Review

On the TRAIL of Better Therapies: Understanding
TNFRSF Structure-Function
Éva S. Vanamee and Denise L. Faustman *Immunobiology Laboratories, Massachusetts General Hospital, 13th Street, Building 149, Rm. 3602,
Boston, MA 02129, USA; eva.vanamee@gmail.com* Correspondence: faustman@helix.mgh.harvard.edu; Tel: +1-617-726-4084
Received:02 February 2020; Accepted: 17 March 2020; Published: 20 March 2020

Abstract: Tumor necrosis factor (TNF) superfamily ligands show diverse biological functions, suchas the induction of apoptotic cell death or cell survival and proliferation, making them excellent
therapeutic targets for cancer and autoimmunity. We review the latest literature on TNF receptor
superfamily signaling with a focus on structure-function. Using combinatorics, we argue thatreceptors that cluster on the cell surface and are activated by membrane-bound ligands need toarrange in a highly ordered manner, as the probability of random ligand and receptor arrangements
matching up for receptor activation is very low. A growing body of evidence indicates that
antiparallel receptor dimers that sequester the ligand binding site cluster on the cell surface, forminga hexagonal lattice. Upon ligand binding, this arrangement puts the activated receptors at the right
distance to accommodate the downstream signaling partners. The data also suggest that the same
geometry is utilized regardless of receptor type. The unified model provides important clues about
TNF receptor signaling and should aid the design of better therapies for cancer and various immune
mediated diseases.
Keywords: TRAIL; TRAIL receptors; apoptosis; TNFSF signaling; receptor clustering; antiparallel
dimer; hexagonal lattice; cancer

1. Introduction
The TNF-related apoptosis-inducing ligand (TRAIL/Apo2L) [1] is a member of the TNF
superfamily (TNFSF). Members of the TNFSF signal through their corresponding family of TNF
receptors (TNFRSF) (Table 1). TRAIL has generated a lot of interest as a potential cancer therapy on
the basis of the observation that it can selectively induce cancer cell death. In addition, because TRAIL
provides an external trigger for apoptosis, it has the potential to overcome resistance to internal
triggers of apoptosis after radiation or chemotherapy. There have been many excellent reviews on
TRAIL biology and the mechanism of action with implication for therapeutic applications in recent
years [2–8]. Here, we focus on the structure-function of TRAIL and extend our discussion to othermembers of the TNFSF/TNFRSF to illustrate the mechanism of signaling by reviewing the most upto-date and relevant information from the scientific literature.
2. Receptors and Ligands Need to Cluster in a Highly Ordered Manner on the Cell Surface for
Efficient Signaling
TRAIL and other TNFSF ligands are type II membrane proteins that share the classic TNF
homology domain (THD) and form noncovalent trimers [9,10]. Trimerization is essential for receptor
activation and the membrane-bound ligands have been shown to signal more efficiently via theircorresponding receptors compared to the cleaved, soluble ligands. The TNFRSF receptors are type I
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2 of 13transmembrane proteins and their ectodomains contain between 1 and 6 pseudorepeats of cysteinerich domains (CRDs) (Table 1) [10–12].
Experimental data support receptor oligomerization of TRAIL and other TNFRSF receptors on
the cell surface but there have been conflicting models proposed over the years [4,6,13,14]. Activating
several receptors all at once by their corresponding membrane-bound ligands necessitates that both
the receptors and the ligands are arranged with the same geometry, which rules out random
receptor/ligand arrangement on the cell surface. To illustrate this, let us assume that there are 10
separate trimeric receptors that are pre-arranged on the surface with the potential sites they canoccupy represented by lattice points in a 10 by 10 matrix. We consider each trimer as a single unit.
The first receptor trimer can be placed onto one of 100 potential sites of the 10 × 10 matrix. Once thatplace is taken, the second receptor trimer has one less, i.e., 99 potential places to occupy, and so on,
resulting in 100 × 99 × 98 × 97 × 96 × 95 × 94 × 93 × 92 × 91 potential ways the 10 receptor trimers canbe arranged, which can also be written as 100 factorial divided by 90 factorial (100!/90!). Because theorder in which the 10 receptor trimers are placed is not important, we need to divide the above
number by the permutation of 10 or 10 factorial (10!). This leads to a potential combination of thereceptor arrangement referred in combinatorics as “hundred choose ten” or C (100,10) and can becalculated as 100!/(90! × 10!). Even with such a small number of receptors, there are more than 17
trillion ways to arrange them in our example. Not all are unique though, and we need to subtract
cases where a simple rotation or translation can move one pattern onto another.

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Table 1. Tumor necrosis factor receptor superfamily (TNFRSF) members, their ligands, andintracellular binding partners.
TNFRSF Receptor(TNFRSF#, Other Names)
Death receptors
TNFR1 (1a, CD120a)
Fas (6, CD95)
TRAILR1 (10A, DR4, CD261)
TRAILR2 (10B, DR5, CD262)
NGFR (16, p75NTR, CD271)
DR3 (25 or 12, TRAMP)
DR6 (21, CD358)
EDAR
Receptors with TRAFinteracting motif
TNFR2 (1b, CD120b)
LTβR (3)

Numberof CRD‡

Intracellular
Binding
Partner

TNFSF Ligand(TNFSF#, Other Names)

4
3
3¶
3¶
4
4¶
4
3¶

TRADD, FADD, RIP
FADD
FADD, TRADD, RIP
FADD, TRADD, RIP
NADE
TRADD, FADD
TRADD, RIP
EDARADDTNF (2, TNF-α), LTα (1, TNF-β), LTβ (3)FasL (6, CD178)
TRAIL/Apo2L (10, CD253)
TRAIL/Apo2L (10, CD253)
NGF (not a TNFSF member)
TL1A (15, VEGI), TWEAK (12)N-APP (not a TNFSF member)
EDA-A1

4
4

TRAF1-3
TRAF2-4, TRAF5
TRAF1-3, TRAF5,
TRAF6
TRAF1-3, TRAF5,
TRAF6
TRAF2, TRAF3,
TRAF5
TRAF1-3, TRAF5
TRAF1-3
TRAF1-3, TRAF5,
TRAF6

TNF (2, TNF-α), LTα (1, TNF-β)LTα (1, TNF-β), LTβ (3) as LTαβ2,, LTα2β

TRAF2, TRAF6

TWEAK (12)OX40 (4, CD134)

4¶

CD40 (5)4CD27 (7)3CD30 (8)4-1BB (9, CD137)

64

RANK (11A, CD265)

4

Fn14 (12A, TWEAKR;
CD266)1

TACI (13B, CD267)

2

BAFFR (13C, BR3, CD268)

1

HVEM (14, CD270)

3

BCMA (17, CD269)

1

GITR (18, AITR, CD357)
TROY (19, TAJ)RELT (19L)3
3¶
1

XEDAR (27)3¶

Decoy receptors
TRAILR3 (10C, DcR1,
CD263)TRAILR4 (10D, DcR2,
CD264)

TRAF2-3, TRAF5,
TRAF6
TRAF2, TRAF3,
TRAF6
TRAF1-3, TRAF5
TRAF1-3, TRAF5,
TRAF6
TRAF1-3
TRAF1-3, TRAF5
TRAF1
TRAF1, TRAF3,
TRAF6
n/a

OX40L (4, CD252)
CD40L (5, CD154)
CD27L (7, CD70)
CD30L (8, CD153)
4-1BBL (9, CD137L)RANKL (11, TRANCE, CD254)

APRIL (13, CD256)
BAFF (13B/20, BLys, THANK, CD257)
LIGHT (14, CD258), LT-α (1, TNF-β)APRIL (13, CD256), BAFF (13B/20, BLys,
THANK, CD257)
GITRL (18, AITRL, TL6)?
Not known
EDA-A2

3¶

TRAIL/Apo2L (10, CD253)

3¶

TRAIL/Apo2L (10, CD253)

OPG (11B)

4

DcR3 (6B)

4

TRAIL/Apo2L (10, CD253), RANKL (11,
TRANCE, CD254)
FasL (6), TL1A (15, VEGI), LIGHT (14,CD258)‡: Uniprot (uniport.org) assignments were used to determine the number of cysteine-rich domains (CRD)
Contains truncated CRD domains.

We can simplify the translation problem by subtracting patterns from the 17 trillion total that
only occupy one half of the 10 × 10 matrix. Every such pattern in one half of the matrix can beCells 2020, 9, 764

4 of 13translated onto a matching pattern in the other half. This can be calculated as C(50,10) = 50!/(40! × 10!)~10 billion, a small rounding error compared to the 17 trillion total. There are other patterns that arecounted more than twice, but their numbers are even smaller and can be neglected. The ~17 trillion
combinations have to be divided by 4 to take into account the four 90 degree rotations that transform
one pattern into another. After taking rotational and translational symmetry into account, we end up
with more than 4 trillion unique patterns or unique ways the receptor trimers can be arranged. Figure
1a illustrates one such pattern. Because the membrane-bound ligands need to be arranged the exact
same way as the receptors in order for them to align for binding and activation, the probability of aparticular random ligand arrangement matching up with a random receptor arrangement in thisexample is less than 1 in 4 trillion. This illustrates the vast number of combinations even for such asmall number of receptors. In reality, the number of receptors are vastly higher on the cell surface
and vary depending on the type of receptor and the cell. As an example, TNF receptors can vary froma little over a hundred on T cells in healthy subjects [15] to several thousand on human neutrophils[16]. Therefore, the probability of random receptors matching up with randomly arranged
membrane-bound ligands is extremely low and highly unlikely. Although it may not seem obvious,
this also rules out pairs of receptor trimers randomly arranged on the cell surface (illustrated in Figure1b) and argues for both the receptors and ligands being arranged in a highly ordered, non-random
cluster with matching geometry. It is not necessary that all receptors are in one large cluster, they
could be expressed in smaller groups, but all the smaller clusters will have to be highly ordered. The
implications of this go beyond the TNF receptor superfamily and we believe will also apply to any
receptor that clusters on the cell surface and is activated by membrane bound ligands.

Figure 1. Representative arrangements of receptors on the cell surface. (a) An example of a randomarrangement of 10 receptor trimers limited to lattice points of a 10 × 10 matrix, top view. Even withthis constraint there are more than 17 trillion possible combinations (C(100,10)), more than 4 trillionof them unique. To activate these receptors with their corresponding membrane-bound ligands, theligands would have to be arranged exactly the same way to simultaneously activate the receptors.
The probability of that is less than 1 in 4 trillion. (b) Random arrangement of pairs of receptor trimers.
Having 10 receptors arranged in pairs of trimers on the cell surface lowers the number of unique
receptor arrangements to over 38 million and the probability that one of these arrangements will

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5 of 13match up with corresponding random ligands is still very low. (c) Tight hexagonal lattice with parallel
dimer arrangements of TNF receptor 1 (TNFR1) [Protein Data Bank (PDB) ID:1NCF] top view, andside view of a single dimer. The N and C terminal are labeled. (d) Hexagonal lattice with antiparallel
receptor dimers of TNFR1 (PDB ID: 1NCF) top view, and side view of a single antiparallel dimer. Fivetimes as many receptors can be fit into the same area in the tight hexagonal cluster in (c) compared to
the larger hexagonal lattice occupied by the antiparallel receptor dimers. The red circles in (c) and (d)illustrate the trimerization interface. The molecular representations were created by the moleculargraphics program PyMOL [17].

Ligand-free TNFRSF receptors have been shown to form two different dimers [18,19]. One form
is a parallel dimer in which the receptors are in a head-to-head arrangement, meaning that the two
N-terminals line up next to each other on one end and the C-terminals on the other. This dimer form
exposes the ligand binding site on the outside (Figure 1c). The other dimer form is an antiparallel orhead-to-tail arrangement, in which the two receptors are connected by their N-terminal ends to eachother but run in the opposite direction, separating the C-terminal ends by more than 100 Å (Figure1d). This dimer interface buries part of the ligand binding site. It has also been shown that TRAIL
and other TNFRSF receptors cluster on the cell surface and interact via their pre-ligand assembly
domains (PLADs) formed by the N-terminal, CRD1 and part of the CRD2 domains [20–22]. Both theparallel and antiparallel dimers can multimerize on the cell surface as dimers of trimers forming
hexagonal lattices [14,18]. Both hexagonal arrangements anchor the receptors as trimers in themembrane and satisfy the requirement for PLAD interactions. The parallel dimers can form a tighthexagonal cluster with no separation between receptor trimers and the antiparallel dimers canarrange in a larger hexagonal lattice where each receptor trimers separated by more than 100 Å(Figure 1c,d). As we have argued earlier, the larger hexagonal lattice is able to accommodate thedownstream signaling partners with the same geometry regardless of receptor type leading to the
hypotheses of a uniform signaling mechanism [14]. Next, we are going to review additional data
supporting this model.
3. TRAIL and Its Receptors
Among the TNFSF, TRAIL signaling biology is one of the most complex. In addition to binding
to its two death receptors, TRAIL receptor 1 (TRAIL-R1, also referred to as death receptor 4 or DR4)
and TRAIL receptor 2 (TRAIL-R2/DR5), it also binds to three decoy receptors, TRAIL-R3 (also known
as decoy receptor 1, DcR1) and TRAIL-R4 (also known as decoy receptor 2, DcR2) and soluble
receptor osteoprotegerin (OPG) that can sequester TRAIL and therefore also functions as a decoy
receptor [23–26]. The differential expression of the DcRs and TRAIL death receptors on different cell
types can modulate the outcome of TRAIL function resulting in cell death of certain cell types but notof others. Similar to other TNFSF ligands, a trimeric TRAIL ligand binds to three receptor monomers
to form the active signaling complex shown in Figure 2. Unique among TNFSF ligands is that TRAIL
contains a Zn ion that is coordinated by a Cys residue (Cys230) from each monomer. The loss of Zn
ion can lead to instability and loss of activity of human recombinant TRAIL (hrTRAIL) [27,28]. Several
successful approaches have been utilized to overcome these challenges and to improve the cancer
targeting potential of hrTRAIL that have been reviewed extensively elsewhere [3,29].

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Figure 2. TRAIL-R2 activation and formation of the death inducing signaling complex (DISC). The
TRAIL-TRAIL-R2 complex structure (PDB ID: 1DU3) is shown in cartoon representation (top left).
The TRAIL ligand trimer (pink) surrounded by three TRAIL-R2 receptors (blue). These complexes
can cluster on the cell surface in a hexagonal lattice (top middle) that are stabilized by agonist
antibodies shown in yellow (top right). Below two TRAIL-TRAIl-R2 complexes are illustrated in sideview. The three cysteine-rich domains (CRD1-3) of TRAIL-R2 are labelled in the left complex. The
transmembrane domain of TRAIL-R2 is also shown (PDB ID: 6NHY). A model of the DISC complex
is illustrated below the cell membrane in spheres representation. The partial model of the TRAIL
death domain (TRAIL-DD) dimer is shown in dark and light blue, the Fas associated domain (FADD)
dimer is shown in dark and lighter green, and the Caspase 8 death effector domain (DED) dimer isshown in red and orange. On the right a model of how the DISC may arrange in a hexagonal lattice
is illustrated in top view.

4. TRAIL Receptor Downstream Signaling: DISC Assembly and Caspase Interactions
TRAIL-R1/R2, similar to Fas induce apoptosis via formation of the death inducing signaling
complex (DISC) that, in addition to the death domain (DD) of TRAIL contains Fas associated death
domain (FADD) and the cysteine protease, Caspase-8. The Fas-DD-FADD complex structure

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provided insight into how these intracellular DISC components may form a hexagonal lattice after
Fas ligand binding and Fas receptor activation [30]. Shen et al. more recently have reported thestructure of Caspase-8 DEDs in an open and closed conformation [31]. Both structures show a dimer
with a novel domain-swapped conformation in which the C-terminal helices are exchanged between
the two subunits. The open conformation exposes a hydrophobic patch that may facilitate theinteraction with FADD in the DISC. On the basis of these structures, we have created our model ofthe DISC complex. First, we modeled the TRAIl-R2-DD monomer based on the Fas-DD open
conformation structure [30] using the Phyre2 server [32]. The server returned a partial structure witha 99.9% confidence interval. The TRAIL-R2 DD-FADD complex was then modeled on the basis of theFas-DD-FADD complex [30]. We used the full FADD structure [33] to complete the TRAIL-R2-DDFADD complex. Finally, we docked the structure of the caspase-8 DED domain-swapped open dimer
structure [31]. The catalytic domains of caspase-8 were not included. The resulting model is shownin Figure 2. This is only a crude model and will likely be improved over the coming years as moreexperimental data become available. However, it clearly demonstrates that in order to accommodate
components of the DISC, the TRAIL receptors have to be separated by ~100 Å or more. This model isfurther supported by data of a TRAIL-R2/DR5 agonist antibody that binds on the outside of thereceptor and bridges two receptor trimers together [13] that are similarly separated by ~100 Å or
more. This antibody stabilizes the receptors in the hexagonal lattice (Figure 2) and shows synergistic
activity when co-administered with hrTRAIL [13,34]. This strategy in general could be employed toother TNFRSF members. Although there are no structures available of the ligand-free TRAIL
receptors, the structure of TRAIL-R2 in complex with human cytomegalovirus (HCMV) UL141 showsa heterotetramer in which TRAIL-R2 is arranged in an antiparallel orientation bridged by an HCMVUL141 dimer [35]. It was proposed that HCMV UL141 blocks the transport of TRAIL-R2 from theendoplasmic reticulum (ER) to the cell surface, thus downregulating TRAIL-R2 surface expression
and function. The structure indicates that the membrane proximal ends of the full TRAIL-R2
ectodomain would be separated by more than 90 Å. This indicates that TRAIL-R2 may exist as an
antiparallel dimer at least in the ER. The structure of the transmembrane domain (TMD) of TRAILR2/DR5 is a notable exemption to the above examples, showing that the TMD can dimerize and may
form tight hexagonal clusters [36]. However, this structure was solved without the ectodomain of thereceptor. The ectodomain is wider by about 25 Å than the TMD and therefore would interfere with
TMD hexamer formation in the full receptor. In addition, the tight cluster could not accommodate
the DISC complex. The structure, if physiologically relevant, may therefore likely represent a state
after receptor ectodomain shedding.
In summary, the experimental data on both the cell surface receptors and in the cytosol on DISC
assembly are consistent with the hexagonal lattice model with a separation of ~100 Å or more between
receptor trimers proposed earlier [13,14,30,31] but not with the tight hexagonal cluster with noseparation between receptor trimers because that would leave no room for the downstream binding
partners that make up the DISC. One might argue that pairs of receptor trimers could easily formtight hexamers and then be separated upon activation by the ligand or by an antibody and movefurther apart as necessary to accommodate the downstream signaling partners. However, as we
discussed earlier, even a few pairs of receptor trimers arranged randomly would have tens of millions
of ways to arrange and an extremely low probability to match up with randomly arranged
membrane-bound ligands. When we speak of pairs of trimers as the minimal unit of signaling it has
to be always considered in the context of a cluster of receptors with a well-defined geometry. If one
starts with a tight cluster, shown in Figure 1c, the movement of a receptor trimer would inevitably
affect other receptors around it. The tight cluster would have to go through a huge reorganization,
moving around many receptors in the membrane after activation to accommodate the downstream
binding partners resulting in loss of signaling efficiency. The most effective receptor quiescent stateis one that anchors the receptors in place in the membrane with the same geometry as the downstream
signaling partners requiring only conformational changes upon activation. The hexagonal model oftrimers of antiparallel dimers satisfies this requirement.

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5. TNFRSF Antiparallel Dimer Stabilization by Antibodies Effectively Block Ligand Binding
Historically, it has been challenging to design powerful antagonists against TNFRSF members.
TNF receptor 2 (TNFR2) is a master switch of cell survival and proliferation [37] and, as reported
earlier, antagonist antibodies targeting TNF receptor 2 (TNFR2, TNFRSF1b) can successfully
downregulate immunosuppressive T regulatory cells and eliminate tumor cells that overexpress the
TNFR2 oncogene for survival [38,39]. These antibodies have shown promise in several cancer models
including ovarian cancer [38] and advanced Sézary syndrome, an aggressive form of cutaneous Tcell lymphoma [40]. When examining their mechanism of action, the best antagonists have beenfound to bind to the CRD3-CRD4 region of TNFR2 and to require either the full antibody or F(ab’)2
to effectively block TNF binding [38]. In addition, these antibodies do not rely on FcγR cross-linking
that often weakens antagonism and, in some cases, turns antagonist antibodies into outright agonists.
The data supports a mechanism where the best antagonist binds to the antiparallel dimer form of thereceptor locking in the quiescent state [14,38]. In another example, an antagonist antibody to CD40
(TNFRSF5) has also been shown to bind to the antiparallel dimer form of the receptor [41]. The
antibody bound as a single Fab domain making interactions to both CD40 monomers in the dimer. It
was further found that the antiparallel dimer stabilization was essential for antagonism as
demonstrated by a closely related antibody that only interacted with a single CD40 monomer andhad agonistic activity [41]. As we discuss next, the structure of the herpes virus entry mediator(HVEM) in complex with B and T lymphocyte attenuator (BTLA) represents another example of an
antiparallel arrangement with BTLA assisting HVEM oligomerization, and playing a regulatory role
in HVEM function.
6. Regulating Receptor Function via Antiparallel Complex Formation
HVEM (TNFRSF14) functions as a molecular switch modulating B and T lymphocyte activation[42], dendritic cell proliferation [43] and protecting mucosal epithelia from damage during
inflammation [44]. In the cytosol it interacts with several TNF receptor associated factor (TRAF)
homologs including TRAF2 to induce NFkB activation. LIGHT and LT- α are the two canonical
TNFSF ligands that activate HVEM. BTLA and CD160 are the non-conventional ligands thatmodulate HVEM function. In addition, HVEM also interacts with viral proteins. Indeed, HVEM was
first identified as a receptor that facilitates the entry of herpes simplex virus (HSV) via its interaction
with HSV glycoprotein D (gD) [45].
BTLA is an immune-globulin superfamily (IgSF) glycoprotein with two immunoreceptor
tyrosine-based inhibitory motifs [46]. BTLA is an inhibitory receptor on T lymphocytes withsimilarities to cytotoxic T lymphocyte-associated antigen 4 (CTLA-4) and programmed death 1 (PD1). The crystal structure of the HVEM-BTLA complex shows a heterotetramer consisting of a dimerof HVEM-BTLA heterodimers [47] (Figure 3) that resembles the antiparallel dimer of TNFR1 shownin Figure 1d. We believe that it is the heterotetramer seen in the crystal structure that represents thecis complex on the cell surface and not the model that was put forward in the original study [47].
CD160 and gD are similar to BTLA in that they also contain an Ig fold. BTLA and gD are monomericin solution, but it has been shown that both may form dimers on the membrane, giving biologicalimportance to the observed crystal structure [48,49]. On the basis of these data, we propose that the
HVEM antiparallel complexes with BTLA may arrange in a hexagonal lattice on the cell surface
representing the receptor quiescent state (Figure 3). Since BTLA is a type I transmembrane protein
similar to HVEM, both can be co-expressed and anchored to the cell by their C-terminal ends. In thecis configuration BTLA does not interfere with LIGHT or LT-α binding, instead it serves to facilitate
HVEM oligomerization on the cell surface and to inhibit the ligand independent activation of HVEM.
In contrast to BTLA, the CD160-HVEM structure shows a 1:1 complex and it has a lower affinity for
HVEM than BTLA [50]. There are conflicting data on whether CD160 is also monomeric on the cellsurface [51–53]. If confirmed, a monomeric CD160 bound in cis may function to limit HVEM
oligomerization on the cell surface in the above model. This shines potentially new light onto BTLA,
CD160 function. Rather than being true ligands, they serve as regulatory proteins modulating HVEM

Cells 2020, 9, 764

9 of 13oligomerization and control receptor activation. In addition to cis interactions, both BTLA and CD160
can also interact in trans adding to the complexity of HVEM regulation [49].
It is important to note here that the viral protein HCMV UL141 that blocks TRAIL-R2 surface
expression interacts with TRAIL-R2 via its Ig-like domain. This highlights a potentially more
extensive relationship between the Ig and TNF superfamilies then previously appreciated. As isshown in Table 1, there are many TNFRSF receptors with three or fewer CRD domains that could
potentially utilize a co-regulatory protein to aid their oligomerization on the cell surface.

Figure 3. Regulation of herpes virus entry mediator (HVEM) signaling by B- and T lymphocyte
attenuator (BTLA). The structure of the HVEM-BTLA cis complex (based on PDB ID: 2AW2) is shownin side view in cartoon representation (top left). The HVEM monomers are shown in blue andmonomers of the BTLA dimer in yellow and orange respectively. BTLA aids the oligomerization of
HVEM. The complexes may arrange in a hexagonal lattice shown on the right in surface
representation (top view). Trimeric LIGHT binding to HVEM activates the receptors to form the
LIGHT-HVEM complexes shown in cartoon representation (PDB ID: 4RSU). LIGHT is shown inmagenta and HVEM in blue. The CRD1-3 are labelled in the left complex. The receptor ligand
complexes may also cluster to form a hexagonal lattice shown on the right in top view. The HVEMLIGHT complexes are bound to TNF related associated factor (TRAF) in the cytosol shown inchartreuse. TRAF trimerization is initiated by LIGHT binding and HVEM activation. This then leads
to the dimerization of the TRAF-N domain shown in cyan. The TRAF complexes also form aCells 2020, 9, 764

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hexagonal lattice shown on the right in surface representation. The TRAF complex was modeled fromseveral structures as described earlier [14].

7. Conclusions
We have argued that the probability of random receptor arrangement on the cell surface
matching up with randomly arranged membrane bound ligands is extremely low. Membrane boundligands are more efficient at receptor activation because they allow the simultaneous activation ofmultiple receptors. However, for that to happen, the receptors and their corresponding ligands need
to be arranged on the cell surface in a highly ordered manner with matching geometry. This should
apply to not only members of the TNF receptor superfamily but to every clustered receptor activatedby membrane bound ligands. We discussed how TRAIL-R1/R2 and other TNFRSF members clusteron the cell surface forming highly ordered hexagonal lattices. The available experimental data
supports a receptor quiescent state of a hexagonal lattice made up of trimers of antiparallel dimers.
For receptors like HVEM that are unable to dimerize on their own, co-regulatory proteins may aid
receptor oligomerization on the cell surface and modulate receptor function. It remains to be seen if
this more broadly applies to other TNFRSF receptors. The same process can also be exploited by viralproteins to modulate immune function. The antiparallel arrangement not only prevents accidental
receptor activation but places the receptors with the right geometry for the downstream signaling
partners to assemble. There may be exceptions but the same geometry seems to apply to both thedeath receptor family and for the TRAF-interacting TNFRSF members. Having the same scaffolding
geometry can allow the switching between apoptosis and NFkB activation for the same receptor suchas TNFR1 depending on the downstream binding partners.
Many questions still remain about the mechanism of TNFRSF signaling, but the presented model
provides important insights into TNFRSF biology and for the design of better targeted therapies at
the molecular level for cancer and other immune mediated diseases. Antibodies that lock in the
antiparallel dimer provide an effective strategy for creating antagonist therapeutics against TNFRSF
receptors. On the other hand, effective agonism may include both ligand and antibody-based
approaches that utilize the hexagonal model of activation.
Author Contributions: É.S.V. and D.L.F. wrote and revised the manuscript. All authors have read and agreed
to the published version of the manuscript.
Funding: This research received no external funding.
Conflicts of Interest: The authors declare no conflict of interest.

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