Alexander J Pak1, John M A Grime1, Alvin Yu1, Gregory A Voth1. 1. Department of Chemistry, Institute for Biophysical Dynamics, and James Franck Institute , The University of Chicago , Chicago , Illinois 60637 , United States.
Abstract
The early and late stages of human immunodeficiency virus (HIV) replication are orchestrated by the capsid (CA) protein, which self-assembles into a conical protein shell during viral maturation. Small molecule drugs known as capsid inhibitors (CIs) impede the highly regulated activity of CA. Intriguingly, a few CIs, such as PF-3450074 (PF74) and GS-CA1, exhibit effects at multiple stages of the viral lifecycle at effective concentrations in the pM to nM regimes, while the majority of CIs target a single stage of the viral lifecycle and are effective at nM to μM concentrations. In this work, we use coarse-grained molecular dynamics simulations to elucidate the molecular mechanisms that enable CIs to have such curious broad-spectrum activity. Our quantitatively analyzed findings show that CIs can have a profound impact on the hierarchical self-assembly of CA by perturbing populations of small CA oligomers. The self-assembly process is accelerated by the emergence of alternative assembly pathways that favor the rapid incorporation of CA pentamers, and leads to increased structural pleomorphism in mature capsids. Two relevant phenotypes are observed: (1) eccentric capsid formation that may fail to encase the viral genome and (2) rapid disassembly of the capsid, which express at late and early stages of infection, respectively. Finally, our study emphasizes the importance of adopting a dynamical perspective on inhibitory mechanisms and provides a basis for the design of future therapeutics that are effective at low stoichiometric ratios of drug to protein.
The early and late stages of human immunodeficiency virus (HIV) replication are orchestrated by the capsid (CA) protein, which self-assembles into a conical protein shell during viral maturation. Small molecule drugs known as capsid inhibitors (CIs) impede the highly regulated activity of CA. Intriguingly, a few CIs, such as PF-3450074 (PF74) and GS-CA1, exhibit effects at multiple stages of the viral lifecycle at effective concentrations in the pM to nM regimes, while the majority of CIs target a single stage of the viral lifecycle and are effective at nM to μM concentrations. In this work, we use coarse-grained molecular dynamics simulations to elucidate the molecular mechanisms that enable CIs to have such curious broad-spectrum activity. Our quantitatively analyzed findings show that CIs can have a profound impact on the hierarchical self-assembly of CA by perturbing populations of small CA oligomers. The self-assembly process is accelerated by the emergence of alternative assembly pathways that favor the rapid incorporation of CA pentamers, and leads to increased structural pleomorphism in mature capsids. Two relevant phenotypes are observed: (1) eccentric capsid formation that may fail to encase the viral genome and (2) rapid disassembly of the capsid, which express at late and early stages of infection, respectively. Finally, our study emphasizes the importance of adopting a dynamical perspective on inhibitory mechanisms and provides a basis for the design of future therapeutics that are effective at low stoichiometric ratios of drug to protein.
Over the past few decades,
antiretroviral therapy (ART) for human immunodeficiency virus type
1 (HIV-1) has made substantial progress.[1−3] These advances can be
attributed, in part, to the identification of multiple enzymes that
are critical to the HIV-1 lifecycle,[4−6] such as reverse transcriptase,
integrase, and protease, as well as the development of small molecules
that competitively inhibit their activities. Current state-of-the-art
ARTs consist of a combination (cART) approach that utilizes multiple
drugs, each active against different targets; this strategy is also
referred to as highly active ART (HAART). Nonetheless, the primary
challenges for HAARTs are to maintain efficacy, safety, and tolerability.[1,2] In particular, genetic variation is responsible for drug resistance
in patients.[7] Treatment regimens must therefore
adapt to these circumstances, e.g., through the introduction of drugs
with alternative mechanisms of action, since clinically available
options are limited.An emerging class of drugs aims to disrupt
the activity of the Gag (group-specific antigen) polyprotein, which
is responsible for coordinating the late stages of the viral lifecycle.[8,9] The capsid domain (CA) of Gag is an attractive therapeutic target,
since both the assembly and maturation of infectious viral particles
are mediated by interactions between CA.[10−16] During maturation, for example, CA self-assembles into a conical
capsid (i.e., the mature core), composed of more than 1000 CA monomers,
that encases the viral genome.[17,18] Given the functional
significance of the CA, it is also important to note that its sequence
is highly conserved (around 70%) among HIV-1 subtypes, thereby reducing
the risk of viral polymorphism.[19,20] Drugs that target CA
are known as capsid inhibitors (CIs) and have been studied for nearly
a decade.[21,22] Several candidates have been identified
that demonstrate the feasibility of the CI approach, such as Bevirimat
and PF-3450074 (PF74), which have half maximal effective concentrations
(EC50), a measure of drug potencies, at nM to μM
concentrations.[23,24] Most recently, GS-CA1 was introduced
as a promising CI with an EC50 around 85 pM concentration,
and targets the same binding pocket as PF74 during early and late
stages of viral infection.[25] Nonetheless,
a clinically viable CI has yet to be discovered. A molecular understanding
of the mechanism of action for CIs is currently lacking, and represents
a barrier for the development of new therapeutics.Perhaps the
most extensively studied CI, PF74 serves as a useful example to highlight
the complexity of potential mechanisms for CIs. Initial reports of
PF74 have suggested that capsid destabilization is the primary mechanism
of action for the drug.[23] Further capsid
disassembly assays have shown that PF74 induces viral uncoating,[26−28] although a contradictory study, using assays at similar concentrations
of PF74, observed no discernible effects on viral uncoating and reverse
transcription.[29] Interestingly, similar
assays that were performed on pre-assembled CA tubules have shown
that PF74 has a stabilization effect.[28,30,31] Several binding assays have indicated that PF74 preferentially
binds to CA multimers rather than isolated CA,[23,28,31,32] and have found
that CA assembly rates increase with PF74 present.[23,31] One hypothesis that may resolve the aforementioned contradiction
is that PF74 affects the kinetics of the CA assembly process, which
warrants further investigation. Another hypothesis has also been presented
on the basis of the crystal structure of PF74 in complex with CA hexamers.
Since the drug binds to a pocket at the interface between the N-terminal
domain (NTD) and C-terminal domain (CTD) of adjacent CA monomers,[23,28] PF74 binding may preclude variable curvatures in CA oligomers that
must be adopted for closed capsids. However, since this binding pocket
has also been associated with cleavage and polyadenylation specific
factor 6 (CPSF6) and nucleoporin 153 kDa (NUP153), two cellular transport
factors that aid nuclear import,[33,34] a third possibility
is that nuclear integration of the virus is abrogated due to competitive
inhibition by PF74.[29] Taken together, these
observations suggest that PF74 (and related CIs, such as GS-CA1) can
exhibit complex, multimodal mechanisms of action that target viral
maturation, uncoating, reverse transcription, and nuclear import.
Understanding the molecular mechanisms by which CIs produce one key
aspect (capsid assembly/disassembly) of such broad activity is the
focus of this work.We use coarse-grained (CG) molecular dynamics
simulations based on prior CG models[11] to
investigate the impact of CIs on viral infectivity. We hypothesize
that the role of CIs is to perturb the population of small, intermediate
oligomers of CA. These effects are implicitly incorporated into our
CG model and used to examine the subsequent implications on late and
early stages of the viral lifecycle. We simulate both capsid assembly
and disassembly and emphasize the differences between the assembly/disassembly
pathways in models for both holo and apo capsids. Our findings suggest
that CIs have multiple modes of action by increasing the population
of mature capsids that either (i) fail to enclose viral RNA during
maturation or (ii) spontaneously disassemble before transport and
nuclear integration. Furthermore, our study implies that the targeting
of CA oligomers, which requires low stoichiometric loadings of drugs
to CA, is a possible design strategy for future therapeutics.
Results
and Discussion
We begin by considering the hierarchical nature
of viral capsid assembly, which is schematically shown in Figure . The capsid is an
enclosed protein core that is composed of tiled CA hexamers with 12
CA pentamers incorporated for topological completeness.[17,18] In solution, CA exists in a dynamic equilibrium between CA monomers
and dimers.[35,36] Furthermore, conformations of
CA dimers are inherently dynamic, as depicted in the top row of Figure , and importantly,
only adopt conformations compatible with the mature capsid with 5–10%
probability (i.e., the conformer observed in mature CA hexamers, which
is shown in the upper half of the red box in Figure ).[37] CA dimers
associate during the assembly process to form the final capsid structure.
Prior CG simulations[10,11,38] and a kinetic model[39] have shown that
a key intermediate is the trimer of dimers (TOD) structure, depicted
in the lower half of the red box in Figure . Three TODs form a complete CA hexamer that
can simultaneously template adjacent hexamers. As CA oligomers increase
in size, there are numerous possible assembly outcomes, including
stalled or malformed assemblies. However, under precise conditions
of weak CA-CA interactions with highly specific association interfaces,
which are only accessible in a limited manner, the self-assembly process
expresses the characteristic fullerene core morphology.[11] These results have suggested that the nucleation
of specific intermediate oligomers is an essential aspect of canonical
mature core assembly. It is also notable that self-assembly is predicted
to proceed even in the absence of viral RNA, which is consistent with
recent experiments that have demonstrated mature capsid formation
when co-assembled with inositol phosphate, a small-molecule co-factor.[40] The conditions used in previous simulations
implicitly include the putative effects of these co-factors, and the
simulations presented hereafter similarly assume that RNA is not essential
for core formation.
Figure 1
Schematic of the hierarchical process that is central
to HIV-1 mature capsid assembly. Within each oligomeric state of N monomers (N-mer), a variety of configurations
are possible. The canonical assembly pathway relies on constant self-correction
across N-mer states, which is contingent on a dynamic
and broad population of small N-mer intermediates.
In this work, we effectively introduce the presence of capsid inhibitor
(CI) drugs using a small but fixed population of trimers of dimers,
a 6-mer with up to three bound CIs (one at each dimer–dimer
interface), thereby perturbing the natural dynamics of the assembly
process. Snapshots of the final structures from 12 CG-MD simulations
are depicted, from which a majority population of eccentric or malformed
capsids can be seen. Here, eccentric (canonical) end-points refer
to structures with regions of densely accumulated pentamers and defective
hexamers (broadly distributed pentamers) while malformed assemblies
are non-enclosed and semi-amorphous structures.
Schematic of the hierarchical process that is central
to HIV-1 mature capsid assembly. Within each oligomeric state of N monomers (N-mer), a variety of configurations
are possible. The canonical assembly pathway relies on constant self-correction
across N-mer states, which is contingent on a dynamic
and broad population of small N-mer intermediates.
In this work, we effectively introduce the presence of capsid inhibitor
(CI) drugs using a small but fixed population of trimers of dimers,
a 6-mer with up to three bound CIs (one at each dimer–dimer
interface), thereby perturbing the natural dynamics of the assembly
process. Snapshots of the final structures from 12 CG-MD simulations
are depicted, from which a majority population of eccentric or malformed
capsids can be seen. Here, eccentric (canonical) end-points refer
to structures with regions of densely accumulated pentamers and defective
hexamers (broadly distributed pentamers) while malformed assemblies
are non-enclosed and semi-amorphous structures.To consider the impact of CIs on the CA assembly process,
we note that crystallographic structures show evidence that PF74 and
GS-CA1 preferentially bind to an inter-CA pocket between the respective
NTD and CTD domains of two adjacent CA monomers.[23,25,28] Importantly, these pockets only appear when
CA oligomerizes, such as in TODs, and appear to mediate inter-CA interactions,
thereby stabilizing multimeric CA.[31] We
therefore hypothesize that CIs stabilize the interface between CA
domains, increasing the population and/or lifetime of intermediate
oligomers. A natural question to investigate is how these perturbations
affect the overall CA assembly process.To simulate the influence
of CIs, we use the “ultra-CG” (UCG) model[11] that was previously developed to investigate
mature capsid assembly. Briefly, the UCG model consists of a Cα
resolution representation of CA helices with an elastic network model[41] (ENM) used to conserve the secondary and tertiary
structure of the protein. Select inter-CA contacts that are exposed
in the “mature” configuration are identified from X-ray
structures[18,42] and projected as “virtual”
CG sites with two possible states: (1) a non-interacting “inactive”
state and (2) an interacting (through an attractive Gaussian interaction)
“active” state. Throughout the simulation, CA dimers
periodically switch between active ([CA+]) and inactive
([CA–]) states and a constant ratio between the
two is maintained; see Figure S1 for more
details. Here, we include the effect of CI binding to CA by introducing
a fixed population of [CA+] that have pre-assembled into
TODs ([CA+]CI), as highlighted by the red box
in Figure . The TODs
are maintained by an auxiliary ENM that conserves the relative position
of adjacent dimer domains as depicted in Figure S1. We note that the additional ENM also rigidifies the TOD
and restricts the distribution of curvatures adopted by the oligomer,
which is consistent with all-atom simulations that we analyze in Figure S2. We performed CG MD simulations under
conditions that previously resulted in self-regulated assembly[11] ([CA+]/[CA–] =
0.11, [CA] = 4 mM, inert crowder density at 200 mg/mL, UCG state switching
interval at 5 × 105 timesteps) with [CA+]CI = 0.025, 0.050, 0.075, 0.100, 0.200, and 0.500 mM
and 2 replicates for each condition resulting in a total of 12 independent
trajectories; note that [CA+]CI = 0.025 mM represents
a single TOD out of a total of 616 CA dimers in a 80 nm length cubic
box. Each simulation was run for 2 × 109 timesteps
(τ) with τ = 10 fs in CG time (which is not to be confused
with actual time). Further details can be found in Methods and in
ref (11).The
bottom row in Figure depicts the outcomes of each of the 12 CG simulations. Here, we
qualitatively define three classes of core morphologies for the purposes
of the following discussion: (1) canonical, (2) eccentric, and (3)
malformed. Malformed capsids are those with non-contiguous, semi-amorphous
lattices, such as when multiple aggregates of CA merge. Canonical
and eccentric capsids refer to contiguous lattices that are distinguished
by their curvatures, and relatedly, their pentamer distributions;
in the former case, pentamers are dispersed such that all pentamers
are separated by (at minimum) a hexamer, while the latter case contains
adjacent pentamers in pentamer-dense regions, which also denote regions
of high curvature; the need for this distinction will become evident
during the discussion below. From our CG simulations, we observe 1
canonical, 10 eccentric, and 1 malformed capsid structure. We note
that an explicit trend between final core morphology and [CA+]CI, as summarized in Table , is not observed at present, although this
can be attributed to the stochastic nature of the process; additional
independent sampling at each [CA+]CI would be
required to confirm a potential trend with respect to [CA+]CI, but is currently computationally cost prohibitive
and outside the scope of this work. Nonetheless, insight into the
influence of [CA+]CI on structural aspects of
the assembly process can be obtained, and certainly with respect to
inhibitor-free systems as discussed later. Our simulations relatedly
suggest that the majority of cores that form due to CIs are highly
pleomorphic with many cores exhibiting large degrees of curvature.
This is a notable result when compared to the expected behavior of
wild-type (WT) viruses. Previous cryo-electron microscopy (cryo-EM)
surveys of mature WT virions have revealed a variety of capsid phenotypes,
including conical capsids, tubular capsids, incomplete capsids and
dual capsids, although the majority (around 60 to 90%) appears to
be conical.[43−46] Our simulations suggest that the presence of CIs shifts this distribution
toward the formation of non-canonical cores, which is consistent with
cryo-EM images of virions treated by GS-CA1.[25] The wide distribution of end-point morphologies shows that even
slight positive perturbation to TOD populations has profound effects
on CA assembly that favor alternative pathways. We note that this
view is conceptually consistent with recent reports of pathway complexity
observed in supramolecular polymers, which emerges when assembly kinetics
cannot be described by simple nucleation-and-elongation models.[47−49] We next discuss the origins of the distinct pleomorphism in lattice
morphology that emerges due to the presence of CIs.
Table 1
Summary of End-Point Capsid Morphologies for Each of the 12 Listed
Systemsa
[CA+]CI (mM)
set 1
set 2
0.025
eccentric, closed [3]
eccentric, closed [6]
0.050
canonical, open [1]
malformed [12]
0.075
eccentric, open [8]
eccentric, closed [7]
0.100
eccentric, closed [5]
eccentric, open [10]
0.200
eccentric, open [9]
eccentric, open [11]
0.500
eccentric, closed [4]
eccentric, open [2]
The numerical
label in brackets refers to the associated snapshot in Figure with left-most = 1 and right-most
= 12.
The numerical
label in brackets refers to the associated snapshot in Figure with left-most = 1 and right-most
= 12.To characterize the
lattice morphology, we first recognize that the CA lattice can be
represented as a connected graph. One may conceive of each CA monomer
as a vertex (v) on a graph (G) with
an edge (e) between vertices signifying their proximal
nature. Within the assembled CA lattice, e represents
dimeric CA as well as adjacent intra-capsomer CA; in other words,
each v is ideally connected to three neighboring v within G, which strictly represents the
largest assembled CA lattice. Throughout the simulation trajectories,
we use a distance criterion to construct G:with V and E denoting the set of v and e in G, i and j denoting the index of each CA monomer, dNTD (dCTD) denoting
the measured distance between residue V36 (E180) in i and j, and rc denoting
a cutoff distance of 2.75 nm; further justification for this cutoff
distance and choice of residues is included in Figure S3. Next, we consider a property of graphs known as
eccentricity (ecc), which effectively measures how
“far” a given vertex is from its furthest vertex. The ecc of each v is formally defined aswhich quantifies the maximum path distance among the
set of minimum paths between v and every other v in V.
For our purposes, we consider the normalized ecc (λi = ecc(v)/max{ecc(v)}) and statistical
measures on its distribution (P(λ)) as a metric
to classify CA lattice morphologies.The utility of P(λ) can be shown with four representative CA lattices
(extracted from a single trajectory) that are analyzed in Figure ; additional discussion
on P(λ) can be found in Figure S4 and Table S1. Figure a depicts an early stage of CA nucleation in which
the lattice appears largely two-dimensional and isotropic around its
six-fold (C6) axis. The resultant P(λ) exhibits a normal distribution with the smallest
(largest) λi associated with the center (edges) of
the lattice. In Figure b, the lattice has grown with some edges appearing “jagged”
(a nascent dendrite, in some sense), which is indicative of anisotropic
nucleation. The λi associated with v that participate in these jagged edges is large (e.g., λi > 0.8) in comparison to interior v; in
fact, as these edges become more dendritic, we expect large λi to be increasingly favored in P(λ).
Here, we argue that anisotropic growth at the edges of the CA lattice
are relevant since the branching junction between dendrites may nucleate
into pentamers, presumably to anneal the lattice and to minimize potential
strain due to curvature. In Figure c, the lattice has fully wrapped into an enclosed 2D
lattice, such that all v can be considered interior v. Now, P(λ) favors a higher population
of small λi (e.g., λi < 0.8)
with large λi associated with oblong areas of the
capsid; note that pristine cleavage of the capsid, such that the edges
are largely composed of hexamers that are a uniform distance from
the narrow end of the capsid, recovers a P(λ)
with a normal distribution, as seen in Figure d. This analysis (and the additional discussion
in Supporting Information) suggests that
we may use the skew and kurtosis of P(λ) (i.e.,
γ(λ) and κ(λ)) to qualitatively classify CA
lattice growth; γ(λ) ≈ 0 and κ(λ) <
0 signifies a lattice with edges that are isotropically distant from
the lattice center while γ(λ) < 0 and κ(λ)
< 0 (or γ(λ) > 0 and κ(λ) > 0) represents
a lattice with anisotropic edges (or with contiguous and uniform oblong
character, such as in complete enclosures).
Figure 2
Topology of the assembled
CA lattice is assessed by the eccentricity (λ) of each vertex
(i.e., each CA monomer) in a graph representation of the lattice.
We show the distribution of λ (P(λ))
at select points during one trajectory of [CA+]CI = 0.100 mM for demonstrative purposes: at (a) 1 × 108, (b) 7 × 108, and (c) 14 × 108 MD
timesteps. The same analysis is performed in (d) using half of the
lattice from (c), i.e., after cleavage by a plane perpendicular to
the long axis of the capsid. Representative lattices are depicted
as insets in (a-d) with each monomer shown as a sphere colored by
its λ from red (λ = 0.5) to blue (λ = 1.0). The
topology of the lattice can be qualitatively characterized by the
skew of the distribution of λ (γ(λ)) in which (a,d)
zero skew is indicative of an open lattice with isotropic edges, (b)
negative skew is indicative of an open anisotropic lattice, and (c)
positive skew is indicative of a closed, non-spherical lattice.
Topology of the assembled
CA lattice is assessed by the eccentricity (λ) of each vertex
(i.e., each CA monomer) in a graph representation of the lattice.
We show the distribution of λ (P(λ))
at select points during one trajectory of [CA+]CI = 0.100 mM for demonstrative purposes: at (a) 1 × 108, (b) 7 × 108, and (c) 14 × 108 MD
timesteps. The same analysis is performed in (d) using half of the
lattice from (c), i.e., after cleavage by a plane perpendicular to
the long axis of the capsid. Representative lattices are depicted
as insets in (a-d) with each monomer shown as a sphere colored by
its λ from red (λ = 0.5) to blue (λ = 1.0). The
topology of the lattice can be qualitatively characterized by the
skew of the distribution of λ (γ(λ)) in which (a,d)
zero skew is indicative of an open lattice with isotropic edges, (b)
negative skew is indicative of an open anisotropic lattice, and (c)
positive skew is indicative of a closed, non-spherical lattice.On the basis of the aforementioned
metric, we now analyze time-series profiles in Figure , in which we compare CG trajectories from
CI-bound cases (12 trajectories) to that of non-CI cases (four trajectories);
two of the non-CI trajectories were obtained from previous work[11] while two additional trajectories were generated
using the same conditions. We find that in all cases (both CI-bound
and non-CI) the assembly rate of CA hexamers (Figure a) is comparable with the exception of [CA+]CI = 0.200–0.500 mM, which is accelerated
by nearly a factor of 2 compared to the [CA+]CI = 0.000 mM case. More evident differences are observed in the assembly
rate for pentamers (Figure b). Here, pentamer incorporation rates are positively correlated
with an increase of [CA+]CI. The observed increase
in multimerization rate is consistent with experimental multimerization
assays for PF74,[23,31] and our simulations suggest that
CI-bound populations of CA (even at stoichiometric ratios as low as
1 mol%) can have a profound impact on multimerization rates. Interestingly,
the onset of pentamer incorporation is notably earlier in the CI-bound
cases (around (50–100) × 106τ) compared
to the non-CI case (around (250–350) × 106τ).
The incorporation of CI-bound TODs (Figure c) is observed to directly precede pentamer
incorporation and suggests that CIs influence core morphology by promoting
pentameric defects; the origins of this behavior will be discussed
below.
Figure 3
Assembly time-series plots that depict (a) the number of assembled
hexamers, (b) the number of assembled pentamers, (c) the number of
incorporated inhibitor-bound TODs (TODCI), and the (d)
skew (γ(λ)) and (e) kurtosis (κ(λ)) of the
distribution of eccentricities (λ) throughout the assembled
lattice as a function of CG MD time step (shifted with respect to
the onset of lattice growth) for each system within the listed concentration
of capsid inhibitors (CIs). We find accelerated assembly, especially
with respect to pentamers, in the CI-present simulations, which appear
to be commensurate with negative γ(λ) and κ(λ),
i.e., a descriptor that indicates anisotropic edge growth in the protein
lattice. The shaded region depicts the standard deviation around the
mean from four trajectories
within the listed range of concentrations while the solid line depicts
a single trajectory. In (f), molecular snapshots of the protein lattice
for the 0.100 mM case (green line in (a)–(e)) at the listed
MD time step (τ [×106]) are shown; green, red,
and blue NTD domains in capsomers indicate hexamers, pentamers, and
incomplete capsomers, respectively.
Assembly time-series plots that depict (a) the number of assembled
hexamers, (b) the number of assembled pentamers, (c) the number of
incorporated inhibitor-bound TODs (TODCI), and the (d)
skew (γ(λ)) and (e) kurtosis (κ(λ)) of the
distribution of eccentricities (λ) throughout the assembled
lattice as a function of CG MD time step (shifted with respect to
the onset of lattice growth) for each system within the listed concentration
of capsid inhibitors (CIs). We find accelerated assembly, especially
with respect to pentamers, in the CI-present simulations, which appear
to be commensurate with negative γ(λ) and κ(λ),
i.e., a descriptor that indicates anisotropic edge growth in the protein
lattice. The shaded region depicts the standard deviation around the
mean from four trajectories
within the listed range of concentrations while the solid line depicts
a single trajectory. In (f), molecular snapshots of the protein lattice
for the 0.100 mM case (green line in (a)–(e)) at the listed
MD time step (τ [×106]) are shown; green, red,
and blue NTD domains in capsomers indicate hexamers, pentamers, and
incomplete capsomers, respectively.Analysis of the changes to the topological character of the
growing CA lattice may provide further insight into the effect of
CIs on CA nucleation and growth. In all cases (CI-bound and non-CI),
γ(λ) and κ(λ), as seen in Figures d,e, is initially close to
0.0 and −1.0. The former, however, shifts toward negative values
directly preceding the onset of pentamer incorporation (and commensurate
with CI-bound TOD incorporation in the CI-bound cases); recall that
the combination of negative γ(λ) and negative κ(λ)
is a feature indicative of non-uniform protrusions along the lattice
edges. The resultant pentamer incorporation typically seems to anneal
the lattice such that γ(λ) increases toward values greater
than or equal to 0.0, and the rate of pentamer incorporation is temporarily
suppressed. However, as the edges of the lattice continue to nucleate
CA, anisotropic character may re-emerge and promote the additional
incorporation of pentamers. The edges of the lattice may ultimately
anneal to form an enclosed CA lattice (with γ(λ) and κ(λ)
≥ 0). Here, CA within incomplete capsomers, which are likely
to be in areas of high curvature, continue to relax until pentamers
are formed, e.g., as evident by the time-series profiles in which
pentamer counts increase while hexamer growth is stalled. Molecular
snapshots from a CI-bound case that exhibits all of these steps are
shown in Figure f.We interpret these collective results by proposing that CI-bound
TODs (i.e., the fixed TODs in our simulations) accelerate CA assembly
compared to CI-free cases by increasing the number of accessible assembly
pathways. First, let us consider that TODs, while important building
blocks, still require free CA dimers (and potentially, other small
oligomers) to continue assembly of the CA lattice.[11] Each CA dimer favors two binding interfaces that should
be satisfied for successful association, as seen in Figure a. Hence, continued CA assembly
requires the near-simultaneous fastening of two CA dimers at adjacent
edges of the lattice, which subsequently create new edges for future
second-order CA association events. The increased population of TODs,
on the other hand, enables CA lattice growth through the near-simultaneous
binding of a TOD and CA dimer. In this alternative assembly pathway,
new binding edges also appear. It is instead likely that subsequent
assembly steps only require a single CA dimer, as seen in Figure a, which therefore
accelerates CA assembly. We note that at low [CA+]CI (e.g., the 0.025–0.050 mM regime in this work) this
alternative assembly pathway is only feasible when the initial nucleation
of the CA lattice is independent of the CI-bound TOD. In the event
that the CI-bound TOD is the initial nucleator and the reservoir of
available CI-bound TODs is depleted, the canonical assembly pathway
is expected to proceed; this scenario is consistent with the [CA+]CI = 0.050 mM case that resulted in a canonical
core (see Table ).
Figure 4
(a) Schematic
of the canonical assembly pathway (top) through the dual association
of CA dimers and accelerated assembly pathway (bottom) through the
association of a trimer of dimers (TOD) that is stabilized by capsid
inhibitors (CIs) and a CA dimer. The stars represent potential binding
interfaces; yellow stars indicate the need for an adjacent CA dimer
to associate nearly simultaneously, while red stars indicate sites
that are energetically satisfied by a single CA dimer. The topological
character of an assembling lattice over time is quantified by the
skew of its eccentricities (γ(λ)) with distributions calculated
from a swarm of 50 trajectories in the (b) absence and (c) presence
of CIs. Here, γ(λ) ≈ 0 is suggestive of an open
isotropic lattice, γ(λ) < 0 is suggestive of an open
anisotropic lattice, and γ(λ) > 0 is suggestive of
a uniform and oblong lattice (such as in closed mature capsids). These
results suggest the preference of isotropic (emergence of anisotropic)
lattice growth during canonical (CI-perturbed) assembly, which is
highlighted in the region bound by the dashed red box. Each trajectory
was discretized into 20 equal bins before histograms were computed
(n = 375 per histogram).
(a) Schematic
of the canonical assembly pathway (top) through the dual association
of CA dimers and accelerated assembly pathway (bottom) through the
association of a trimer of dimers (TOD) that is stabilized by capsid
inhibitors (CIs) and a CA dimer. The stars represent potential binding
interfaces; yellow stars indicate the need for an adjacent CA dimer
to associate nearly simultaneously, while red stars indicate sites
that are energetically satisfied by a single CA dimer. The topological
character of an assembling lattice over time is quantified by the
skew of its eccentricities (γ(λ)) with distributions calculated
from a swarm of 50 trajectories in the (b) absence and (c) presence
of CIs. Here, γ(λ) ≈ 0 is suggestive of an open
isotropic lattice, γ(λ) < 0 is suggestive of an open
anisotropic lattice, and γ(λ) > 0 is suggestive of
a uniform and oblong lattice (such as in closed mature capsids). These
results suggest the preference of isotropic (emergence of anisotropic)
lattice growth during canonical (CI-perturbed) assembly, which is
highlighted in the region bound by the dashed red box. Each trajectory
was discretized into 20 equal bins before histograms were computed
(n = 375 per histogram).To demonstrate the emergence of additional assembly paths
in the presence of CIs, we perform 50 short independent simulations
(over 150 × 106 τ) of CA assembly with [CA+]CI = 0.000 and 0.100 mM starting from a pre-assembled
lattice with 37 CA hexamers (i.e., the equivalent of four concentric
“layers” of hexamers). We depict the progression of
γ(λ) in Figure b,c and compare the two cases; we focus on γ(λ)
as κ(λ) remains consistently negative during this early
growth phase (see Figure ). In the [CA+]CI = 0.000 mM case (Figure b), we find that
the majority of trajectories maintain γ(λ) around 0.0.
However, in the [CA+]CI = 0.100 mM case (Figure c), a fraction of
the trajectories instead adopt γ(λ) < 0, which we suggest
is commensurate with increasingly anisotropic lattice growth, while
this fraction increases as time progresses. This observation is most
evident after 50 × 106 τ; states associated
with γ(λ) < – 0.75 are sampled by CI-bound trajectories
(see red box in Figure c) while absent from non-CI trajectories (see red box in Figure b). We therefore
suggest that the presence of CI-bound TODs enables an alternative
assembly pathway through enhanced CA association kinetics and increasingly
anisotropic lattice growth. Here, we should mention that our UCG model
does not explicitly consider the possible binding of CIs to CA after
multimerization. However, as we expect CIs to stabilize CA association,
thereby accelerating nucleation and growth (or hindering CA reconstruction),
the qualitative impact on assembly is likely comparable to that of
the current UCG model.One consequence of the accelerated CA
assembly, and relatedly, the rapid pentamer incorporation, induced
by CIs is that the resultant mature cores may fail to enclose viral
RNA for two reasons. First, the enhanced CA assembly kinetics may
preclude the need for viral RNA and nucleocapsid (NC), i.e., the ribonucleoprotein
(RNP) complex, to serve as templates for assembly; some experiments
have suggested that the RNP complex nucleates mature CA assembly,[43] which is further mediated by integrase,[44,50] although this behavior does not appear to be universal as evident
by mature capsid formation even in the absence of an enclosed RNP
complex.[44,45,51] Second, CI-perturbed
cores are likely to adopt highly curved morphologies with small internal
volumes that may impede the encapsulation of the RNP complex. In our
simulations, cores that underwent full enclosure were observed to
contain on the order of 100 hexamers (see Figure a). For comparison, previous accounts from
cryo-EM data suggest canonical capsid cores contain on the order of
200 hexamers. Based on an effective reduction of surface area by a
factor of 2, we approximate an associated reduction of internal volume
by up to 65% (for simple spherical geometries). However, we note that
RNA condensation, which is likely dependent on salt and viral protein
content, may allow the RNP complex to occupy these reduced volumes;
note that such condensation is suggested by the localization of RNP-associated
densities in cryo-EM images within the broad region of conical mature
capsids.[43,51] Nonetheless, the proposed phenotype is consistent
with previous cryo-EM experiments that have observed RNP-associated
density outside that of protein cores, especially those treated with
inhibitors.[44−46] Hence, our simulations suggest that one mechanism
of action of CIs is to increase the population of eccentric cores
that may fail to enclose the RNP complex.In the event that
CI-bound mature cores successfully condense the RNP complex, we also
investigated their viral uncoating behavior. During the post-entry
stages of viral infection, capsid disassembly and trafficking toward
the nuclear pore is highly regulated.[6] Although
the uncoating process is not completely understood, it has been suggested
that a combination of biological triggers, such as the binding of
host cell factors[52−54] or the initiation of reverse transcription,[27,55] act as signals to delay then initiate disassembly. For instance,
cyclophilin A (cypA) can stabilize the mature core throughout trafficking
and disengage in a downstream event to allow induced uncoating by
transportin 3 (TNPO3).[56] On the other hand,
restriction factors (such as TRIM5α and TRIMCyp) can induce
premature uncoating.[57−59] Maintenance of the viral capsid post-entry is additionally
purported to be an essential barrier against innate immune responses.[60] Hence, perturbations to canonical uncoating
behavior that result in spontaneous uncoating may also reduce infectivity.We simulate putative post-entry events following the procedures
established in ref (11), in which we deplete the concentration of available [CA+] (= 0 mM) and integrate dynamics over 12 × 108τ. In Figure , we compare time-series profiles that depict the fraction
of the mature core that persists. Here, we select and compare four
closed end-point morphologies from our simulations described above.
As a control, we also prepared a closed canonical core that was pre-assembled
based on alignment to an atomic model for a complete capsid[61] (PDB 3J3Y). As seen in Figure , the 3J3Y core remained stable throughout our simulated time-scale, in agreement
with previous all-atom MD simulations[61−63] that suggest the core
is inherently stable at equilibrium. Interestingly, three out of four
of the selected eccentric cores undergo a clear stepwise disassembly
process, as described by the processive periods of plateaus and decrements
seen in Figure a.
The molecular snapshots depicted in Figure a of an eccentric core ([CA+]CI = 0.075 mM) throughout the disassembly process provide insight
into the origins of this behavior. During the plateau periods, pentamers
switch between pentameric states (red capsomers in Figure a) and that of an incomplete
hexamer (blue capsomers in Figure a). In this latter state, it is more likely for a CA
dimer to dissociate from the lattice, which has been suggested as
the rate-limiting step for viral uncoating.[64] The resultant defect is then the site of spontaneous dissociation
of CA. In comparison, we find that the fourth core ([CA+]CI = 0.500 mM) remains largely intact, which is evident
from the flat profile in Figure a. However, fluctuations that correspond to the aforementioned
structural instability of pentamers in pentamer-dense regions eventually
result in core opening. Hence, all of the studied eccentric cores
exhibit a tendency toward spontaneous CA disassembly due to inherent
instabilities in high curvature regions with large pentamer density,
which can contribute a secondary mechanism for viral inhibition.
Figure 5
(a) Disassembly
time-series plot that depicts the fraction of remaining hexamers and
pentamers (with respect to the initial size of the mature capsid core)
for the five listed systems as a function of MD time step. All four
of the eccentric cases exhibit spontaneous disassembly, which appear
to be initiated at sites with large pentamer density. Molecular snapshots
of the protein lattice for the 0.075 mM case (cyan line in (a)) at
the indicated points are shown; green, red, and blue capsomers indicate
hexamers, pentamers, and incomplete capsomers, respectively. (b) Molecular
snapshots from each trajectory at the indicated MD time step (τ
[×106]) are shown. The inhibitor-bound TODs are represented
as gray capsomers. This data suggests that capsid inhibitors promote
the formation of “leaky” mature cores that spontaneously
open at regions of high curvature (or high pentamer density), and
represents one failure mechanism that suppresses infectivity.
(a) Disassembly
time-series plot that depicts the fraction of remaining hexamers and
pentamers (with respect to the initial size of the mature capsid core)
for the five listed systems as a function of MD time step. All four
of the eccentric cases exhibit spontaneous disassembly, which appear
to be initiated at sites with large pentamer density. Molecular snapshots
of the protein lattice for the 0.075 mM case (cyan line in (a)) at
the indicated points are shown; green, red, and blue capsomers indicate
hexamers, pentamers, and incomplete capsomers, respectively. (b) Molecular
snapshots from each trajectory at the indicated MD time step (τ
[×106]) are shown. The inhibitor-bound TODs are represented
as gray capsomers. This data suggests that capsid inhibitors promote
the formation of “leaky” mature cores that spontaneously
open at regions of high curvature (or high pentamer density), and
represents one failure mechanism that suppresses infectivity.The extent of disassembly within
our simulated time-scales is considerably variable, but does suggest
that increasing [CA+]CI is negatively correlated
with a destabilization effect on fully enclosed mature cores. This
is in contrast to some capsid stability assays[26,28] and fluorescence experiments[64] that suggest
that purified cores are destabilized when treated with PF74. However,
a direct comparison should not be made as canonical cores that are
treated with PF74 and those that are assembled in the presence of
PF74 may also be morphologically distinct, as suggested by our results
above (see Figure ). Our disassembly experiments instead seem to corroborate a capsid
integrity assay that suggests that cores formed with high concentrations
of PF74 have similar integrity to that of the WT.[29] Hence, we expect inhibitory effects based on disassembly
to only be relevant at lower concentrations of CIs. We further stress
that the observed relationship between [CA+]CI and core stabilization is not necessarily indicative of the same
relationship between [CA+]CI and infectivity
(as we expect the opposite to be true). Recall that we only simulate
the disassembly of cores that are fully enclosed within our simulated
time, which represents a subset of the cores observed in our simulations.
We speculate that the fraction of malformed and eccentric cores that
fail enclosure is positively correlated with [CA+]CI, which would, for instance, corroborate the increasing inhibition
of infection at increasing PF74 concentration.[23,26]It is important to mention that our CG simulations have not
explicitly considered the influence of host cellular factors, which
impact downstream events such as trafficking, nuclear import, and
integration as discussed previously. For instance, all-atom MD simulations
have demonstrated that the binding of PF74 induces greater allosteric
coupling between the cypA binding loop and a CA hinge region, although
the implications for cypA activity remain unclear.[62] Intriguingly, PF74 is able to inhibit infection even in
the absence of some host cellular factors, including CPSF6 and cypA,
although their presence can induce mostly cooperative (but sometimes
antagonistic) influences on PF74 efficacy in a dose-dependent manner.[65] However, the presence of NUP153 appears to be
critical for PF74 efficacy at low concentrations.[65] As NUP153 binds to the same pocket as PF74, it is conceivable
that the latter competitively inhibits pre-integration complexes (PICs)
from engaging with NUP153 for nuclear entry. The plateaus from our
disassembly profiles in Figure , such as when [CA+]CI = 0.100 mM, suggest
that partially disassembled cores may exist as metastable states.
Indeed, PF74-treated cores were recently found to undergo partial
uncoating.[66] We find that all CI-bound
TODs remained bound to the partially disassembled capsids, as depicted
in Figure b. Thus,
in the event that viral uncoating proceeds uninhibited, a third mechanism
of action is possible: the remaining CA assembly, which is likely
to be part of the PIC, may consist of an elevated coverage of CI-bound
CA that inhibit NUPs. A careful examination of this third mechanism
of action is outside the scope of the current study, but would be
a valuable subject for investigation.On a final note, our simulations
demonstrate that a CG model can aid interpretation of the anomalously
broad activity of CIs observed in experiments. In the case of PF74,
the binding of CIs to pre-established binding pockets stabilizes CA
multimers in tubular structures and prevents disassembly.[28,30,31] Our simulations incorporate this
stabilization effect with the use of TODs that are fixed during dynamics.
We only consider a low stoichiometric ratio of CI-bound CA given that
experimental EC50 estimates tend to be in the range of
μM concentrations or below.[23−25] Our results show that
perturbing TOD distributions in this way is sufficient to induce alternative
assembly pathways that yield diverse capsid morphologies, including
eccentric cores that were previously seen as a minority population
in WT viruses.[43−45] Given the importance of CIs during the assembly process,
we suggest that future studies take care in distinguishing inhibitor
behavior based on post-treatment of viral cores and integration during
late stages (i.e., virion production) of the viral lifecycle. The
increased diversity of capsids formed under the influence of CIs compared
to WT virus results in multiple mechanisms of action, which may help
explain the cooperativity that is suggested by PF74 dose–response
curves.[65] Furthermore, these mechanisms
appear to be fundamentally different from that of inhibitors that
target monomeric CA, which tend to affect either early or late (but
not both) stages of the viral lifecycle. For example, CAP-1 and CAI
bind to CA monomers and prevent proper CA association at key interfaces
(e.g., the CTD dimeric interface) during late-stage assembly.[67,68] For these types of CIs, higher drug concentrations (e.g., μM
or above) may have been required to ensure that the population of
apo CA monomers is sufficiently repressed to prevent complete assembly.
Hence, CIs that target the highly regulated dynamical processes observed
throughout the viral lifecycle by means of CA oligomer subpopulations
may have two primary benefits: (1) broader spectrum inhibitory effects
and (2) reduced stoichiometric requirements that facilitate drug delivery
challenges.
Conclusions
In summary, we use CG molecular dynamics
simulations and elucidate underlying mechanisms that contribute to
the broad-spectrum HIV-1 inhibitory effects of capsid inhibitors (CIs),
such as PF74 and GS-CA1, by virtue of small perturbations to the hierarchical
self-assembly of viral capsid (CA) proteins. We find that an important
mode of action by CIs is to stimulate CA association and propagate
anisotropic assembly pathways, which results from the stabilization
of a subpopulation of trimer of dimers (TODs); this behavior is consistent
in all of our CG simulations, even at the lowest accessible drug to
CA stoichiometry of less than 1 mol%. Consequently, pentameric defects
appear to be rapidly incorporated, thereby increasing the expression
of eccentric cores, that is, mature cores with inherently large curvature
and pleomorphism. Capsids of this phenotype may unsuccessfully enclose
the viral nucleic acid and nucleocapsid protein (RNP) complex, which
is one possible failure mode for infection. However, in the event
that the RNP complex is encapsulated, a secondary failure mode during
post-entry events is observed from our capsid disassembly simulations.
Here, regions of the capsid that are dense with pentameric defects
appear to be inherently unstable and initialize CA dissociation; eccentric
cores that form due to CIs may therefore spontaneously disassemble
after entry into the cytoplasm. Taken together, our findings reveal
that CIs affect processes during both viral maturation and uncoating.
While not explicitly observed in this work, we expect additional inhibitory
effects to emerge during processes involving host cellular factors.
Our results also suggest that the identification of potential binding
pockets that appear upon CA oligomerization, especially those with
small degrees of genetic polymorphism, and the design of small molecules
that specifically target these sites—even at low stoichiometric
loadings—will facilitate the design of HIV-1 (and other viral)
inhibitors with similarly broad mechanisms of action.
Methods
Coarse-Grained Modeling and Simulation
As mentioned above, the CG models used in this work, e.g., for
CA and the inert crowding agent, are described in ref (11) and summarized in Figure S1. Our simulations contained CA, pre-assembled
TODs, and inert crowding agents, as described in the main text, which
were initially dispersed randomly within the periodic simulation box.
The key difference from the simulations performed in ref (11) is the addition of pre-assembled
TODs using an ENM between adjacent dimer domains (depicted in Figure S1) to preserve the inter-dimer distances
around the binding pocket for CIs such as PF74 and GS-CA1; a harmonic
bending stiffness of 1.0 kcal/mol was used. Configurations were allowed
to equilibrate over 5 × 106τ without any attractive
interactions. Production runs were then performed as described in
the main text, while [CA+]/[CA–] UCG
state switching was attempted every 5 × 105τ,
i.e., the subset of assembly-competent CA dimers from all available
CA dimers in solution were stochastically chosen while a constant
fraction of active species was maintained. All simulations were performed
in the constant NVT ensemble at 300 K using a Langevin
thermostat[69] with a damping period of 100
ps and τ = 10 fs. All simulations were run using an in-house
MD engine called UCG-MD, which is optimized to run implicit-solvent
UCG simulations with dynamic load-balancing and runtime algorithms.[70] Neighbor lists up to 4 nm with an additional
1 nm skin depth were used, while load balancing was attempted every
2 × 104τ. Molecular snapshots were saved every
1 × 106 τ for analysis.
Data Analysis
Graph analysis was performed using the python package NetworkX 2.1
(http://networkx.github.io/). A graph was constructed for each molecular snapshot following
the criteria described in the main text and Figure S3. Hexamers and pentamers were identified by vertices (i.e.,
CA monomers) that participated in a closed cycle of length six and
five, respectively. The remaining nodes were identified as components
of incomplete capsomers. The λ of each vertex was computed using
the eccentricity function.
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