HIV-1 protease inhibitors are part of the highly active antiretroviral therapy effectively used in the treatment of HIV infection and AIDS. Darunavir (DRV) is the most potent of these inhibitors, soliciting drug resistance only when a complex combination of mutations occur both inside and outside the protease active site. With few exceptions, the role of mutations outside the active site in conferring resistance remains largely elusive. Through a series of DRV-protease complex crystal structures, inhibition assays, and molecular dynamics simulations, we find that single and double site mutations outside the active site often associated with DRV resistance alter the structure and dynamic ensemble of HIV-1 protease active site. These alterations correlate with the observed inhibitor binding affinities for the mutants, and suggest a network hypothesis on how the effect of distal mutations are propagated to pivotal residues at the active site and may contribute to conferring drug resistance.
HIV-1 protease inhibitors are part of the highly active antiretroviral therapy effectively used in the treatment of HIV infection and AIDS. Darunavir (DRV) is the most potent of these inhibitors, soliciting drug resistance only when a complex combination of mutations occur both inside and outside the protease active site. With few exceptions, the role of mutations outside the active site in conferring resistance remains largely elusive. Through a series of DRV-protease complex crystal structures, inhibition assays, and molecular dynamics simulations, we find that single and double site mutations outside the active site often associated with DRV resistance alter the structure and dynamic ensemble of HIV-1 protease active site. These alterations correlate with the observed inhibitor binding affinities for the mutants, and suggest a network hypothesis on how the effect of distal mutations are propagated to pivotal residues at the active site and may contribute to conferring drug resistance.
In the absence of a
vaccine and in lieu of a cure, antiretroviral
combination therapy has been the main form of treatment for individuals
infected with HIV. As is the case with treatment of most rapidly evolving
viruses/diseases, drug resistance decreases the effectiveness of treatment.
The high replicative capacity of HIV and the infidelity of the reverse
transcriptase quickly lead to a heterogeneous population of viruses
within patients, from which resistance has emerged to all 30 of the
currently used antiviral drugs.HIV-1 protease inhibitors (PIs)
have recently emerged as the most
effective drugs in the treatment of HIV.[1−3] PIs are competitive active
site inhibitors that mimic the transition state of the enzyme and
are the most potent antiretroviral drugs for the treatment of HIV/AIDS.[4] These drugs are ideal for therapy as they target
the viral protease responsible for viral maturation and thus the spread
of the virus. Unfortunately, the rapid evolution of HIV-1, coupled
with the selective pressure of therapy, results in many viable multidrug
resistant variants. In fact, mutations at 45 of the 99 residues that
make up HIV-1 protease have been implicated in drug resistance.[5] While resistance due to mutations at 11 of these
45 residues can be explained as direct changes within the active site,
the resistance mechanisms for the majority of the remaining mutations
outside the active site of the enzyme mostly remain elusive.Drug resistance mutations in HIV-1 protease allow the enzyme to
become less susceptible to inhibition while retaining enzymatic activity.
Points of inhibitor–protease contact at residues within the
active site where the inhibitor protrudes beyond the substrate envelope
are sites selected for resistance, as their interactions are more
critical for inhibitor binding than substrate turnover.[6] While mutations at some active site residues,
such as 82 and 84, lead to resistance to all PIs, other mutations
are signatures of specific inhibitors, such as D30N for nelfinavir
and I47A for lopinavir.[7] These mutations
directly impact inhibitor binding by altering or reducing contacts
necessary for inhibiting the enzyme, but can also simultaneously decrease
the catalytic efficiency or enzymatic fitness. The mutations at the
remaining 34 of the 45 residues associated with drug resistance occur
outside the active site. These changes have often been considered
secondary or accessory mutations, and are thought to indirectly impact
inhibitor binding while assisting in enzyme fitness or stability.
Structural studies on the effect of several HIV-1 protease secondary
mutations have provided insights into how inhibitor binding may be
affected.[8−12] However, for the most part, their specific role in protease inhibitor
resistance or mechanism of action has not been elucidated.Darunavir
(DRV) is the most potent of the United States Food and
Drug Administration (FDA) approved HIV-1 protease inhibitors. This
high potency combined with the inhibitor’s fit within the substrate
envelope appears to account for DRV’s robustness against drug
resistance.[13,14] Drug resistance to DRV usually
occurs only in patients who have high levels of pre-existing PI resistance,
requiring at least seven mutations to simultaneously occur for therapeutic
failure. In fact, DRV is being investigated as a potential monotherapy
in treatment-naïve patients.[15]In DRV-resistant HIV variants, many changes occur outside the active
site of the enzyme in complex combinations. Single site mutations
cannot confer high levels of resistance to DRV, and a combination
of multiple mutations including those outside the active site are
needed to decrease potency. However, the role of these mutations in
conferring resistance is not well understood: some may be enhancing
enzymatic activity, while others may directly confer drug resistance
and still others may be residual mutations from previous therapy history.
In this study, we examine some of the most common of these mutations,
V32I, L33F, L76V, and L90M (as a control; not a signature of DRV resistance
but frequent in multidrug resistance[10]),
for their impact on DRV inhibition. Using a combination of static
and dynamic structural analyses, by determining crystal structures
of complexes and performing molecular dynamics simulations, we elucidate
the possible roles of these secondary mutations both independently
(L76V, L90M, V32I) and in combination (V32I/L33F) in conferring resistance.
We find how mutations at residues with no direct contact with the
inhibitor can alter the structure and dynamics of the protease to
affect inhibitor binding through common mechanisms, which we define
through a “network hypothesis”.
Results
To determine
how mutations remote from the active site contribute
to DRV resistance in HIV-1 protease, the impact of four mutations
(L76V, L90M, V32I, and V32I/L33F; Figure 1)
in a subtype B background was investigated in terms of enzyme inhibition,
inhibitor-bound crystal structures, and molecular dynamics simulations.
Figure 1
Structure
of HIV-1 protease variants bound to DRV. Crystal structures
of mutant protease variants superimposed with the WT protease complex
structure in blue. The side chains of mutation sites are in red sticks.
Structure
of HIV-1 protease variants bound to DRV. Crystal structures
of mutant protease variants superimposed with the WT protease complex
structure in blue. The side chains of mutation sites are in red sticks.
Enzyme Inhibition
The enzyme inhibition
constant for
DRV was measured against each of the protease mutants, in addition
to WT subtypes B and C for comparison (Table 1). DRV is highly potent against WT subtype B protease with a Ki of 2 pM, as we previously reported.[13] The level of inhibition for the mutants varied
from 2 pM to 45 pM, with the L90M mutant being inhibited as potently
as the WT protease and the V32I/L33F double mutant exhibiting the
greatest decrease in susceptibility to DRV with a fold-change greater
than 20. Hence, single mutations are not enough to confer high levels
of DRV resistance, as expected, and the mutations had varying degrees
of effects on DRV susceptibility.
Table 1
DRV Interaction and
Susceptibility
of HIV-1 Protease Variantsa
protease variant
Ki (pM)
vdW (kcal/mol)
ΔvdW (kcal/mol)
subtype C
5 ± 2 (2.5)
WT
2 ± 1 (1.0)
–44.5
L76V
3 ± 2 (1.5)
–43.0
1.5
L90M
2 ± 2 (1.0)
–44.4
0.1
V32I
7 ± 9 (3.5)
–44.2
0.2
V32I/L33F
45 ± 18 (22.5)
–43.3
1.2
DRV inhibition constants (Ki) of HIV-1
protease variants, with fold-changes
relative to subtype B WT protease in parentheses. The overall vdW
interaction energy between the inhibitor and protease was determined
from crystal structures.
DRV inhibition constants (Ki) of HIV-1
protease variants, with fold-changes
relative to subtype B WT protease in parentheses. The overall vdW
interaction energy between the inhibitor and protease was determined
from crystal structures.
Crystal
Structures
To structurally characterize the
effects of the mutations on DRV binding, we determined the crystal
structures of variants L76V, L90M, V32I, and V32I/L33F, which diffracted
to resolutions of 1.5–1.9 Å in the P212121 space group (Table 2). Alignment of the four complex structures on our previously
determined structure of the WT protease–DRV complex (1T3R[16]) showed that the variants had only minor backbone variations,
mainly in the 20s loop likely due to crystal packing differences (Figure 1). Therefore, the mutations had very little impact
on the overall backbone structure of the protease.
Table 2
Crystallographic Statistics for DRV-Bound
HIV-1 Protease Structures
Detailed Structural Analysis of DRV Binding from Cocrystal Structures
The high-resolution cocrystal structures enabled detailed analysis
of protease–DRV contacts in each of the five complexes. The
WT complex had the most extensive van der Waals (vdW) contacts with
the inhibitor with a favorable energy of −44.5 kcal/mol, similar
to V32I and L90M variants (Table 1). The L76V
variant and V32I/L33F double mutant lost more than 1 kcal/mol in vdW
contact energy with DRV relative to the WT complex. Thus, despite
no large-scale changes in the protease backbone, subtle changes in
repacking occurred around DRV in these two complexes to weaken protease
interactions with the inhibitor. However, the extent of contacts lost
with DRV in the mutant crystal structures with respect to WT protease
does not correlate completely with the fold-change loses in Ki values (Table 1).Contacts involving specific DRV moieties (Figure 2) and protease active site residues (Figure 3) were analyzed in detail. In general, the impact of mutations
on DRV contacts are larger at the P2 and P2′ than the central
P1 and P1′ moieties. The bis-THF group of DRV P2 moiety forms
the most extensive contacts in all of the complexes (Figure 2), but also loses considerable contacts due to the
mutations, except in the V32I structure. In the case of V32I, DRV
contacts are retained as in the WT complex, consistent with no significant
change in total vdW or Ki values (Table 1). When this mutation occurs together with L33F
in the double mutant though, contacts are lost in all three of P2,
P1, and P2′ moieties. In the L90M variant, although interactions
get weaker at the P2 position, gain of contacts at P1 compensate for
this loss yielding comparable total vdW contacts and susceptibility
to DRV as WT protease.
Figure 2
Contacts of DRV moieties with HIV-1 protease variants.
(A) Chemical
structure of DRV (TMC114) with the inhibitor moieties P2–P2′
indicated. (B) vdW interaction energy (kcal/mol) of DRV moieties for
contacts with the protease active site in the crystal structures,
and changes in vdW interaction energy in mutant structures relative
to the WT complex. Positive values indicate loss of contacts.
Figure 3
Contacts of protease active site residues with
DRV in the crystal
structures. (A) The two monomers of WT protease in surface representation
with the bound DRV displayed as sticks. Active site residues are colored
from blue to red for increasing vdW contacts with the inhibitor. The
monomer that interacts mostly with the P2–P1 moieties of DRV
is on the left, and the primed-side monomer is on the right. (B) The
vdW interaction energy of active site residues in crystal structures
(top), and changes in mutant complexes relative to the WT structure
(bottom). Only the residues displaying considerable changes relative
to WT are included for both monomers. See Figures S1 and S2 in the Supporting Information for all active site residues.
Positive values indicate loss of contacts.
Contacts of DRV moieties with HIV-1 protease variants.
(A) Chemical
structure of DRV (TMC114) with the inhibitor moieties P2–P2′
indicated. (B) vdW interaction energy (kcal/mol) of DRV moieties for
contacts with the protease active site in the crystal structures,
and changes in vdW interaction energy in mutant structures relative
to the WT complex. Positive values indicate loss of contacts.Contacts of protease active site residues with
DRV in the crystal
structures. (A) The two monomers of WT protease in surface representation
with the bound DRV displayed as sticks. Active site residues are colored
from blue to red for increasing vdW contacts with the inhibitor. The
monomer that interacts mostly with the P2–P1 moieties of DRV
is on the left, and the primed-side monomer is on the right. (B) The
vdW interaction energy of active site residues in crystal structures
(top), and changes in mutant complexes relative to the WT structure
(bottom). Only the residues displaying considerable changes relative
to WT are included for both monomers. See Figures S1 and S2 in the Supporting Information for all active site residues.
Positive values indicate loss of contacts.While the apo form of the protease is a symmetric homodimer,
DRV
induces asymmetry to the complex and thus despite identical residues
mutating in both monomers, the effect of these mutations on protease–inhibitor
contacts is distinct in the two monomers (Figure 3). Specifically, L76V and L90M mutations cause considerable
loss of contacts at I47, but to a lesser extent at I47′. Other
active site residues whose contacts are altered in mutant structures
include I50 at the tip of the flaps, and 81–82–84 at
the 80s loop. Contrary to previous reports,[17] we do not see any major enhancement of DRV contacts with the catalytic
D25 in the L90M mutant, or any of the other 3 variants.Residue
32 is at the periphery of the active site, and V32I mutation
causes a unique pattern of rearrangement of inhibitor contacts than
the other variants studied. Unlike L76V and L90M, contacts with 47
are retained in V32I. Although the backbone is not shifted significantly,
the proximity of residue 32 to the 80s loop causes subtle rearrangements
to result in repositioning of the DRV away from I84’s and more
toward I50s at the tip of the flaps. As a result, DRV contacts with
residues 84, 81′, and 84′ are lost but those with 50
and 50′ are enhanced. The larger isoleucine also forms additional
contacts with the inhibitor in the unprimed-side monomer. In the V32I/L33F
variant, which loses an additional 7-fold in binding affinity relative
to V32I (Table 1), the contacts are rearranged
again. In contrast with V32I alone, additional loss of interactions
at residues 47 and 50 are observed. These losses of contacts are similar
to the alterations observed in the L76V and L90M variants. Thus, the
double mutant V32I/L33F variant alters the active site in a synergistic
manner, leveraging both alterations similar to L76V and L90M, and
some changes from V32I. The change in variants’ affinity is
not simply due to a loss of van der Waals contacts, but an interdependent
change in optimal contacts.In the WT complex, DRV forms a network
of hydrogen bonds within
the active site involving both backbone and side chains. Most of these
bonds, including the two water-mediated ones with I50, are conserved
in the variant complexes. Two exceptions occurred in the L76V and
V32I complexes: Consistent with the loss of vdW contacts, in the L76V
complex a hydrogen bond to the backbone of D30 is lengthened from
2.0 to 3.0 Å. In the V32I variant, an additional water-mediated
hydrogen bond with the side chain of D30 is formed. Nevertheless,
overall the hydrogen bonds with DRV within the various complexes are
conserved.
Dynamic Simulations of Complexes
Analysis of crystal
structures above revealed that the mutations away from the active
site are able to influence interactions of DRV-contacting residues
at the active site. The alterations in vdW contacts or hydrogen bonds
lost, however, only partly correlate with the experimentally determined
enzyme inhibition constants. Another possible mechanism by which these
secondary mutations could alter inhibitor binding is by influencing
the dynamic ensemble of the enzyme.Starting from the crystal
structures of the DRV complexes, three replicates of fully hydrated
10 ns MD simulations of each DRV complex were performed and analyzed.
Root-mean-square deviations (RMSD) of Cα atoms during the simulation
and the average root-mean-square fluctuations (RMSF) about their mean
positions readily reveal that the secondary mutations alter the overall
enzyme dynamics (Figure 4A). The L90M and V32I/L33F
variants display larger fluctuations throughout the enzyme compared
to the other variants, although the catalytic D25 stays relatively
rigid in both monomers. These altered fluctuations are not restricted
to the sites of mutation, but propagate throughout the enzyme.
Figure 4
Molecular dynamics
simulations of DRV–HIV-1 protease complexes.
(A) RMSD of Cα atoms from the initial positions, and RMS fluctuations
of residues averaged over three 10 ns trajectories. (B) Significantly
altered change in distance between residue pairs around the active
site relative to WT complex, sampled during the MD simulations; increased
and decreased distances are indicated by blue and red, respectively.
See Figure S3 for the distance distributions.
Molecular dynamics
simulations of DRV–HIV-1 protease complexes.
(A) RMSD of Cα atoms from the initial positions, and RMS fluctuations
of residues averaged over three 10 ns trajectories. (B) Significantly
altered change in distance between residue pairs around the active
site relative to WT complex, sampled during the MD simulations; increased
and decreased distances are indicated by blue and red, respectively.
See Figure S3 for the distance distributions.To further analyze the impact
of mutations on the dynamic ensemble
sampled by the protease, the distance distributions were calculated
across the active site at a variety of positions (Figure 4B and Figure S3). In
all the variant complexes, the dynamic ensemble sampled by the protease
is altered relative to WT. Many of the distances displaying a significant
change are longer than the WT distance, indicating a widening of the
active site. In the L76V complex, the changes are highly asymmetric,
with one side of the active site constricting and the other widening
(Figure 4B). In all variant complexes, alterations
involve residues in the 80s loops. The 80s loops in both monomers
form the “side walls” of the active site. Relative to
the WT complex, the distance between residues 81 in the two monomers
are shorter, and that between 84–84′ are longer in all
variants. Hence, the “upper” part of the side walls
are closer and the “lower” part is farther away in the
mutant complexes compared to the WT. In addition to the 80s loop,
certain distances involving residue 50 at the tip of the flaps, and
even the catalytic D25 are altered in the variant complexes. The catalytic
site is the most invariant and dynamically restricted region of the
protease, both when different crystal structures are compared and
dynamics analyzed by simulations and NMR experiments.[18−20] Therefore, widening of the D25–D25′ distance in the
V32I/L33F double mutant is an unusually profound impact of remote
changes on the catalytic region.The MD simulations also permitted
a detailed analysis of the interaction
network both for direct interactions within the active site to DRV
and the internal hydrogen-bonding network throughout the enzyme (Figure 5, Figures S4–S6). Throughout the MD simulations the WT complex maintains a network
of stable hydrogen bonds. Starting from the bottom of the enzyme the
c-terminal α-helix forms a network of hydrogen bonds that links
the termini of the protein to the flap regions. The backbone of residue
95 links to residue 90 which in turn contacts residue 86, residue
88 bridges to residues 29, 31, and 74, and residue 76 bonds to both
residues 31 and 33 which is bonded to residue 78. Residues 29 and
30 make direct hydrogen bonds to DRV in both monomers. The hydrogen
bonds linking residues 47 and 54 within the flaps stay tightly hydrogen
bonded throughout the simulation. Thus, as we previously observed,[12] the hydrogen bonding network is stably retained
within the WT MD simulation.
Figure 5
Network of hydrogen bonds within HIV-1 protease.
(A) Crystal structure
of DRV bound to the active site, and only one monomer of the protease
is shown for clarity. The sites of mutation (L76, L90, V32, and L33)
have colored side chains. (B) Histograms of the changes of the percentage
time hydrogen bonds are formed relative to the WT simulation for each
of the complexes. (C) Schematic hydrogen bond network of the HIV-1
protease dimer with the percentage time hydrogen bonds are formed
during the WT simulation (Figure S4). (D)
Schematic representation of the V32I_L33F complex simulation with
the change in hydrogen bonding relative to the WT simulations. The
remaining variants schematic are shown in Figure
S5.
Network of hydrogen bonds within HIV-1 protease.
(A) Crystal structure
of DRV bound to the active site, and only one monomer of the protease
is shown for clarity. The sites of mutation (L76, L90, V32, and L33)
have colored side chains. (B) Histograms of the changes of the percentage
time hydrogen bonds are formed relative to the WT simulation for each
of the complexes. (C) Schematic hydrogen bond network of the HIV-1
protease dimer with the percentage time hydrogen bonds are formed
during the WT simulation (Figure S4). (D)
Schematic representation of the V32I_L33F complex simulation with
the change in hydrogen bonding relative to the WT simulations. The
remaining variants schematic are shown in Figure
S5.In comparing the simulations of
the variant DRV complexes with
the WT, subtle changes are seen in the vdW contacts within the active
site (Figure S6), similar to what was observed
in the crystal structures. However, in each of the four variants,
with the notable exception of the 47–54 linkages, the hydrogen
bond network is disrupted to a greater or lesser extent asymmetrically,
including the direct hydrogen bonds with DRV (Figure 5B, S4, S5). The V32I/L33F variant
is the most disrupted with 12 hydrogen bonds changing by greater than
20% relative to the WT complex throughout the dimer, with 11 being
weakened (Figure 5D) including most dramatically
the interactions of the side chain of Asn 88. Eight of these changes
are within the monomer that coordinates the highly rigid bis-THF moiety
including weakened interactions at points of contact between the protein
and DRV. Thus, mutations distal to the active site often weaken the
strength of the hydrogen bonds in the network, which is propagated
through to the active site including altering vdW packing, pushing
the flaps, and thereby the contact of I47 with DRV. Taken together,
one can decipher how contacts between protein and inhibitor are affected
by these changes even for residues that are packed through vdW contacts
or covalently linked along the backbone and are not directly involved
in the hydrogen bonding network (Figure 5A
and C).
Discussion
HIV-1 protease evolves
in complex combinations to evade inhibition,
but still maintains biological function. The active site mutations
have a relatively straightforward mechanism of disturbing the inhibition–function
balance, which is effectively explained by the substrate envelope.[6] However, in highly resistant variants, active
site mutations often coexist with mutations outside the active site.
This is particularly necessary when resistance is achieved to the
highly potent inhibitor DRV, which fits well within the substrate
envelope. However, the role of these changes outside the active site
has long been thought to be only in recovering viral fitness, or protease
stability.In the current study, we have primarily chosen enzyme
variants
that are associated with DRV resistance: L76V, V32I, and L33F.[21] Although L76V causes only a 1.5-fold decrease
in DRV binding affinity (Table 1), this mutation
is often observed in highly mutated DRV-resistant variants,[22,23] as well as variants with hyper-susceptibility to other PIs. L33F
is a highly networked mutation co-occurring with many others in highly
drug-resistant patient isolates, often together with V32I.[24] Therefore, comparison of V32I and the V32I/L33F
double mutant permits the context-dependence of mutational effects
in drug resistance. While not directly associated with DRV resistance,
L90M is a canonical highly networked mutation that typically arises
in multidrug resistant proteases. The large and rigid P1/P1′
moieties in NFV and SQV have been implicated in susceptibility to
L90M, a feature lacking in DRV.[10] L90M
has been found in more than half of patient isolates with at least
one PI resistance substitution, and hence is often present in patients
needing DRV-based salvage therapy.[24] Thus,
elucidating the physical impact of these secondary mutations on DRV
binding provides a detailed perspective on how the enzyme accommodates
such frequently observed changes.Specifically, we find that
mutations outside the active site impact
inhibitor binding thereby playing a direct role in conferring drug
resistance. Compared to the WT complex, the overall structure and
backbone conformations are very similar in the cocrystal structures
of the variant complexes. However, the mutations cause subtle but
significant rearrangements in the structure to cause altered interactions
with the bound inhibitor, as well as impacting the dynamic ensembles
of these complexes. We had previously hypothesized[12] and tested[25] that alterations
in the hydrophobic core of the enzyme could alter the conformational
dynamic ensemble through changes in the hydrophobic sliding of internal
residues potentially impacting drug resistance. This impact on dynamics
is not localized to the points of mutation but would propagate throughout
the enzyme. In the present study we hypothesize these mutations outside
the active site share a common pathway of altering the overall enzyme
dynamics and propagating their effects to the active site.Although
the resistance-associated mutations are located at a variety
of positions in the protease and away from the active site, they all
may utilize a common mechanism or pathway of altering the protease–inhibitor
interactions. The mutations cause subtle changes through the repacking
of the active site; in particular, these are observed in the crystal
structures at residues 47, 50, and 84 in both monomers, and also observed
in the MD analysis (Figure S6). Within
the crystal structures of both the L76V and L90M complexes residue
I47, which is located in the flap, loses contact with DRV. In contrast,
in the V32I complex I47 contacts are retained, while this loss is
restored when L33F occurs in V32I/L33F (these changes are also observed
in subtle differences in the MD simulation Figure
S6). Interestingly, V32I and I47V are the second most frequent
pair of residues often found to coevolve, thus compensating for each
other.[24] Mutations at I47, together with
I54, which its backbone is hydrogen bonded with, is a major DRV resistance
site. Among about 30 total active site residues that contact DRV,
I47 is consistently the residue whose contacts are affected the most
in L76V, L90M, and V32I/L33F variants (Figure
S3). These results suggest that the interactions of residue
47 with inhibitors within the active site may represent a pivotal
site in conferring drug resistance to PIs, and these interactions
can be altered by changes propagated through the enzyme from remote
sites.In addition to repacking around the inhibitor in the
crystal structures,
the secondary mutations share a common pattern of altering the dynamic
ensemble sampled by the protease, and the shape of the active site.
Overall in the dynamic ensemble of the V32I and the V32I/L33F variants
the active site is expanded, with the double mutant expanding the
active site more, while L76V active site contracts and the L90M active
site displays asymmetric changes. Hence, even though not located at
the active site, mutations at all these remote sites affect the shape
of the active site in the dynamic ensemble.How are single mutations
at a remote site able to alter interactions
and dynamics of the active site with highly common molecular mechanisms?
We propose a “network hypothesis” where the perturbation
introduced by mutation of a distal residue is propagated to the active
site through a network of interactions within the protease structure
(Figure 5). The distal mutation sites we studied
are all part of a hydrogen-bonded network connecting to the active
site where the inhibitor binds. Our network hypothesis postulates
that the mutations have similar effects and common mechanisms as they
all cause a rearrangement of this same network. This hypothesis is
supported by the alterations observed during the MD simulations in
the stability of the hydrogen bonding networks (Figure 5), where changes propagate from residues 74–78 and
87–90, through 28–33, to 84–85 and 25. This altered
interaction network includes repacking of the vdW contacts with residues
47 and 54, which are pivotal in linking the networked residues to
the rearrangement of the flaps, residues 29 and 30 that directly hydrogen
bond to DRV, and 82 and 84 that are key sites within the active site
cavity. We hypothesize that all these are the active site residues
where the impact of distal mutations is propagated as a common mechanism
of resistance in all variants and their subtle rearrangements can
cause inhibitor specific resistant changes.These common mechanisms
provide an explanation for why some mutations
are redundant and thus are not observed together in patient sequences,
while others are synergistic and occur together to confer higher levels
of drug resistance as they impact one another at pivotal sites that
confer resistance often through expanding the active site. This hypothesis
does not exclude the possibility that some changes may still provide
additional stability, increasing the combined fitness of the variants.
Most significantly, our findings show that all of the mutations we
have studied, although outside the active site, still directly alter
the shape and flexibility of the active site, thus likely play a direct
role in conferring resistance.
Methods
Protease Gene
Construction
Each of the four protease
mutants was constructed using a standard site-directed mutagenesis
protocol on a WT-HXB2 protease gene with a codon sequence optimized
for E. coli expression. The WT PR gene contained
the amino acid substitution Q7K to minimize the enzyme’s autoproteolytic
activity.
Protease Expression and Purification
Each PR mutant
was expressed and purified as previously described.[26] Briefly, the mutant HIV-1 protease gene was cloned into
the pXC-35 plasmid, which was then transformed into the TAP56 strain
of Escherichia coli. Transformed cells were grown
in 6 × 1 L cultures from which cell pellets were harvested 3
h after induction. The cell pellets were lysed and the protease was
retrieved from inclusion bodies with 100% glacial acetic acid. The
protease was separated from higher molecular weight proteins by size-exclusion
chromatography on a Sephadex G-75 column. The purified protein was
refolded by rapid dilution into a 10-fold volume of 0.05 M sodium
acetate buffer at pH 5.5, containing 10% glycerol, 5% ethylene glycol,
and 5 mM dithiothreitol (refolding buffer). The protease solution
was concentrated, followed by dialysis to remove any remaining acetic
acid. Protease used for crystallization was further purified with
a Pharmacia Superdex 75 fast-performance liquid chromatography column
equilibrated with refolding buffer.
Protease Crystallization
Crystals were set up with
a 5-fold molar excess of inhibitor to protease, which ensures ubiquitous
binding. The final protein concentration ranged from 0.8 to 1.6 mg/mL
in refolding buffer. The hanging-drop method was used for crystallization
as previously described.[26] For the L76V,
L90M, and V32I mutants, the reservoir solution consisted of 126 mM
phosphate buffer at pH 6.2, 63 mM sodium citrate, and ammonium sulfate
at a range of 24–29%. For the V32I/L33F double mutant, the
reservoir solution consisted of 0.1 M citrate-phosphate buffer, 7%
DMSO, and 25–30% ammonium sulfate.
Enzyme Kinetics
Enzyme inhibition studies were carried
out using a PerkinElmer Envision multilabel plate reader. A substrate
peptide mimicking the MA-CA (p17-p24) cleavage site labeled with K-E(EDANS)-S-Q-N-Y-P-I-V-Q-K(DABCYL)-R
(0.5 μM, final concentration) was added just prior to the reading
to each well containing 50 nM of PR and varying concentrations of
inhibitor. The FRET pair (EDANS, the donor and DABCYL, the quencher)
was attached to the indicated amino acids of the peptide (Molecular
Probes). Fluorescence intensity increase upon hydrolysis of the fluorogenic
substrate was monitored at 490 nm (emission of EDANS) from the highest
inhibitor concentration to the lowest, as well as the no inhibitor
control well. Each inhibitor titration included at least 12 inhibitor
concentration points. Initial velocities were obtained from the progress
curves and plotted against inhibitor concentration to get inhibition
curves. Resulting curves were globally fitted to Morrison’s
equation to obtain the Ki value, as described
previously.[27]
Evaluation of Hydrogen
Bonding and van der Waals Interactions
The Maestro component
of the Schröedinger software suite
was used to analyze the hydrogen bonds between the inhibitor and the
protease residues and neighboring waters after optimization of the
complex structure. Briefly, a hydrogen bond was defined by a distance
between donor and acceptor of <3.5 Å and a donor-hydrogen
acceptor angle of >120°. The vdW contacts between the inhibitor
and protease were calculated using a simplified Lennard–Jones
potential, following previously published protocols.[28]
MD Simulations
The MD simulations
were performed using
the program Sander in the Amber 8 package, as previously described.[20] A set of three simulations was run for each
of the four mutants and the WT-PR yielding a total of 15 trajectories
for analysis. Each simulation was assigned initial velocities according
to the Maxwellian distribution and random seeds were assigned with
five different values for each PR. An in-house script was used to
determine the intra and intermonomeric Cα distances between
various residues using the trajectories. To calculate the hydrogen
bond duration between various residues within the network from the
simulations, the Visual Molecular Dynamics (VMD) version 1.9.1 was
used.[29,30] VMD was used to write out the trajectory
in a pdb format using the coordinates and trajectory files generated
by PTraj from the AMBER simulation software. VMD was also used to
generate the trajectory pdb files to determine the vdW contact energies
over the simulations. The in-house vdW script was then modified to
assess vdW contacts from the simulations. The script was run to determine
vdW contacts for each of the trajectories. Once the robustness of
the system was assessed, the three trajectories for each system were
concatenated into one file containing 1500 frames and the total vdW
contacts were analyzed.[31]
Authors: Thomas P Young; Neil T Parkin; Eric Stawiski; Tami Pilot-Matias; Roger Trinh; Dale J Kempf; Michael Norton Journal: Antimicrob Agents Chemother Date: 2010-08-30 Impact factor: 5.191
Authors: Thomas D Wu; Celia A Schiffer; Matthew J Gonzales; Jonathan Taylor; Rami Kantor; Sunwen Chou; Dennis Israelski; Andrew R Zolopa; W Jeffrey Fessel; Robert W Shafer Journal: J Virol Date: 2003-04 Impact factor: 5.103
Authors: Klára Grantz Sasková; Milan Kozísek; Martin Lepsík; Jirí Brynda; Pavlína Rezácová; Jana Václavíková; Ron M Kagan; Ladislav Machala; Jan Konvalinka Journal: Protein Sci Date: 2008-06-17 Impact factor: 6.725
Authors: Nancy M King; Moses Prabu-Jeyabalan; Ellen A Nalivaika; Piet Wigerinck; Marie-Pierre de Béthune; Celia A Schiffer Journal: J Virol Date: 2004-11 Impact factor: 5.103
Authors: Zhanglong Liu; Thomas M Casey; Mandy E Blackburn; Xi Huang; Linh Pham; Ian Mitchelle S de Vera; Jeffrey D Carter; Jamie L Kear-Scott; Angelo M Veloro; Luis Galiano; Gail E Fanucci Journal: Phys Chem Chem Phys Date: 2016-02-17 Impact factor: 3.676
Authors: Mina Henes; Gordon J Lockbaum; Klajdi Kosovrasti; Florian Leidner; Gily S Nachum; Ellen A Nalivaika; Sook-Kyung Lee; Ean Spielvogel; Shuntai Zhou; Ronald Swanstrom; Daniel N A Bolon; Nese Kurt Yilmaz; Celia A Schiffer Journal: ACS Chem Biol Date: 2019-08-13 Impact factor: 5.100
Authors: Troy W Whitfield; Debra A Ragland; Konstantin B Zeldovich; Celia A Schiffer Journal: J Chem Theory Comput Date: 2020-01-16 Impact factor: 6.006
Authors: Debra A Ragland; Troy W Whitfield; Sook-Kyung Lee; Ronald Swanstrom; Konstantin B Zeldovich; Nese Kurt-Yilmaz; Celia A Schiffer Journal: J Chem Theory Comput Date: 2017-10-09 Impact factor: 6.006
Authors: Zhanglong Liu; Xi Huang; Lingna Hu; Linh Pham; Katye M Poole; Yan Tang; Brian P Mahon; Wenxing Tang; Kunhua Li; Nathan E Goldfarb; Ben M Dunn; Robert McKenna; Gail E Fanucci Journal: J Biol Chem Date: 2016-08-30 Impact factor: 5.157