Acquired resistance to therapeutic agents is a significant barrier to the development of clinically effective treatments for diseases in which evolution occurs on clinical time scales, frequently arising from target mutations. We previously reported a general strategy to design effective inhibitors for rapidly mutating enzyme targets, which we demonstrated for HIV-1 protease inhibition [Altman et al. J. Am. Chem. Soc. 2008, 130, 6099-6113]. Specifically, we developed a computational inverse design procedure with the added constraint that designed inhibitors bind entirely inside the substrate envelope, a consensus volume occupied by natural substrates. The rationale for the substrate-envelope constraint is that it prevents designed inhibitors from making interactions beyond those required by substrates and thus limits the availability of mutations tolerated by substrates but not by designed inhibitors. The strategy resulted in subnanomolar inhibitors that bind robustly across a clinically derived panel of drug-resistant variants. To further test the substrate-envelope hypothesis, here we have designed, synthesized, and assayed derivatives of our original compounds that are larger and extend outside the substrate envelope. Our designs resulted in pairs of compounds that are very similar to one another, but one respects and one violates the substrate envelope. The envelope-respecting inhibitor demonstrates robust binding across a panel of drug-resistant protease variants, whereas the envelope-violating one binds tightly to wild type but loses affinity to at least one variant. This study provides strong support for the substrate-envelope hypothesis as a design strategy for inhibitors that reduce susceptibility to resistance mutations.
Acquired resistance to therapeutic agents is a significant barrier to the development of clinically effective treatments for diseases in which evolution occurs on clinical time scales, frequently arising from target mutations. We previously reported a general strategy to design effective inhibitors for rapidly mutating enzyme targets, which we demonstrated for HIV-1 protease inhibition [Altman et al. J. Am. Chem. Soc. 2008, 130, 6099-6113]. Specifically, we developed a computational inverse design procedure with the added constraint that designed inhibitors bind entirely inside the substrate envelope, a consensus volume occupied by natural substrates. The rationale for the substrate-envelope constraint is that it prevents designed inhibitors from making interactions beyond those required by substrates and thus limits the availability of mutations tolerated by substrates but not by designed inhibitors. The strategy resulted in subnanomolar inhibitors that bind robustly across a clinically derived panel of drug-resistant variants. To further test the substrate-envelope hypothesis, here we have designed, synthesized, and assayed derivatives of our original compounds that are larger and extend outside the substrate envelope. Our designs resulted in pairs of compounds that are very similar to one another, but one respects and one violates the substrate envelope. The envelope-respecting inhibitor demonstrates robust binding across a panel of drug-resistant protease variants, whereas the envelope-violating one binds tightly to wild type but loses affinity to at least one variant. This study provides strong support for the substrate-envelope hypothesis as a design strategy for inhibitors that reduce susceptibility to resistance mutations.
Many chemical
and biological agents have been developed to deliver quality-of-life
improvements, especially in health care and agriculture. Advances
include herbicides and pesticides, as well as medical tests, treatments,
and interventions. However, therapeutic and environmental agents impose
selective pressure that can lead to acquired resistance. Although
resistance can be attained through many mechanisms,[1−6] for infectious diseases and cancer, in particular, mutation of the
direct target is often the source of resistance and is associated
with accelerated mutation rates. Such resistance limits the effectiveness
of therapies that are time-consuming and expensive to develop and
approve through regulatory processes. Thus, it is crucial to devise
general strategies to incorporate into standard drug discovery paradigms
that lead to elimination of resistance or at least to a large reduction
in its incidence. Often the targets are enzymes essential to disease
maintenance or progression. For such cases, the development of inhibitors
that are as similar as possible to the disease-related substrates
has been hypothesized as an effective strategy for reducing resistance.[7] The notion behind such substrate mimicry is that
enzyme mutations that reduce inhibitor binding would then, by similarity
arguments, be very likely to also reduce substrate binding and possibly
also turnover, and thus not be well tolerated. Inhibitors that are
similar to substrates thus restrict resistance by introducing significantly
higher genetic barriers that must be surmounted in their presence.HIV-1 protease has proven an extremely useful case for studying
the development and avoidance of resistance. HIV-1 protease was the
first therapeutic target for which structure-based drug design was
broadly applied.[8] Ten HIV-1 protease inhibitors
have been approved by the U.S. FDA since the 1990s. All but tipranavir[9] are peptidomimetics that are similar to transition-state
analogues of substrates, including saquinavir,[10] ritonavir,[11] indinavir,[12] nelfinavir,[13] amprenavir[14]/fosamprenavir,[15] lopinavir,[16] atazanavir,[17] and
darunavir.[18] These drugs allow longer life
expectancy for AIDSpatients but still fall short of a cure. Therapeutic
failure is due to rapid evolution of viral strains and accumulation
of resistance-endowing mutations under selective drug pressure. In
an effort to understand how drug-resistant HIV-1 protease maintains
the ability to recognize and cleave its substrates, the Schiffer group
compared the crystal structures of an inactive variant of HIV-1 protease
with six peptides that correspond to the natural substrate cleavage
sites.[19] It was discovered that the protease
recognizes the substrates of diverse sequences through an asymmetric
shape commonly adopted by the substrates, whose surface has been referred
to as “the substrate envelope”. The same group further
showed that many inhibitors protrude beyond the substrate envelope
and make contacts with enzyme residues not contacted by substrates
and that are the sites of primary resistance mutations.[7] It was thus hypothesized that “an inhibitor
contained within the substrate envelope, interacting only with the
same residues that are necessary to recognize substrate, may be less
susceptible to drug resistance.”[7] This so-called “substrate-envelope hypothesis” was
assessed in a computational framework for inhibitors of HIV-1 protease[20,21] as well as Abl kinase, chitinase, thymidylate synthase, DHFR, and
neuraminidase.[22] It was shown that the
volume of an inhibitor molecule that protrudes outside the substrate
envelope correlates with average mutation sensitivity. Recent crystallography
data and analyses suggested that the substrate-envelope hypothesis
also applies to the inhibitors of the NS3/4A protease, a target for
hepatitis C virus (HCV) infection.[23,24]Implementing
a general strategy to design robustly effective inhibitors for mutatable
enzyme targets, we previously performed computational inverse design
of HIV-1 protease inhibitors that reside inside the substrate envelope.[25] Promising candidates were synthesized, assayed,
and characterized, which led to the identification of subnanomolar
inhibitors to drug-resistant variants. Thirty-six compounds (comprising
the MIT-2 library) were potent inhibitors
of wild-type HIV-1 protease, with Ki values
ranging from 14 pM to 4 nM. Ten of the most potent inhibitors were
further assayed in antiviral activity against a panel of four drug-resistant
HIV-1 protease variants derived from clinically isolated, drug-resistant
strains. Two compounds remained potent against the panel with less
than 15-fold affinity loss, and four had moderate shifts of less than
80-fold loss.[25]In this study, we
further investigate the implications of the substrate-envelope hypothesis
in designing robust inhibitors that are of low susceptibility to drug-resistance
mutations. The scaffold forming the basis of the MIT-2 library was
adopted from amprenavir and darunavir, the latter of which has an
especially flat resistance profile. Thus, we sought to investigate
whether the relatively high incidence of these compounds with flat
binding profiles in the MIT-2 library was due to their being designed
to bind within the substrate envelope or was instead a result of their
being based on an advantageous scaffold. Here, we computationally
designed two series of compounds that progressively protrude outward
toward and through the substrate envelope but are otherwise identical,
in order to isolate the effect of the substrate-envelope constraint
and study its impact on binding specificity profiles; all compounds
in the current study share the amprenavir/darunavir scaffold. Eight
compounds were designed based on two MIT-2 parent compounds, with
protrusions beyond various subpockets of the binding site (including
two levels of protrusions at the P1′ site). Two compounds that
were predicted and shown experimentally to violate significantly the
substrate envelope were shown to bind tightly to wild type but poorly
to members of the mutant panel; in contrast, the parent compounds
respect the substrate envelope and are flat binders against the panel,
with less than 50-fold affinity loss. Four newly designed compounds
that essentially respect the substrate envelope were also flat binders.
Taken together these results indicate that the six broadly binding
compounds along with earlier designs[25] benefit
from residing fully within the substrate envelope and thus decreasing
the chance of losing interactions with a drug-resistant variant, rather
than benefitting from an advantaged scaffold. Moreover, the substrate-envelope
violators lost the most binding affinity to protease variants with
mutations nearby the site of the violation. Thus, these results greatly
strengthen the notion that the substrate-envelope hypothesis provides
a valuable framework for developing enzyme inhibitors that are robust
against both wild type and resistant variants.
Results and Discussion
Drug-resistant mutations in HIV-1 protease occur in various positions
and combinations. Principles for the design of therapeutics that avoid
resistance mutations for HIV-1 protease and other targets would be
valuable. The substrate-envelope hypothesis is a general principle
for avoiding resistant variants for enzyme targets. Here we further
tested the substrate-envelope hypothesis by designing paired inhibitors
of HIV-1 protease that differ only in whether they respect the substrate
envelope, chemically synthesizing them, and performing inhibitory
and antiviral activity assessments.
Computational Design of
Inhibitors
Computational molecular design was applied to
target the HIV-1 protease active site using a design library consisting
of a scaffold with three variable positions. The goal was to probe
changes in binding specificity as increasing functional group size
approached and eventually pierced the substrate envelope. Two parent
compounds reported previously were selected for this study, MIT-2-AD-93
and MIT-2-KB-83, chosen for their high affinities and relatively flat
binding profiles.[25] Designs were carried
out in the wild-type active site, using larger substituents that are
allowed to pierce the substrate envelope. From the sets of predicted
high-affinity designs, we selected eight molecules for synthesis and
testing that had functional groups larger than those in the corresponding
parent compound and thus probed the substrate envelope with the potential
to extend beyond it (Table 1).
Table 1
Parent Compounds (AD-93 and KB-83) and Designed New Compounds
The selected compounds
involve the same single substitutions to both parent compounds, with
an N-acetyl-isoleucine substitution at R1, a smaller
cyclohexylmethyl and a larger 3-phenylpropyl hydrophobic substitution
at R2, and 5-(isoxazol-5-yl)-2-thiophene at R3. The numbers of non-hydrogen
atoms in the substitutions (original function group) were 9 (7), 7
(4 or 5), 9 (4 or 5), and 10 (8 or 9), respectively, which corresponds
to a net increase of 1–5 non-hydrogen atoms in each substitution.
Inhibitor Synthesis and Activity
The compounds were synthesized
(see Methods for synthetic methods and compound
characterization). They were assayed for inhibitory activity against
wild type and a panel of drug-resistant protease variants using modified
high-throughput enzyme inhibition assays compared to the original
characterization of the parent compounds.[25,26] The mutant panel included two multi-drug-resistant variants M1 (L10I, G48V, I54V, V82A) and M3 (L10I,
A71V, G73S, I84V, L90M), a signature variant
of nelfinavir resistance M2 (D30N, N88D),
and a signature variant of amprenavir and darunavir resistance M4
(I50V, A71V). (In each case the boldface mutations are
the primary drug-resistant ones.) The inhibition data for the parent
and variant compounds against the panel are given in Table 2. Because all inhibitors appear to act competitively,
we interpret the measured inhibition constants (Ki) as inhibitor affinities (disassociation constants Kd).
Table 2
Measured Binding
Affinity Values against Wild-Type and Mutant Panel
wild typea
M1 (L10I, G48V, I54V, V82A)a
M2 (D30N, N88D)a
M3 (L10I, A71V, G73S, I84V, L90M)a
M4 (I50V, A71V)a
worst-fold
affinity lossb
AD-93
0.046 ± 0.023
0.724 ± 0.377
0.905 ± 0.124
1.713 ± 1.042
1.920 ± 0.834
41
AG-23
0.021 ± 0.009
0.376 ± 0.168
0.028 ± 0.025
0.048 ± 0.022
0.092 ± 0.025
18
AF-72
0.129 ± 0.028
1.328 ± 0.851
0.383 ± 0.097
2.753 ± 0.609
4.823 ± 3.116
37
AF-69
0.070 ± 0.005
19.18 ± 3.84
2.004 ± 0.298
9.965 ± 0.530
2.265 ± 0.643
274
AF-71
3.329 ± 0.663
18.20 ± 8.12
2.951 ± 0.128
44.82 ± 22.42
30.04 ± 3.79
13
KB-83
0.194 ± 0.007
1.560 ± 0.124
0.283 ± 0.097
2.021 ± 0.033
1.101 ± 0.241
10
AF-68
0.146 ± 0.071
0.819 ± 0.255
0.049 ± 0.034
1.029 ± 0.134
0.144 ± 0.115
7
AF-77
0.546 ± 0.028
2.045 ± 0.502
0.490 ± 0.100
2.469 ± 0.860
3.404 ± 0.593
6
AF-78
0.437 ± 0.132
42.93 ± 0.559
2.543 ± 0.462
23.80 ± 4.17
5.887 ± 2.755
98
AF-80
2.493 ± 0.251
28.13 ± 1.37
1.261 ± 0.176
10.53 ± 0.16
13.53 ± 4.10
11
The measured Ki of each inhibitor to each enzyme is given
as the mean ± standard deviation, in units of nM. Measurements
are reported for wild-type HIV-1 protease as well as for four drug-resistant
variants (M1, M2, M3, and M4) for which the specific mutations are
given in parentheses, with the key resistance mutations in bold face
(relative to the PDB ID 1T3R wild type).
The worst-fold loss is given as the weakest Ki to one of the drug-resistant variants (bold face) divided
by the Ki to wild type for each inhibitor.
The measured Ki of each inhibitor to each enzyme is given
as the mean ± standard deviation, in units of nM. Measurements
are reported for wild-type HIV-1 protease as well as for four drug-resistant
variants (M1, M2, M3, and M4) for which the specific mutations are
given in parentheses, with the key resistance mutations in bold face
(relative to the PDB ID 1T3R wild type).The worst-fold loss is given as the weakest Ki to one of the drug-resistant variants (bold face) divided
by the Ki to wild type for each inhibitor.Pareto plot of affinity and specificity.
Plot shows two metrics for each of 10 inhibitors studied, weakest
binding affinity and worst fold loss, against the wild-type and mutant
panel.The parent compounds are potent,
subnanomolar binders to wild-type protease and show flat resistance
profiles across the panel of resistant variants. The binding profile
is characterized using two metrics, the worst-fold affinity loss and
the weakest binding affinity. The worst-fold affinity loss is the
ratio between the weakest binding affinity (Ki) of a compound for a protease variant and its affinity for
wild-type protease. Specifically, AD-93 (KB-83) had a wild-type affinity
of 0.046 nM (0.19 nM) and 41-fold (10-fold) loss against the mutant
panel, where the weakest binding affinity was 1.92 nM (2.02 nM) measured
with the M4 (M3) variant. Several observations were made for the new
compounds. (1) Relative to the parent compounds, six of the eight
new compounds had comparable or improved binding affinity with wild-type
protease. The two exceptions, AF-71 and AF-80, both involved the same
substitution at R3, remained nanomolar binders to wild-type protease,
but suffered 72-fold and 13-fold loss, respectively, in affinity compared
to their respective parent compounds. (2) The binding specificity
profiles of the new compounds fall into two classes: six that remained
potent or had a moderate shift against the mutant panel (<50-fold
affinity loss) and two that were more susceptible to resistance mutations
(>80-fold affinity loss). The latter two, AF-69 and AF-78, both
involve the large 3-phenylpropyl hydrophobic substitution at R2 and
in the crystal structures showed a large expected violation of the
substrate envelope (see Table 3). Both suffered
their largest affinity loss when binding variant M1. Interestingly,
AF-71 and AF-80, the two relatively weak binders to wild-type protease,
had rather flat binding specificity profiles with worst-fold affinity
losses of 13 and 11, respectively. This is consistent with a common
perception that it is less difficult to identify broadly binding compounds
with low affinity than it is to find broadly binding ones with high
affinity.[27] (3) Of the 10 compounds, six
maintained subnanomolar to nanomolar affinity in their weakest complexes.
They include parent compounds and new compounds involving the N-acetyl-isoleucine substitution at R1 or the smaller cyclohexylmethyl
substitution at R2. In both the AD-93 and the KB-83 series, the larger
3-phenylpropyl hydrophobic substitutions at R2 and the 5-(isoxazol-5-yl)-2-thiophene
substitutions at R3 resulted in weakest binding affinities, with Ki’s greater than 20 nM.
Table 3
Measured Substrate Envelope Violations (in Å3) and
Their Decompositions
compound
total
R1 (near P2)
R2 (near P1′)
R3 (near P2′)
AD-93
7.8
0.5
0.0
5.1
AG-23
11.0
2.1
0.8
4.8
AF-72
13.6
0.3
6.2
5.5
AF-69-A/Ba
14.5/20.0
1.1/0.1
6.0/13.4
5.8/5.7
AF-71
19.9
0.3
0.0
17.4
KB-83-A/Ba
7.4/10.1
0.4/3.0
0.0
5.2
AF-68
10.9
2.3
0.0
6.3
AF-77
15.2
0.2
6.7
5.9
AF-78-A/Ba
29.0/29.5
0.1/0.6
21.5
5.7
AF-80
20.3
0.5
0.0
18.2
“A/B”
indicates that there exist two conformations (A and B) that often
have equal occupancies. The atomic volumes of substrate-envelope violations
for these compounds were provided as in the two conformations separated
by “/”(where applicable).
“A/B”
indicates that there exist two conformations (A and B) that often
have equal occupancies. The atomic volumes of substrate-envelope violations
for these compounds were provided as in the two conformations separated
by “/”(where applicable).In designing potent inhibitors that are of low susceptibility
to resistance mutations, it is not clear which metric, weakest binding
affinity or worst-fold affinity loss, is more important. Therefore,
we show in Figure 1 a two-dimensional plot
of both metrics for all 10 compounds against the wild-type and mutant
panel. The lower-left corner of the plot indicates where ideal low-susceptibility
inhibitors would lie. Inhibitors located here have both tight and
flat binding specificity profiles. AG-23, AF-68, and AF-77 are the
best compounds judged by this type of Pareto optimality; that is,
no other compound achieves lower values in both weakest binding affinity
and worst-fold affinity loss. One would shift priority from AG-23
to AF-68 and then to AF-77 as increasing priority was put on worst-fold
affinity loss relative to worst binding affinity.
Figure 1
Pareto plot of affinity and specificity.
Plot shows two metrics for each of 10 inhibitors studied, weakest
binding affinity and worst fold loss, against the wild-type and mutant
panel.
Crystal Structures of Bound Complexes
To understand further the resistance patterns described above, crystal
structures were solved for the complexes of wild-type HIV-1 protease
and all eight new compounds. The AD-93 and KB-83 complexes were reported
previously[25] (PDB accession codes 2QI4 and 3SA8, respectively).
These crystal structures are shown in Figure 2 (AD-93 series) and Figure 3 (KB-83 series).
Violations of the substrate envelope were computed from the crystal
structures (total and decomposition by functional groups are given
in Table 3; crystallographic details are in Methods and Supplementary Table
1). For the 10 compounds, observed envelope violation volumes
correlated well with corresponding substituent sizes in the designed
structures. Parent compounds AD-93 and KB-83, both flat binders, had
negligible violation of the substrate envelope. New compounds with
small violations all displayed flat specificity profiles. In particular,
AG-23, AF-72, AF-68, and AF-77 did not violate the substrate envelope
by more than 15.2 Å3, which is smaller than the volume
of a carbon atom (20.6 Å3 in the model used here),
and the maximum worst-fold affinity loss across the set is 37. These
substrate-envelope violation volumes are calculated to be a little
higher than those for amprenavir (3.73 Å3) or darunavir
(4.10 Å3) that have low susceptibility to drug-resistant
variations but are much lower than those for drugs with high susceptibility,
such as saquinavir (80.40 or 64.73 Å3; PDB accession
code 3OXC(28) [A or B]). In contrast, compounds with substantial
substrate-envelope violations had poor specificity profiles. In particular,
AF-69 (in conformation B with 50% occupancy) and AF-78 (in both conformations
A and B with equal occupancies) had violations of about 20 and 29
Å3, respectively, which are comparable to 1–1.5
carbon atoms, and their worst-fold affinity loss was 274 and 98, respectively.
There seems to be a relationship between the location at which an
inhibitor protrudes outside the substate envelope and the mutant sustaining
the greatest loss in affinity. Namely, binding is most sensitive to
mutations near that envelope violation, which might be most likely
to disrupt interactions with the protruding group. For example, the
greatest structural violations of both AF-69 and AF-78 were due to
the R2 group, where the same bulky hydrophobic substitution (3-phenylpropyl) was introduced, and their weakest
binding affinities were measured with M1, which includes the P1′
site mutations (G48V and V82A) near where R2 packs in the bound complex.
Taken together, the data presented here show that zero or small violations
of the substrate envelope can lead to compounds with relatively flat
binding profiles and that larger violations can produce inhibitors
that are susceptible to resistant variants. This is by no means a
highly quantitative relationship; for example, compounds with larger
envelope violations can have smaller worst-fold affinity losses (AF-78
vs AF-69), particularly against a relatively small panel of mutants.
Figure 2
Crystal
structures of AD-93 series. Proteases are shown in gray cartoon with
sticks representing side chains that are mutated in the mutant panel.
One-letter amino acid code and residue index are used to label these
residues, color-coded by various drug-resistant variants (blue for
M1, green for M2, orange for M3, and purple for M4). These structures
are aligned and viewed from the top (flap region), and this view was
applied to all panels in Figures 2 and 3. All compounds are represented as van der Waals
spheres. Carbon atoms are gray for proteases and cyan for inhibitors.
The remaining atoms follow the same color-coding rule: red for oxygen,
blue for nitrogen, and yellow for sulfur (hydrogen atoms are not shown).
A gray, half-transparent surface around each compound represents the
substrate envelope. Thus parts of spheres that are not veiled by the
gray surface correspond to atomic volumes that pierce the substrate
envelope. (A) AD-93, (B) AG-23, (C) AF-72, (D) AF-69, conformation
A, (E) AF-69, conformation B, (F) AF-71.
Figure 3
Crystal structures of KB-83 series. See the caption of Figure 2 for details. (A) KB-83, conformation A (conformation
B of compound KB-83 only differs slightly in R1 compared to conformation
A and is thus not shown here), (B) AF-68, (C) AF-77, (D) AF-78, conformation
A, (E) AF-78, conformation B, (F) AF-80.
Crystal
structures of AD-93 series. Proteases are shown in gray cartoon with
sticks representing side chains that are mutated in the mutant panel.
One-letter amino acid code and residue index are used to label these
residues, color-coded by various drug-resistant variants (blue for
M1, green for M2, orange for M3, and purple for M4). These structures
are aligned and viewed from the top (flap region), and this view was
applied to all panels in Figures 2 and 3. All compounds are represented as van der Waals
spheres. Carbon atoms are gray for proteases and cyan for inhibitors.
The remaining atoms follow the same color-coding rule: red for oxygen,
blue for nitrogen, and yellow for sulfur (hydrogen atoms are not shown).
A gray, half-transparent surface around each compound represents the
substrate envelope. Thus parts of spheres that are not veiled by the
gray surface correspond to atomic volumes that pierce the substrate
envelope. (A) AD-93, (B) AG-23, (C) AF-72, (D) AF-69, conformation
A, (E) AF-69, conformation B, (F) AF-71.Crystal structures of KB-83 series. See the caption of Figure 2 for details. (A) KB-83, conformation A (conformation
B of compound KB-83 only differs slightly in R1 compared to conformation
A and is thus not shown here), (B) AF-68, (C) AF-77, (D) AF-78, conformation
A, (E) AF-78, conformation B, (F) AF-80.Note that two compounds violate the envelope but bind robustly
across the mutant panel. AF-71 and AF-80, involving the same R3 substitution
with a double-ring aromatic system, had violation amounts of about
20 Å3 but worst-fold affinity losses of only about
10. In the P2′ site surrounding the R3 group, only one residue
(Asp 30) is involved in the mutations included in the mutant panel
(D30N in M2). However, AF-71 and AF-80 have improved affinity with
M2 compared to that of wild type. This is consistent with the notion
that the panel does not have mutations nearby that can challenge these
violations, but that these inhibitors could bind poorly to other functional
HIV-1 protease variants with more disruptive mutations in the vicinity.
Interestingly, the solved X-ray crystal structure had a second conformation
for AF-69 (conformation A), which had a smaller R2 violation. If these
are both equally accessible, one might imagine that binding to mutants
could occur in at least conformation A, and so the loss in affinity
would be minor (kbTln2). That this is not the case could
be due to unequal occupancy of these two conformations.
Antiviral Activity
Profiles of Inhibitors
Cell-based antiviral assays were carried
out by Monogram Biosciences (South San Francisco, CA) using a panel
of various strains of wild-type and variant proteases (Table 4). Four designed compounds that all respected the
substrate envelope were tested (the Pareto optimal AG-23 and AF-68
and the somewhat bulkier AF-72 and AF-77) together with two FDA-approved
drugs (amprenavir and darunavir, whose inhibition and antiviral activities
were previously characterized[25,26]). All four designed
compounds had flat antiviral activity profiles across the viral panel
with worst-fold activity losses of between 2.2 and 4.4, which were
comparable to those of amprenavir (5.5) and darunavir (2.4). In terms
of absolute antiviral activity against wild-type virus, the EC50’s of AG-23 (2.7 nM) and AF-72 (3.5 nM) were similar
to that of amprenavir (5.5 nM) but an order of magnitude weaker than
that of darunavir (0.25 nM). The EC50’s of AF-68
(63.7 nM) and AF-77 (47.4 nM) were another order of magnitude higher.
Taken together, these results further strengthen the substrate-envelope
hypothesis, by showing that the flat binding profiles of envelope-respecting
compounds extends to flat activity profiles.
Table 4
Antiviral
Activity (EC50 Values in nM) against Selected Wild-Type
and Drug-Resistant HIV Clones
wild-type (CNDO control strain)a
wild-type
clade A (I13V, E35D, M36I, R41K, H69K, L89M)a
wild-type
clade B (N37H, R41K, V77I, I93L)a
wild-type clade C (I15V,
M36I, R41K, H69K, L89M, I93L)a
Wild-type control strain CNDO and patient-derived strains
of wild-type HIV-1 from clades A, B, and C .
MDRC4, multi-drug-resistant control strain R268.
(Genbank accession numbers for all strains are given in the Supporting Information; mutant residues listed
here are relative to the CNDO wild-type control strain.).
The worst-fold loss is given as the
weakest EC50 value to one of the variants (bold face) divided
by that to wild-type for each inhibitor.
Wild-type control strain CNDO and patient-derived strains
of wild-type HIV-1 from clades A, B, and C .MDRC4, multi-drug-resistant control strain R268.
(Genbank accession numbers for all strains are given in the Supporting Information; mutant residues listed
here are relative to the CNDO wild-type control strain.).The worst-fold loss is given as the
weakest EC50 value to one of the variants (bold face) divided
by that to wild-type for each inhibitor.
Conclusion
In this study, we provide a detailed test
of the substrate-envelope hypothesis as a means of designing robust
inhibitors against drug-resistant variants. While the use of substrate
and transition-state analogues as a starting point for inhibitor design
is common, the rationale there is one of achieving affinity: because
substrates and transition-states bind to the target, their analogues
could bind as well. The substrate-envelope hypothesis relies on more
detailed substrate mimicry so the inhibitor does not inadvertently
rely on binding interactions nonessential to substrates and thus susceptible
to resistance mutations. In other words, the goal of substrate-envelope
mimicry is to borrow specificity rather than just affinity from substrates.To this end, two series of related HIV-1 protease inhibitors were
computationally designed. Compounds within each series probed single
functional group changes that expanded toward and eventually breached
the substrate envelope. Affinity, specificity, and antiviral activity
assays were performed on the synthesized compounds using drug-resistant
panels of protease and virus, and complexes with the wild-type protease
were structurally characterized with X-ray crystallography.Although all compounds share the amprenavir/darunavir scaffold, which
is associated with relatively flat binding profiles, we found pairs
of compounds that differed by only a single functional group that
bound to the wild-type enzyme in a similar manner with similar affinity
but differed greatly in their ability to inhibit drug-resistant proteases
variants (AD-93 vs AF-69 and KB-83 vs AF-78). The single distinguishing
feature separating flat from nonflat binders in these pairs was that
flat binders respected (AD-93 and KB-83) and nonflat binders violated
(AF-69 and AF-78) the substrate envelope. This suggests that the envelope
is more important than the shared scaffold in the development of inhibitors
of low susceptibility to drug-resistant mutations.Interestingly,
mutations in the protease occur near different locations on the envelope.
There is excellent correspondence between losses in affinity and the
location of envelope-violating inhibitor excursions. AF-69 and AF-78
both have R2 extensions that violate the envelope at P1/P1′,
and both inhibitors lose their greatest affinity to the M1 variant
with characteristic mutations G48V and V82A, which are close to the
envelope at P1/P1′, consistent with the notion that the inhibitors
violate the envelope to make non-substrate-like P1/P1′ interactions
that are disturbed in the M1 variant. In contrast, two of the designed
compounds, AF-71 and AF-80, violate the envelope substantially but
exhibit flat binding profiles against the mutant panel. As they involve
the same R3 substitution and the panel lacks mutations in the P2/P2′
site nearby, we predict that they would become susceptible to other
drug-resistant variants that are not present in the panel studied.
In other words, these two cases should not be regarded as counterexamples
of the substrate-envelope hypothesis but rather examples showcasing
potential predictive powers of the hypothesis.Although the
substrate-envelope hypothesis, in a narrow sense, applies only to
enzyme targets, one can generalize the envelope hypothesis for non-enzyme
targets through extending the definition of the envelope to include
other necessary functions of a target besides binding substrates.
Consequentially, designed compounds that hide inside some “envelope
of function” could be immune to target mutations that maintain
native function.
Methods
Computational
Design
In our previous study,[25] 36 MIT-2 compounds were computationally designed, and the binding
specificity profiles for 10 of them against the wild-type and mutant
panel were experimentally measured. Two compounds that exhibited flat
binding profiles, namely, MIT-2-AD-93 and MIT-2-KB-83, were chosen
as parent compounds. A 1.2-Å crystal structure of darunavir-bound
wild-type HIV-1 protease (PDB accession code 1T3R) was used as the
fixed target into which inhibitor compounds were computationally designed.
All inhibitors share the (R)-(hydroxyethylamino)sulfonamide
scaffold derived from the clinically approved inhibitors amprenavir[14] and darunavir[18] but
possess various functional groups (that attach to the scaffold at
different positions) derived from the ZINC database[30] and commercial catalogs. The same design framework and
parallel synthetic components were used for the previously reported
MIT-2 library.[25] The special design strategy
here was to compare the lists of top candidates designed with the
substrate-envelope constraint and the maximal-envelope constraint,
identify functional group choices at each position that violate the
substrate-envelope constraint and are otherwise energetically favored
against the background of other positions, and generate the list of
derivative compounds that are one functional group away from each
parent compound covering various positions and molecular properties.
Synthesis
The designed protease inhibitors were synthesized
using a stepwise synthetic approach. The Boc-protected intermediates
(R)-(hydroxyethylamino)sulfonamides 5–12 (Scheme 1) were prepared
from the commercially available chiral epoxide 1, (1S,2S)-(1-oxiranyl-2-phenylethyl)carbamic
acid tert-butyl ester, using methods described previously.[25,31] Briefly, regioselective ring-opening of epoxide 1 with
selected primary amines 2a–d provided
the β-amino alcohols 3a–d,
respectively. Selective reactions of secondary amino group in 3a–d with 4-methoxybenzene sulfonyl chloride
using aqueous sodium carbonate (Na2CO3) and
with bezothiazole-6-sulfonyl chloride and 5-(isoxazol-5-yl)thiophene-2-sulfonyl
chloride using diisopropylethylamine in anhydrous CH2Cl2 provided the (R)-(hydroxyethylamino)sulfonamide
intermediates 5–12. Removal of the
Boc protection using trifluoroacetic acid in CH2Cl2 followed by the reactions of the resulting freeamines with
carboxylic acids 13a,b using either EDCI/HOBt/DIEA
in a DMF–CH2Cl2 (1:1) mixture (Method
A) or EDCI/HOBt in a H2O–CH2Cl2 (1:1) mixture (Method B)[25] provided the
designed inhibitors 14–21.
Scheme 1
Synthesis
of Paired Compound Library
Reagents and conditions:
(a) EtOH or iPrOH, 80 °C, 3 h; (b) aq Na2CO3, CH2Cl2, 0 °C to
rt, overnight; (c) Et3N, CH2Cl2,
0 °C to rt, overnight; (d) TFA, CH2Cl2,
rt, 1 h; (e) EDCI, HOBt, DIEA, DMF–CH2Cl2 (1:1), 0 °C to rt, overnight; (f) EDCI, HOBt, H2O–CH2Cl2 (1:1), 0 °C, 24 h.
Synthesis
of Paired Compound Library
Reagents and conditions:
(a) EtOH or iPrOH, 80 °C, 3 h; (b) aq Na2CO3, CH2Cl2, 0 °C to
rt, overnight; (c) Et3N, CH2Cl2,
0 °C to rt, overnight; (d) TFA, CH2Cl2,
rt, 1 h; (e) EDCI, HOBt, DIEA, DMF–CH2Cl2 (1:1), 0 °C to rt, overnight; (f) EDCI, HOBt, H2O–CH2Cl2 (1:1), 0 °C, 24 h.
Assays for Inhibition and Antiviral Activities
HIV protease inhibitor activities were determined by the fluorescence
resonance energy transfer (FRET) method.[32,33] Protease substrate, Arg-Glu(EDANS)-Ser-Gln-Asn-Tyr-Pro-Ile-Val-Gln-Lys(DABCYL)-Arg,
was labeled with the energy transfer donor (EDANS) and acceptor (DABCYL)
dyes at its two ends to perform FRET. Fluorescence measurements were
carried out on an EnVision plate reader (PerkinElmer). Drug susceptibility
assays were carried out by Monogram Biosciences against wild-type
HIV-1 control, three patient-derived strains of wild-type HIV-1 from
clades A, B, and C, and two multi-drug-resistant HIV-1 variants including
MDRC4 as control strain and MDR1 strain with protease mutations M46I,
I54V, V82A, and L90M.
Crystallography
The expression,
isolation, and purification of wild-type and drug-resistant HIV-1
protease variants used for crystallization and binding experiments
were carried out as previously described.[34] More details are provided in Supporting Information. The data collection and refinement statistics are shown in Supplementary Table 1.
Structural Analysis
The wild-type protease-inhibitor crystallographic complexes were
evaluated in terms of substrate-envelope hypothesis. The extent to
which an inhibitor violates the substrate envelope was measured by
the volume of its non-hydrogen atoms that protrude outside (calculated
in total or decomposed at various sites). The protrusion volume was
calculated based on a grid with 0.2-Å spacing.
Authors: Madhavi N L Nalam; Akbar Ali; Michael D Altman; G S Kiran Kumar Reddy; Sripriya Chellappan; Visvaldas Kairys; Aysegül Ozen; Hong Cao; Michael K Gilson; Bruce Tidor; Tariq M Rana; Celia A Schiffer Journal: J Virol Date: 2010-03-17 Impact factor: 5.103
Authors: Keith P Romano; Jennifer M Laine; Laura M Deveau; Hong Cao; Francesca Massi; Celia A Schiffer Journal: J Virol Date: 2011-04-20 Impact factor: 5.103
Authors: Maloy Kumar Parai; David J Huggins; Hong Cao; Madhavi N L Nalam; Akbar Ali; Celia A Schiffer; Bruce Tidor; Tariq M Rana Journal: J Med Chem Date: 2012-07-13 Impact factor: 7.446
Authors: N A Roberts; J A Martin; D Kinchington; A V Broadhurst; J C Craig; I B Duncan; S A Galpin; B K Handa; J Kay; A Kröhn Journal: Science Date: 1990-04-20 Impact factor: 47.728
Authors: Akbar Ali; G S Kiran Kumar Reddy; Madhavi N L Nalam; Saima Ghafoor Anjum; Hong Cao; Celia A Schiffer; Tariq M Rana Journal: J Med Chem Date: 2010-11-11 Impact factor: 7.446
Authors: Alexander L Perryman; Weixuan Yu; Xin Wang; Sean Ekins; Stefano Forli; Shao-Gang Li; Joel S Freundlich; Peter J Tonge; Arthur J Olson Journal: J Chem Inf Model Date: 2015-02-17 Impact factor: 4.956
Authors: Ashley N Matthew; Florian Leidner; Gordon J Lockbaum; Mina Henes; Jacqueto Zephyr; Shurong Hou; Desaboini Nageswara Rao; Jennifer Timm; Linah N Rusere; Debra A Ragland; Janet L Paulsen; Kristina Prachanronarong; Djade I Soumana; Ellen A Nalivaika; Nese Kurt Yilmaz; Akbar Ali; Celia A Schiffer Journal: Chem Rev Date: 2021-01-07 Impact factor: 60.622
Authors: Xue Zhi Zhao; Steven J Smith; Daniel P Maskell; Mathieu Métifiot; Valerie E Pye; Katherine Fesen; Christophe Marchand; Yves Pommier; Peter Cherepanov; Stephen H Hughes; Terrence R Burke Journal: J Med Chem Date: 2017-08-10 Impact factor: 7.446
Authors: Xue Zhi Zhao; Steven J Smith; Daniel P Maskell; Mathieu Metifiot; Valerie E Pye; Katherine Fesen; Christophe Marchand; Yves Pommier; Peter Cherepanov; Stephen H Hughes; Terrence R Burke Journal: ACS Chem Biol Date: 2016-02-05 Impact factor: 5.100