validate the Alphafold prediction, Figure 1(b)
shows the predicted structure overlaid with known crystal structures for a TCR
(PDB: 2P5E) and anti-CD3 fragment (PDB: 1XIW). The predicted structure shows
good spatial overlap with the experimental structures, having a root mean
squared deviation of 0.624 and 0.672 respectively between the Alphafold
structure and PDB structures.

The online Adaptive Poisson-Boltzmann Solver (APBS) tool was used to assign
electrostatic charges to the Alphafold structure at different pH values 12. A
visualisation of the resulting surface charge at pH 7.0 is shown in Figure
1(c). The TCR section of the molecule carries a largely negative charge while
the anti-CD3 portion is positively charged based on surface exposed charge
densities. This is further illustrated by the net charge of the protein at
different pH values (calculated using Prot-pi 9) compared with that of the
respective sections (i.e. the scFv and TCR), shown in Figure 1(d). This is a
feature of the way the protein has been designed and engineered, in that
creating a fusion of two proteins with contrasting isoelectric points results
in a molecule with a net charge of -12.0 at pH 7, but an anisotropic
distribution of that charge.

###  2.2 Measurement of protein-protein interactions

Figure 2: a) SLS data plotted as a Debye plot. Straight lines are linear fits
to data with slopes equal to the second virial coefficient $B_{22}$. b)
Diffusion data measured by DLS. Straight lines show fits to the data with
slope equal to interaction parameter $k_{D}$. c) Relationship between
interaction parameter and second virial coefficient for ImmTAC1 and lysozyme
13. Inset shows relationship between measured hydrodynamic radius and
molecular weight for ImmTAC1 along with the expected relationship (dashed
line) calculated from theory (Equation 17). d) Hydrodynamic function
calculated using Equation 12 as a function of concentration.

To evaluate the strength of net PPIs, static light scattering (SLS) was
carried out in 100 mM sodium phosphate at pH 6.8 and 7.0, in phosphate
buffered saline (PBS) at pH 7.4, and in 50 mM Tris at pH 7. The SLS data are
shown in Figure 2(a) in the form of a Debye plot. We fit a straight line
according to the Debye-Zimm equation:

$\frac{Kc}{R}=\frac{1}{M}+2B_{22}c,$ (1)

where $c$ is the protein concentration, $R$ is the excess Rayleigh Ratio
(defined as the ratio of scattered light to incident light at a given angle,
in this case 90°), $M$ is the protein molecular weight and $K$ is an
instrument constant given by

$K=\frac{4\pi^{2}n^{2}(\frac{dn}{dc})^{2}}{N_{A}\lambda^{4}}$ (2)

with $n$ equal to sample refractive index, $\frac{dn}{dc}$ the refractive
index increment (here taken to be 0.19 in accordance with Zhao et al 14),
$N_{A}$ Avogadro’s constant and $\lambda$ the laser light wavelength (632.8
nm). The second virial coefficient $B_{22}$ is in units of volume-moles per
mass squared. $B_{22}$ represents deviations to the osmotic pressure
introduced by pairwise interactions and hence is often used as a measure of
net interaction strength. This is often reported in units of volume,
$B_{22}^{V}=\frac{B_{22}M^{2}}{N_{A}}$ and is defined as 13

$B_{22}^{V}=-\frac{1}{2}\int_{0}^{\infty}[e^{-\frac{w(r)}{k_{B}T}}-1]4\pi
r^{2}dr,$ (3)

where $r$ is the protein-protein separation, $w(r)$ is the average
interprotein interaction potential, $k_{B}$ is Boltzmann’s constant and $T$ is
temperature in Kelvin. According to this definition, positive values of
$B_{22}$ correspond to net repulsion between protein molecules (and therefore
conditions which are likely conducive to colloidal stability) while negative
values reflect net attractive interactions and a likely tendency towards
aggregation 13. All molecules experience inter-particle repulsion at short
range due to steric exclusion, which contributes a positive component to the
value of $B_{22}$. Using Equation 3 and approximating the particles as hard
spheres, this excluded volume contribution is $B_{22}^{V,ex}=4V_{HS}$ where
$V_{HS}$ is the hard sphere volume, i.e. $B_{22}^{V,ex}$ is equal to the
excluded volume per particle. Simulations have shown that $B_{22}^{V,ex}$ is
well approximated by the excluded volume per particle of a sphere with radius
equal to the hydrodynamic radius $R_{h}$ 15. Here we assume the relation
between molecular weight $M$ and radius of gyration $R_{g}$ to be

$\frac{M}{\rho}=\frac{4\pi}{3}R_{g}^{3},$ (4)

where $\rho$ is the protein density, taken here to be 1.4 g/cm3 16, while we
use the molecular weight calculated based on the amino acid sequence of
ImmTAC1 to be 77.2 kDa (calculated using the ProtParam tool available on the
ExPASy server 17). For globular proteins the ratio of $R_{g}$ and $R_{h}$ is
generally found to be 0.775 18, hence we estimate

$B_{22}^{V,ex}=\frac{4M}{\rho}\left(\frac{1}{0.775^{3}}\right).$ (5)

The net contributions of all other pair interactions (i.e. “soft”
interactions) normalised by the hard sphere contributions is often represented
as

$B_{22}^{*}=\frac{B_{22}-B_{22}^{V,ex}}{B_{22}^{V,ex}},$ (6)

known as the reduced second virial coefficient. Values obtained from fits to
the data in Figure 2(a) are shown in Table 1. The fitted $B_{22}^{*}$ values
obtained by SLS indicate net attractive interactions between protein
molecules.

Solution condition | $B_{22}^{*}$ |  | Molecular
---
weight
(kDa)
$k_{D}$ |  | Hydrodynamic
---
radius
(nm)
PBS pH 7.6 | -0.7 $\pm$ 0.3 | 190 $\pm$ 10 | -8.3 $\pm$ 0.3 | 4.62 $\pm$ 0.04
50 mM tris pH 7.0 | -1.4 $\pm$ 0.5 | 160 $\pm$ 10 | -10.7 $\pm$ 0.9 | 4.9 $\pm$ 0.1
| 100 mM sodium
---
phosphate pH 7.0
-1.5 $\pm$ 0.6 | 118 $\pm$ 6 | -12.2 $\pm$ 0.4 | 4.42 $\pm$ 0.02
| 100 mM sodium
---
phosphate pH 6.8
-1.5 $\pm$ 0.5 | 123 $\pm$ 5 | -15.1 $\pm$ 0.3 | 4.34 $\pm$ 0.03
Table 1: Second virial coefficient and molecular weight values measured by SLS
and $k_{D}$ and Hydrodynamic radius values measured by DLS.

Dynamic light scattering (DLS) was also used to measure net interaction
parameter $k_{D}$ using the same solution conditions in order to validate the
SLS results. The intensity correlation function is given by

$G_{2}(\tau)=\frac{\langle I(t)I(t+\tau)\rangle}{\langle I(t)\rangle^{2}},$
(7)

where $I$ is intensity of scattered light, $t$ is time and $\tau$ is a lag
time, effectively comparing the intensity at a given time $I(t)$ to that at a
later time $I(t+\tau)$. For monodisperse solutions the correlation function
takes the form 19

$G_{2}(\tau)=B\left(1+\beta e^{-2Dq^{2}\tau}\right)=B\left(1+\beta
g_{2}(\tau)\right),$ (8)

where $D$ is the diffusion coefficient and $q$ is the Bragg wave vector,
related to the refractive index $n$ of the solvent, wavelength of scattered
light $\lambda$ and the scattering angle $\theta$ by $q=\frac{4\pi
n}{\lambda}sin(\theta/2)$. $B$ and $\beta$ are the amplitude (or intercept)
and baseline of the correlation function respectively, while $g_{2}(\tau)$ is
referred to as the normalised correlation function. In a polydisperse solution
20,

$g_{2}(\tau)=\frac{\sum_{i}\rho_{i}M_{i}^{2}e^{-2D_{i}q^{2}\tau}}{\sum_{i}\rho_{i}M_{i}^{2}},$
(9)

where $\rho$ is number density and subscript $i$ denotes each species in the
solution. We may fit ln($g_{2}(\tau)$) to a second order polynomial

$ln(g_{2}(\tau))=-2q^{2}D_{c}\tau+q^{4}\tau^{2}(\delta D_{c})^{2},$ (10)

where the first order coefficient gives the collective diffusion coefficient
while the second order coefficient corresponds to fluctuations in the
diffusion coefficient as described in 20. From the collective diffusion
coefficient we may derive the net interaction parameter $k_{D}$, using 13

$\frac{D_{c}}{D_{0}}=1+k_{D}\phi,$ (11)

where $D_{0}$ is the diffusion coefficient of the protein extrapolated to
infinite dilution, and $\phi=\nu c$ is the protein volume fraction with
partial specific volume $\nu$ of the protein taken here to be 0.73 ml/g. Shown
in past studies to correlate with the second virial coefficient for some
globular proteins 20, a positive $k_{D}$ value is indicative of net repulsive
interactions, while negative $k_{D}$ indicates net attractive interactions 21.
However, $k_{D}$ differs from $B_{22}$ in that there is a contribution from
hydrodynamic, or indirect, interactions (since diffusion is affected by both
hydrodynamics and thermodynamics) while $B_{22}$ is a purely thermodynamic
quantity. Collective diffusion coefficients for ImmTAC1 are shown in Figure
2(b). Values of $k_{D}$ obtained by a linear fit according to equation 11 are
given in Table 1. In agreement with $B_{22}$ values, the fitted $k_{D}$ values
indicate net attractive PPIs.

In order to test the agreement between the data obtained from SLS and DLS,
$k_{D}$ values were plotted against $B_{22}$, along with values for lysozyme,
obtained by Muschol and Rosenberger 13 and are shown in Figure 2(c). Our data
show good agreement with the linear relationship measured by Muschol and
Rosenberger 13 within errors (taken to be the error on the gradient given by
the linear fits).

If we were to only consider the net charge of the protein, this result that
interprotein interactions are measured to be net attractive in nature may
appear to be somewhat surprising. The pH range studied here (6.8-7.4) is
higher than the theoretical isoelectric point of 5.27, with theoretical values
for net charge being between -9.8 and -13.5 (Figure 1(d)). Based on these
values of net charge we might expect double layer repulsion to dominate the
net interaction potential at low ionic strengths. Attractive pairwise
interaction potentials in charged proteins have been explained in past studies
as an attractive electrostatic force between oppositely charged “patches” on
the surface of molecules with anisotropic surface charge density 20, 22. This
is consistent with the asymmetry in surface charge observed from the Alphafold
models in Figure 1(c) and evident in the contrast in charge between the TCR
and scFv sections (Figure 1(d)). It is reasonable to suggest that this results
in electrostatic attraction with the negatively charged TCR and positively
charged scFv of two different ImmTACs will experience a charge-charge
attraction at sufficiently small intermolecular distances. Indeed, past
simulations have also shown the importance of considering anisotropy to
explain protein phase behaviour 23, 24, 20, 25.

Since DLS measures contributions from hydrodynamic interactions while SLS does
not, data from these two techniques may be combined to ascertain the strength
of hydrodynamic interactions. The hydrodynamic function $H$ relfects how the
drag force on a protein is affected by solvent flow due to surrounding
proteins. It can be shown that 13

$1-H(q=0)=\frac{D_{c}}{D_{0}}\frac{R}{KcM}.$ (12)

Resulting values for hydrodynamic functions are shown in Figure 2(d). Values
for $H$ are seen to be distributed around 0 for all solution conditions other
than for PBS at pH 7.6, i.e. hydrodynamic interactions only play a significant
role in the protein interactions in PBS. According to the measured $B_{22}$
and $k_{D}$ values the protein has the least attractive net PPIs in PBS
compared with the other buffers examined. PBS contains a high proportion of
NaCl, which provides electrostatic screening. This implies that in the case of
high screening the direct interactions of electrostatic origin are suppressed
sufficiently that hydrodynamic (indirect) interactions have a measurable
effect, while under other solution conditions the weak intermolecular
electrostatic interactions dominate to the point of suppressing the
hydrodynamic interactions.

Figure 3:  Thermal unfolding curves measured by nano-DSF in the presence of
various concentrations of NaCl (a) and sucrose (b). Concentrations of NaCl and
sucrose are in (w/v) percentage.

In order to rule out this difference being due to structural changes such as
unfolding, nano differential scanning fluorimetry (nano-DSF) was used to
measure structural changes with temperature in the presence of various co-
solutes. The temperature of the samples was varied between 20 and 100 °C and
the ratio of fluorescence intensities at 355 and 330 nm was measured in order
to monitor the degree of unfolding. The temperature at which ImmTAC1 unfolds
($T_{m}$) was measured in 100 mM sodium phosphate buffer at pH 7.0, shown in
Figure 3. The data show two unfolding transitions, corresponding to the scFv
section and the TCR section. Data were fitted to the following three-state,
biphasic function:

$y=\frac{(F+m_{F}T)+K_{1}(I+m_{I}T)+K_{1}K_{2}(U+m_{U}T)}{1+K_{1}+K_{1}K_{2}}$
(13) $K_{1}=e^{-\frac{\Delta H_{1}}{R}(\frac{1}{T}-\frac{1}{T_{m1}})}$ (14)
$K_{2}=e^{-\frac{\Delta H_{2}}{R}(\frac{1}{T}-\frac{1}{T_{m2}})}$ (15)

where $y$ is the ratio of intensities, $F$, $I$ and $U$ are the intercepts of
the lower, intermediate and upper plateaus respectively, $m_{F}$, $m_{I}$ and
$m_{U}$ are the gradients of the respective plateaus, $\Delta H_{1}$ and
$\Delta H_{2}$ are the Van’t Hoff enthalpies for the first and second
transitions respectively, and $T_{m1}$ and $T_{m2}$ are the corresponding
unfolding temperatures, defined as the temperature values halfway between
states. In buffer, the transition temperatures produced by the fit are 59.80
$\pm$ 0.05 °C and 74.28 $\pm$ 0.02 °C, corresponding to the unfolding of the
two sections. The $T_{m}$ values indicate a high degree of structural
stability, likely due to the addition of a non-native disulphide bond in the
design of the ImmTAC molecules 26. The addition of sucrose had the effect of
increasing the thermal stability, with a continuous increase in $T_{m}$ values
as sucrose concentration was increased; the highest concentration measured
here (26.6 % (w/v) sucrose) increased the unfolding temperatures by 3.48 °C
and 4.82 °C respectively (Figure 3(b)). The presence of NaCl (Figure 3(a)) had
no effect on the structural stability of the protein indicating that
differences in $\Delta H$ between conditions with and without NaCl is not due
to changes in structure. The highest NaCl concentration measured was 0.78 %
(w/v), which is comparable to the NaCl concentration in PBS buffer.

###  2.3 Observation of oligomeric states

Figure 4: a) Hydrodynamic radius of ImmTAC1 measured by DLS as a function of
concentration. Solid lines are linear fits to the data. Open symbols represent
predicted hydrodynamic radius values at infinite dilution (calculated using
Equation 17) for monomer, dimer and trimer respectively. b) Scattered light
intensity as a function of concentration. Dashed lines are theoretical
scattering intensities for monomer, dimer and trimer respectively.

Using diffusion data obtained using DLS, hydrodynamic radius may be calculated
using the Stokes-Einstein equation

$D=\frac{k_{B}T}{6\pi\eta R_{h}}$ (16)

where $\eta$ is the viscosity of the solvent. Resulting radii are plotted in
Figure 4(a) with a linear fit. Using Equation 4 and again assuming that
$R_{g}/R_{h}=0.775$, we estimate the theoretcial hydrodynamic radius to be

$R_{h}=\frac{1}{0.775}\left(\frac{3}{4\pi}\frac{M}{\rho}\right)^{1/3}.$ (17)

This relationship is in good agreement with experimental data reported by
Smilgies and Folta-Stogniew 27, who compared protein molecular weights and
hydrodynamic radius values obtained by DLS. Theoretical hydrodynamic radii for
an ImmTAC1 monomer, dimer and trimer are shown as dotted lines in Figure 4(a).
Measured values of $R_{h}$ extrapolated to infinite dilution lie between
theoretical values for monomer and trimer, suggesting that there are some
oligomers present even at the lowest concentrations. In Figure 4(b), scattered
light intensities measured by SLS are plotted along with theoretical
scattering intensities for monomer, dimer and trimer solutions respectively,
calculated from scattering theory as detailed by Minton 28. In agreement with
the hydrodynmamic radii, the measured scattering intensities suggest that the
average particle size is larger than monomer but (mostly) smaller than trimer.
It is important to note that both of these techniques give an estimation of
“average” size, for example a measurement of $R_{h}$ or scattered intensity
corresponding to “trimer” could in fact result from a mixture of monomer and a
range of small oligomers, for example.

Figure 5: Sedimentation equilibrium AUC data for ImmTAC1 measured a) 1 mg/ml
at 9000 RPM b) 11 mg/ml at 6000 RPM and c),d) 11 mg/ml at 15,000 RPM. Purple
lines are fits to the data.

To determine the oligomer sizes consistent with the DLS and SLS data, we
employed sedimentation equilibrium analytical ultracentrifugation (SE-AUC).
Data were fitted using the SEDPHAT software 29 to the equation for a single
ideal non-interacting species 30

$c(r)=c_{0}exp\left[\frac{M_{b}\omega^{2}}{RT}\left(\frac{r^{2}-r_{0}^{2}}{2}\right)\right],$
(18)

where $c_{0}$ is the concentration at a reference radius $r_{0}$, $\omega$ is
the rotor speed and $R$ is the gas constant. $M_{b}=M_{w}(1-\nu\rho_{s})$ is
the buoyant mass of the particle, with $\nu$ the partial specific volume of
the particle and $\rho_{s}$ the solvent density. At 1 mg/ml (Figure 5(a)), the
data show a good fit to a single ideal species with a fitted molecular weight
of 78.00 kDa, in good agreement with the the theoretical molecular weight for
a monomer based on the amino acid sequence (77.2 kDa). At 11 mg/ml (Figure
5(b)), attempting to fit the data to a single ideal species results in a non-
ideal distribution of residuals, pointing to some polydispersity. The
molecular weight from the fit was 209.70 kDa (2.72 times the theoretical
monomer weight). When the 11 mg/ml sample was centrifuged at a higher speed of
15,000 RPM, the data showed two distinct sedimentation pools (Figure 5(c)).
Analysing the the lower molecular weight species (Figure 5(d)), there is a
good fit to a single species with a fitted molecular weight of 80.10 kDa. This
suggests that a non-negligible amount of monomer is present, along with a
higher-order oligomer, with the total molecular weight pointing towards
trimer.

Given that our data indicate that net PPIs are dominated by electrostatic
attraction, the formation of small oligomers is a reasonable conclusion. We
may rule out partial unfolding or other structural changes as the cause of
oligomerization, since the unfolding temperatures and unfolding enthalpies
that we measured (Figure 3 and Supplementary information) indicate a high
degree of structural stability at room temperature, with the stability not
significantly enhanced by the addition of common stabilizing excipients. It is
unlikely that there are any structural changes occuring at the temperature (20
°C) at which the DLS and SLS were carried out. This further supports that the
assembly into higher order structures is due to the PPIs rather than any
partial unfolding of the protein structure.

While reports of anisotropic charge distributions leading to net-attractive
PPIs for proteins are rare, more work has been explored for colloidal systems
where “patchy” particles have been studied widely by coarse-grained
simulations 31, 32, 33. Janus particles are particles with two distinct
surfaces or regions with different properties. Charged Janus particles,
colloids exhibiting positive charge on one side and negative charge on the
other have come to be known as inverse patchy particles (IPCs). This may be
thought of as the simplest possible coarse-grained model of the surface charge
distribution of ImmTAC1, which has a positively charged end and a negatively
charged end (upper section of the molecule in Figure 1(c)). Simulations of
IPCs have been shown produce multiple phases including crystals, gels and
clusters 34, 35, 36 ranging from trimer to higher order multimers. At lower
concentrations, size-limited clusters are formed, which this supports the self
assembly observed here.

The question remains as to why the protein appears to form predominantly
trimers (by AUC) and, on the timescales of our experiments, do not proceed to
form higher order oligomers. In all conditions measured, the polydispersity
index (PDI) is smaller than 0.18, and in all conditions other than Tris, is
smaller than 0.07 (see Supplementary Information), indicating that no large
aggregates are present. A species with at least double the hydrodynamic radius
generally needs to be present in order to see the polydispersity reflected in
an increased PDI value, which corresponds to an eight-fold increase in
molecular weight. This indicates that the oligomers being formed are smaller
than 8-mer. One possible explanation is the asymmetry between the sizes of the
two charged regions. The TCR section which carries a charge of -15.9 at pH 7.0
(see Figure 1 (d)) has a solvent accessible surface area (SASA) of 215.2 nm2
while the anti-CD3 section carries a charge of 3.8 at the same pH with a SASA
of 121.2 nm2 (SASA values were calculated using the “measure sasa” tool
available in UCSF ChimeraX 37). It has been shown in simulations of both
spherical and circular IPCs that as the difference in size between the two
regions increases, the number of attractive contacts that each particle can
make without forming repulsive contacts decreases, leading to lower
coordination number and limiting cluster sizes 34, 36. Another possible
explanation is that once a small oligomer is formed, the total charge is
sufficient to stabilize the oligomer. Studies have reported that increasing
the charge of a protein, either through mutanegnesis 38, 39, 40 or nonspecific
binding of small charged molecules to the surface 41, 42 resutls in an
increase of the colloidal stability of the molecule in solution by increasing
the intermolecular electrostatic repulsion at low ionic strength. Hence, we
hypothesize that upon small oligomer formation, the local charge anisotropy is
reduced, producing an oligomer with a more balanced distribution of charge
across the surface and a more isotropic net interaction potential.

It is interesting to note that during preparation of all samples (for both
light scattering and AUC experiments), the highest concentration samples were
prepared first and diluted to obtain the lower concentrations. During AUC, the
oligomers observed in the 11 mg/ml sample were not observed in the 1 mg/ml
sample, indicating that the higher order structures had dissociated in this
diluted sample. However, the hydrodynamic radii measured by DLS close to 1
mg/ml indicate the presence of species larger than monomer, implying that
dilution alone is not enough to cause the oligomers to dissociate. Indeed, the
fact that centrifugation of the 11 mg/ml sample at higher speeds was able to
remove the oligomeric species altogether leaving monomer behind suggests that
there is no association/dissociation equilibrium between monomers and small
oligomers, at least on shorter timescales. It is possible that the formation
of trimer is weakly reversible, and that shear forces from the
ultracentrifugation itself is enough to cause dissociation at low
concentration.

##  3 Conclusions

We have shown that ImmTAC1 exhibits an anisotropic distribution of surface
charge akin to a Janus particle, due to its design as a fusion of two proteins
with different isoelectric points. Due to this feature, the molecule exhibits
net attractive interactions, dominated by electrostatic interactions between
regions of unlike charges on different molecules. This in turn leads to the
self assembly of small oligomers, which coexist with monomers.

This work has implications for the rational design of protein and/or peptide
self-assembly; it may be feasible to direct desired self-assembled states by
engineering molecules with different configurations of anisotropic surface
charge.

Understanding the impact of protein structure and anisotropy on PPIs and self
assembly is also important for formulation; ultimately these proteins are
designed to be therapeutic molecules and as such require stable solution
conditions in order to be used for treatment. Understanding the solution
behaviour of anisotropic molecules as Janus particles opens the door for more
rational approaches to formulation and selection of formulation excipients in
the future.

##  4 Methods and Materials

###  4.1 Sample Preparation

ImmTAC molecules were provided by Immunocore as 2.4 mg/ml solutions in PBS.
Reagents were purchased from Thermo Fisher Scientific and Merck-Millipore.
Buffers containing 100 mM sodium phosphate at pH 6.8 and 7, 50 mM Tris at pH
7.0 and PBS at pH 7.6 were all prepared in Milli-Q water (system by Merck
Millipore) by dissolving the appropriate amount of salts. All buffers
contained 0.02% w/v sodium azide to prevent microbial growth and were degassed
and filtered using a 0.45 $\mu$m, 47 mm cellulose filter (Millex or
Sartorius). Amicon Ultra-4 (10 kDa molecular weight cutoff) from Merck-
Millipore were used to concentrate protein solutions and buffer exchange to
the appropriate buffer. Protein concentrations were measured by UV
spectroscopy at a wavlength of 280 nm.

###  4.2 Light scattering

Static and dynamic light scattering (SLS and DLS) were performed using an
ALV/CGS-3 goniometer and ALV/LSE-5004 Multiple Tau Digital correlator with a
638.2 nm HeNe laser. The sample environment was kept at 20 °C using a Thermo
Scientific DC30-K20 water bath, and measurements were taken at a 90°scattering
angle. Protein samples were centrifuged at 13,000 xg for one hour prior to
measurements in order to remove aggregates. Measurements were made starting
with the highest concentration and performing a serial dilution to obtain the
lower concentrations.

###  4.3 Analytical Ultracentrifugation

Sedimentation equilibrium analytical ultracentrifugation (SE-AUC) was
performed using a Beckman XL-I analytical ultracentrifuge with dual sector
epon-filled centrepieces with quartz glass in an AN-50 Ti rotor. Samples were
sedimented at 1907, 4292 and 11924 xg at concentrations of 1 and 11 mg/ml.

###  4.4 Nano Differential Scanning Fluorimetry

Nano differential scanning fluorimetry (Nano-DSF) was carried out using an
Applied Photophysics SUPR-DSF. 25 $\mu$l of sample at 0.5 mg/ml was pipetted
into 384-well plates. Temperature ramps were performed betweeen 20 °C and 100
°C at a rate of 1 °C per minute. A high power 280 nm LED was used for
excitation, and the resulting fluorescence spectra were measured for
wavelengths between 310 nm and 420 nm with a 25 ms integration time. The ratio
of fluorescence intensities at 355 and 330 nm was calculated at each
temperature.

##  5 Acknowledgements

This work was made possible by funding from EPSRC (EP/T517872/1) and
Immunocore. We would like to thank Applied Photophysics for use of the SuprDSF
and continued instrument support. The Authors thank Thomas Jowitt for
assistance with AUC measurements.

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