NMR and MD simulations have demonstrated that the flaps of HIV-1 protease (HIV-1p) adopt a range of conformations that are coupled with its enzymatic activity. Previously, a model was created for an allosteric site located between the flap and the core of HIV-1p, called the Eye site (Biopolymers 2008, 89, 643-652). Here, results from our first study were combined with a ligand-based, lead-hopping method to identify a novel compound (NIT). NIT inhibits HIV-1p, independent of the presence of an active-site inhibitor such as pepstatin A. Assays showed that NIT acts on an allosteric site other than the dimerization interface. MD simulations of the ligand-protein complex show that NIT stably binds in the Eye site and restricts the flaps. That bound state of NIT is consistent with a crystal structure of similar fragments bound in the Eye site (Chem. Biol. Drug Des. 2010, 75, 257-268). Most importantly, NIT is equally potent against wild-type and a multidrug-resistant mutant of HIV-1p, which highlights the promise of allosteric inhibitors circumventing existing clinical resistance.
NMR and MD simulations have demonstrated that the flaps of HIV-1 protease (HIV-1p) adopt a range of conformations that are coupled with its enzymatic activity. Previously, a model was created for an allosteric site located between the flap and the core of HIV-1p, called the Eye site (Biopolymers 2008, 89, 643-652). Here, results from our first study were combined with a ligand-based, lead-hopping method to identify a novel compound (NIT). NIT inhibits HIV-1p, independent of the presence of an active-site inhibitor such as pepstatin A. Assays showed that NIT acts on an allosteric site other than the dimerization interface. MD simulations of the ligand-protein complex show that NIT stably binds in the Eye site and restricts the flaps. That bound state of NIT is consistent with a crystal structure of similar fragments bound in the Eye site (Chem. Biol. Drug Des. 2010, 75, 257-268). Most importantly, NIT is equally potent against wild-type and a multidrug-resistant mutant of HIV-1p, which highlights the promise of allosteric inhibitors circumventing existing clinical resistance.
Proteins are inherently dynamic and conformationally
heterogeneous. It is generally recognized that they exist in an ensemble
of differently populated conformational states in equilibrium, where
certain conformations play crucial roles in protein functions such
as enzymatic activity and molecular recognition.[3,4] Therefore,
it may be possible to design ligands that specifically target certain
conformational states of a protein and “lock” it into
an inactive state.[5−8]The aforementioned phenomenon can also be applied to other
protein systems to modulate enzymatic activity. In this study, we
focus on the clinically important HIV-1 protease (HIV-1p). HIV-1p
is a C2-symmetric, homodimeric protease
(Figure 1A). It is critical in the maturation
of the infective HIV virion[9] as it cleaves
the gag and gag-pol polyproteins to release the structural proteins (MA, CA, NC, and
p6) and the enzymes reverse transcriptase, integrase, and protease.[10] Thus, it is an important target for HIV infection
treatments and has led to several FDA-approved drugs that specifically
target its active site, which catalyzes the hydrolysis of the substrate
peptides.
Figure 1
(A) Cartoon representation of HIV-1p in the semiopen conformation
(PDB: 1HHP).
(B) Pharmacophore model of the HIV-1p allosteric site, the Eye site,
constructed by Damm et al.[1] When the 5NI–protease
crystal structure is superimposed on the pharmacophore model, the
agreement is obvious. The pharmacophores are color-coded according
to chemical property: hydrophobic (cyan), aromatic (green), hydrogen-bond
donor (red), and hydrogen-bond acceptor (blue). (C) Structure of compound 1 with inhibitory activity against HIV-1p.
(A) Cartoon representation of HIV-1p in the semiopen conformation
(PDB: 1HHP).
(B) Pharmacophore model of the HIV-1p allosteric site, the Eye site,
constructed by Damm et al.[1] When the 5NI–protease
crystal structure is superimposed on the pharmacophore model, the
agreement is obvious. The pharmacophores are color-coded according
to chemical property: hydrophobic (cyan), aromatic (green), hydrogen-bond
donor (red), and hydrogen-bond acceptor (blue). (C) Structure of compound 1 with inhibitory activity against HIV-1p.The active site of HIV-1p is gated by a pair of
glycine-rich, β-hairpin loops, one from each monomeric HIV-1p,
which is commonly referred to as the “flaps” (K45-M-I-G-G-I-G-G-F-I54).
The flaps control the access and positioning of the substrate in the
active site during hydrolysis, thus their mobility is essential to
HIV-1p activity. Several studies based on crystallography,[11,12] EPR,[13,14] NMR,[15] and molecular
dynamics (MD) simulations[16−18] suggest that the flaps of HIV-1p
exist in an ensemble of conformational states and can adopt a range
of conformations (closed, semiopen, and open).[19−22]HIV-1p possesses hydrophobic
flap-tip recognition pockets, or “Eye” sites, consisting
of residues Val32, Ile47, Gly48, Gly49, Ile50, Ile54, Val56, Gly78,
Pro79, Thr80, Pro81, and Ile84 (Figure 1A).
Upon substrate binding, each flap closes down and positions its flap
tip (residues 49–52) into this highly conserved region on the
opposite-side monomer. These sites are not present in the closed form
as the flap tip of the opposing monomer occupies each site. However,
in the event of flap opening, the flap tip undocks and the flap handedness
reverses, opening up the Eye site.As the opening of the Eye
site is dependent upon the positions of the flaps, we previously hypothesized
that specifically targeting this Eye site with the binding of a small
molecule could modulate the enzymatic activity of the protease through
altering the dynamics of the flaps and the equilibrium of the flap
conformational states.[1] To identify such
inhibitors, the varied conformations of the flaps were used to create
a pharmacophore model of the Eye site that was used for virtual screening.
This novel Eye-site pharmacophore model was constructed using the
multiple protein structures (MPS) method[23−26] (Figure 1B). Our earlier study screened the Center of Chemical Genomics (CCG)
library against the Eye site pharmacophore model, and subsequent testing
of the computational hits identified compound 1 as our
best inhibitor of HIV-1p proteolytic activity (Figure 1C).The possibility of targeting the Eye site was confirmed
by a recent study by Perryman et al.[2] that
identified potential allosteric sites of HIV-1p through fragment-based
crystallography. Of particular interest was a 2.1 Å crystal of
fragment-bound HIV-1p in semiopen conformation because the molecular
probe 5-nitroindole (5NI) was found to reside in the Eye site of HIV-1p.
In this particular 5NI-bound HIV-1p crystal structure, the molecular
probe 5NI forms hydrophobic contacts with Val32, Ile47, Ile54, Pro81,
and Ile84, and a hydrogen bond with the Gly51 amide through 5NI’s
nitro group. These residues have been suggested to play a role in
flap recognition.[16] This is the first crystallographic
confirmation that demonstrates the existence of the Eye site in the
semiopen HIV-1p, supporting the notion that the Eye site is a viable
site for small molecule targeting. Furthermore, 5NIfits well within
our Eye-site pharmacophore model (Figure 1B)
and overlaps with two of the three aromatic pharmacophore elements
as well as the hydrogen-bond acceptor element. Furthermore, the crystal
structure exhibited ligand binding to only one Eye site, not both,
which is consistent with our previous modeling work.[1]Here, we demonstrate that a nitro-containing compound
(NIT) derived from a ligand-based Markush search, which has similarity
to 5NI, can modulate the activity of HIV-1p. Additional experimental
and computational studies of the nitro-containing ligand suggest it
acts through the Eye site, an allosteric site of HIV-1p. Furthermore,
it is equipotent against a multidrug resistant (MDR) HIV-1p, which
shows that inhibitors with this mode of action can overcome existing
clinical resistance. Although NIT has only lead-like affinity, its
small size (MW = 357) gives a respectable ligand efficiency of −0.23
kcal/mol·heavy-atom. It is the first small, drug-like molecule
to be fully characterized as having an alternative mechanism against
HIV-1p and the ability to evade existing clinical resistance.
Materials and Methods
Markush Chemical-Similarity
Search
UNITY,[27,28] a module of the SYBYL[29] suite (version 8.0), was used for ligand-based
chemical search. A Markush search was constructed based on the chemical
structure and connectivity of the reference structure, compound 1. UNITY performed the query searches against academic and
commercial chemical libraries: ChemBridge (2007), ChemDiv (2007),
MayBridge (2007), and the CCG (2007.10) chemical libraries. Compounds
that matched the queries were selected, and 3D comparisons to compound 1 were used to further prioritize the sets. The 3D conformers
were generated with OMEGA 2.3.2,[30] a module
of the OpenEye suite. The selected compounds were scored and ranked
by ROCS (version 3.0.0) and EON (version 2.0.1), respectively.[31] ROCS scores a chemical according to its shape
similarity to the bound pose from our previous work,[1] while EON scores the charge distribution similarity of
a chemical to the reference structure. A consensus score of the ROCS
and EON scores with equal weight were used to rank the selected compounds.
The top 200 compounds from each library were examined manually, and
48 compounds were selected for testing experimentally based on diversity,
size, solubility, cost, and availability from the vendors (CCG, 5
compounds; ChemBridge, 30 compounds; ChemDiv, 8 compounds; MayBridge,
5 compounds).
Inhibitor Screening Assay
Pseudo
wild-type (WT; G7K) and a MDR strain (L10I/L63P/A71V/G73S/I84V/L90M)
of HIV-1p were kindly provided by Dr. Celia Schiffer of the University
of Massachusetts. Pseudo-WT protease was used to avoid autoproteolysis
activity of HIV-1p. A resonance energy transfer (FRET)-based biochemical
assay was used to assess the HIV-1p enzymatic activity. A fluorogenic
peptide substrate was used, RE(EDANS)SQNYPIVQK(Dabcyl)R (Molecular
Probes, Catalogue no. H-2930) was used. This substrate contains a
fluorophore EDANS and a chromophore Dabcyl, which quenches the excited
fluorophore when the two chromophores are in close proximity.[32] EDANS has an excitation wavelength near 340
nm and emission wavelength near 490 nm, while Dabcyl has an excitation
wavelength overlapping the emission range of EDANS. The peptide substrate
turnover by the protease was monitored by the spectrometer SpectraMax
M5 from the Molecular Devices. Top-read mode was used in the fluorescence
detection, where excitation/emission wavelengths of EDANS at 340 and
490 nm, respectively, were monitored. A 475 nm cutoff filter was applied
to reduce the noise signal. Screening assays were performed in triplicate
in black, round-bottom, low-volume, 384-well plates (Corning no. 3676).All purchased compounds were screened at 150 μM (HIV-1p at
30 nM and substrate at 2 μM). Stock solution of the tested compound
dissolved in DMSO was diluted with milli-Q H2O to 10-fold
the desired final concentration. Final concentration of DMSO in the
assay was kept below 2% v/v.[33] Milli-Q
H2O and pepstatin A (PepA) were used as the negative and
positive controls, respectively. The ligand solution was mixed with
the protease in the standard assay buffer (100 mM sodium acetate,
1 M NaCl, 1 mM EDTA, 1 mM DTT, 20% v/v glycerol, 0.1% w/w CHAPS, 0.2%
v/v PEG-400, pH = 4.7)[1,34−38] and incubated for 30 min at room temperature. The
enzymatic assay was initiated by introduction of the fluorogenic peptide
substrate (diluted in assay buffer) and shaken for 15 s inside the
plate reader; the assay was monitored for 10 min at 30 °C. The
kinetic data was fitted linearly to determine the rate of fluorogenic
substrate turnover, measured as change in fluorescence intensity per
unit time. Inhibitory activity was calculated by comparing the turnover
rate against the negative control,where RFU is the raw
fluorescence unit measured by the spectrometer.
Michaelis–Menten
Kinetics
The Michaelis–Menten kinetics of the fluorogenic
peptide substrate with WT or MDR HIV-1p was performed by varying the
fluorogenic substrate concentration between 2.5 and 100 μM against
a constant concentration of HIV-1p at 30 nM. The experimental conditions
were identical to those mentioned above. As this experiment requires
the use of high concentrations of fluorogenic peptide substrate, which
contains the chromophore Dabcyl, reabsorption of the fluorophore-emitted
light by the chromophores in the solution will be significant. This
effect, called the inner filter effect, will disproportionally affect
and reduce the intensity of observed fluorescence at high substrate
concentration (>20 μM) while having little influence on the
intensity of fluorescence at low substrate concentration. To correct
this effect, a standard curve of EDANS fluorescence against an increasing
concentration of the fluorogenic peptide substrate was obtained and
used to correct the intensity of observed fluorescence. The data-analysis
package SigmaPlot version 11.0 (from Systat Software, Inc., San Jose
California USA, www.sigmaplot.com) was used to calculate
the Michaelis constant (Km) by fitting
the data to an one-site saturation model with a nonlinear regression
method.
Dose-Dependent Inhibition Assay
For IC50 determination, the final concentrations of protease and fluorogenic
peptide substrate were 30 nM and 5 μM, respectively. For our
buffer and assay condition, Km of the
substrate was determined to be 91 ± 11 and 207 ± 26 μM
for WT and MDR HIV-1p, respectively. IC50 and Hill slope
were obtained by fitting the kinetic data to a sigmoidal dose–response
model using SigmaPlot. Assuming that dose–response kinetics
are appropriate to describe allosteric inhibition, the inhibition
constant (Ki) of the tested compound was
obtained through the Cheng–Pursoff equation
Dimerization Inhibition
Analysis
To rule out the mechanism where the compounds inhibit
dimerization, Zhang–Poorman kinetics analysis was performed.[37,39−41] Protease concentration was varied between 0.5 and
30 nM while substrate concentration was fixed at 10 μM. The
kinetic data was plotted as √v vs [E]0/√v, where v is the rate of substrate turnover and [E]0 is the concentration of the protease. The kinetic data
was linearly fitted and the mode of inhibition was determined by comparing
the slope of the curves, where parallel lines indicate the compound
modulates protease activity through binding the monomer and blocking
dimerization while intercepting lines indicate the mode of inhibition
targets the dimeric form of HIV-1p.
Cross-Competitive Inhibition
A variation of Yonetani–Theorell kinetic analysis was used
to examine the mode of inhibition.[42,43] PepA, a known
competitive inhibitor for HIV-1p, was used in this kinetic assay.
PepA concentration varied from 0–300 nM in assay with WT HIV-1p
and 0–400 nM with MDR HIV-1p.[44] The
concentrations of substrate and protease were kept at 5 μM and
30 nM, respectively, while other experimental conditions were the
same as above. The kinetic data was plotted as v0/v versus [PepA]/IC50PepA. The kinetic
data was fitted linearly to determine the interaction factor that
defines the type of interaction (agonistic, antagonistic, or mutually
exclusive) between the known competitive inhibitor and the tested
compound.
Dynamics Simulations
Unrestrained all-atom MD and Langevin
dynamic (LD) simulations were performed with the FF99SB force field[45] and the AMBER10 suite of programs.[46] An apo HIV-1p in semiopen conformation (PDB: 1HHP(47)) obtained from the PDB[48] was
used and the C2-symmetric homodimer was
generated using PyMOL version 1.2.[49] The
ionizable groups of the protein were protonated by the defaults in
tLEaP and approved through “by hand” inspection. One
of the catalytic Asp25s was protonated, from ASP to ASH. The ligand
NIT was placed into the Eye site of HIV-1p by docking with Schrödinger’s
Glide[50] (version 5.5), using standard precision
and default settings. The web-based R.E.D.[51] (version 3.4) and Ante_R.E.D. (version 2.0) were used to derive
the RESP charge values for the ligand NIT. The ESP charges were determined
at HF/6-31G* level with Gaussian09, which were then fitted to the
ligand through a two-stage RESP fitting. Force field parameters of
NIT were built from analogy to parameters in the general AMBER force
field[52] and the RESP charges using the
Antechamber module of AMBER.[53]Five
independent, 20 ns MD simulations were performed using different random-number
seeds. The NIT–protease complex was solvated with a truncated
octahedral TIP3P water box[54] with a buffer
distance of 12 Å and closeness parameter of 0.5. The system charge
was neutralized with Cl– counterions. A 10- Å
cutoff for van der Waals interactions was used, and particle mesh
Ewald for long-range electrostatics[55] was
employed. The simulations were run in the NPT ensemble, and SHAKE[56] was used to constrain all bonds to hydrogen
atoms to allow a 2 fs time step. To avoid water from inappropriately
warping the protein, we applied the following equilibration protocol.[57] For the solvated system, hydrogen atoms were
first minimized, followed by the side chains and then all atoms. The
system was then equilibrated first with a gradual heating of water
from 10 to 310 K over 50 ps and then a water equilibration with protein
atoms restrained for 250 ps at 310 K. This was followed by a full
system heating from 10 to 310 K over 180 ps and a full system equilibration
with protein unrestrained at 310 K for 400 ps. The production phase
was run for 20 ns at 310 K.Five independent, 20 ns LD simulations
were also performed. Hydrogen atoms were constrained with SHAKE while
a 999 Å cutoff distance for nonbonded interactions was used.
Generalized Born approach was used to implicitly model aqueous solvation
for the LD simulations.[58] Default dielectric
values, where interior = 1 and exterior = 78.5, were used. The time
step and the collision frequency of the simulation were 1 fs and 1
ps–1, respectively. Simulations began with hydrogen
minimization, followed by side chain and then all-atom minimizations.
Equilibration was done in six stages: the system was gradually heated
from 100 K to the final temperature at 300 K in the first two equilibration
steps. Restraints were placed on all heavy atoms and gradually removed
over the first four equilibration steps using force constants from
2.0 to 0.1 kcal/mol·Å2, where the first three
steps were done over 10 ps and the fourth step over 50 ps. Only the
backbone atoms were restrained at 0.1 kcal/mol·Å2 over 50 ps in the fifth equilibration step. In the sixth equilibration
step, the restraints were removed, and all atoms were allowed full
freedom for 300 ps at 300 K. The production phase was run for 20 ns.
Analysis of the trajectories was performed using the PTRAJ module
of AMBER.
Essential Dynamics Analysis
Essential dynamics analysis
of the MD trajectory data was used to compare dynamics of the protein
structure in simulations.[59,60] PTRAJ was used to perform
the orthogonal transformation calculation on the covariance matrix
of the backbone heavy atoms and solve for the eigenvectors and the
associated eigenvalues of the MD trajectories.[61] The eigenvectors were compared by calculating the dot product
of the corresponding vectors in each set of eigenvector. The dot-product
values were then rescaled to between 0 and 100, where 0 corresponds
to a dot-product of 1.0, i.e., strongly correlated, and 100 corresponds
to a dot-product of −1.0, i.e., strongly anticorrelated. The
rescaled dot-product values were added to a reference PDB structure
for visualization in VMD 1.8.9.[62]
Results
and Discussion
Identification of Compounds through Pharmacophore
Screening
The Eye-site pharmacophore model has been used
to virtually screen against the CCG library from the University of
Michigan. The best inhibitor, 2,2,4-trimethyl-1,2-dihydroquinolin-6-yl
4-methoxybenzoate (compound 1), had dose-dependent activity
against HIV-1p (Figure 1C).[1] This compound was the first experimentally tested, active
inhibitor that was designed to target the newly discovered allosteric
site rather than the traditional catalytic site.The chemistry
space around the chemical scaffold of compound 1 was
further explored and expanded to identify new scaffolds that would
fit the Eye site pharmacophore model and target the allosteric site
of HIV-1p. We applied a structure-based, lead-hopping method to explore
nearby chemical space. The chemical features of compound 1 were used to generate a Markush chemical similarity search with
the following general features: (1) sp2 N–H connecting to an aromatic ring (analogue to quinolin-6-yl
moiety) that can be either a 5- or 6-membered ring, (2) aromatic ring
of any decoration (analogue to p-methoxy benzoate
moiety), and (3) a 3-atom linker of connecting (1) and (2) (analogue
to the ester linkage).The Markush search queries were constructed
(Figure 2A) based on the chemical features
and connectivity of the reference structure, compound 1 (Figure 1C). UNITY, a module of SYBYL suite,
was used in the ligand-based chemical search against the CCG library
(v2007.10, ∼90000 compounds) and libraries of three commercial
vendors: ChemBridge (EXPRESS-Pick v2007, ∼50000 compounds),
ChemDiv (2007, ∼120000 compounds), and MayBridge (v2007, ∼56000
compounds) chemical libraries. As a result, 7230 compounds matched
the Markush search queries.
Figure 2
(A) Summary of Markush search based on the chemical
features and connectivity of compound 1. The search queries
have these designations: A, any bond order; S, single bond only; x,
any heavy atom; i and j, number
of heavy atoms. (B) List of linker moieties used in the filtering
of Markush search results.
(A) Summary of Markush search based on the chemical
features and connectivity of compound 1. The search queries
have these designations: A, any bond order; S, single bond only; x,
any heavy atom; i and j, number
of heavy atoms. (B) List of linker moieties used in the filtering
of Markush search results.To prioritize and rank the compounds that matched the Markush
search queries, 3D conformations of the selected compounds were compared
to the conformations of compound 1. The 3D comparisons
were scored by ROCS and EON, both modules of the OpenEye suite. ROCS
scores a chemical according to its shape complementary to the reference
structure (compound 1), while EON scores based on the
similarity of charge distribution of a chemical to the reference structure.
A consensus score of the ROCS and EON scores with equal weight were
used to rank the selected compounds. The top-200 compounds were examined
manually, and only those with fused double aromatic rings (similar
to quinolin-6-yl moiety) and unique linkers (Figure 2B) were selected. Finally, 48 compounds (5 from CCG, 30 from
ChemBridge, 8 from ChemDiv, and 5 from MayBridge) were purchased for
experimental testing (listed in Table S1 of the
Supporting Information). One compound, ChemBridge 5979646,
was identified to have good inhibitory activity against HIV-1p, and
most importantly, it shared chemical features with compound 5NI, the
fragment found to bind the Eye site in crystallographic studies.[2] This compound was specifically selected for more
in depth study. The mass spectroscopy data and proton NMR spectrum
for ChemBridge 5979646 (compound NIT) are given in the Supporting Information, Figure S1. Although nitro
groups are often a concern for medicinal chemistry, it is desirable
in this case. NIT does not trigger any of the chemical alerts in OpenEye’s
FILTER[63] program nor does it contain any
functional groups identified in the PAINS filter (Pan Assay Interference
compounds).[64]
Dose-Dependent Inhibition
of NIT
We confirmed that ChemBridge 5979646, 4-nitro-2-(2-thioxo-2,3-dihydrobenzothiazol-6-yl)isoindoline-1,3-dione
(NIT, Figure 3A), inhibited WT HIV-1p activity
in a dose-dependent manner and has a Ki = 96 ± 3 μM (Figure 3B). This
translates into a binding affinity of approximately −5.5 kcal/mol
and a respectable binding efficiency of −0.23 kcal/mol·heavy-atom.
To eliminate the possibility of NIT as a promiscuous aggregator, we
performed a dose-dependence assay at three HIV-1p concentrations (15,
30, 45 nM);[65] no significant change in
Hill slope value was observed (Figure 3B, insert).
Figure 3
(A) Compound
NIT is identified through Markush chemical similarity search queries
built from compound 1. (B) Dose-dependence inhibition
curves of compound NIT against HIV-1p. It has similar inhibitory activity
against the WT (●, Ki = 96 ±
3 μM) and MDR HIV-1p (○, Ki = 92 ± 6 μM) at 30 nM protease concentration. The insert
figure is the dose-dependence inhibition curves of NIT at different
WT HIV-1p concentrations (▼, 15 nM; ○, 30 nM; ●,
45 nM) and have very similar Hill slope values. (C) FRED[66] docking pose of NIT (green stick) overlaying
with the Eye site pharmacophore model.[1] The pharmacophores are color-coded according to chemical property:
hydrophobic (cyan), aromatic (green), hydrogen-bond donor (red), and
hydrogen-bond acceptor (blue). (D) FRED docking pose of NIT (green
stick) overlaying with the crystal fragment 5NI (purple stick) in
the Eye site.[2]
(A) Compound
NIT is identified through Markush chemical similarity search queries
built from compound 1. (B) Dose-dependence inhibition
curves of compound NIT against HIV-1p. It has similar inhibitory activity
against the WT (●, Ki = 96 ±
3 μM) and MDR HIV-1p (○, Ki = 92 ± 6 μM) at 30 nM protease concentration. The insert
figure is the dose-dependence inhibition curves of NIT at different
WT HIV-1p concentrations (▼, 15 nM; ○, 30 nM; ●,
45 nM) and have very similar Hill slope values. (C) FRED[66] docking pose of NIT (green stick) overlaying
with the Eye site pharmacophore model.[1] The pharmacophores are color-coded according to chemical property:
hydrophobic (cyan), aromatic (green), hydrogen-bond donor (red), and
hydrogen-bond acceptor (blue). (D) FRED docking pose of NIT (green
stick) overlaying with the crystal fragment 5NI (purple stick) in
the Eye site.[2]We investigated the effectiveness of compound NIT against
a MDR HIV-1p mutant (L10I/L63P/A71V/G73S/I84V/L90M). Using the competitive
inhibitor PepA as the control, we showed that the MDR mutations cause
a 2.5-fold increase in Ki of PepA compared
to WT HIV-1p (KiMDR = 0.23
± 0.06 μM and Hill slope ∼1.0; KiWT = 0.094 ± 0.012 μM and Hill
slope ∼1.0). Significantly, the MDR mutations do not appear
to impact the Ki of compound NIT at all
(Figure 3B; KiMDR = 91 ± 6 μM and Hill slope ∼1.5; KiWT = 96 ± 3 μM and Hill
slope ∼1.6). The MDR mutant is as sensitive to NIT
as the WT. Furthermore, NIT has a Hill slope value of ∼1.5
in the dose-dependent assay against both WT and MDR HIV-1p. This implies
NIT may interact with more than one binding site on the protease,
which is consistent with the presence of two Eye sites on each HIV-1p.Docking of NIT to the Eye site of semiopen HIV-1p with FRED shows
that NIT overlays some of the Eye pharmacophores (Figure 3C). The nitro group matches the hydrogendonor pharmacophore,
while the isoindoline-1,3-dione (IID) moiety overlaps with the aromatic
pharmacophores. In addition, the 4-nitro-IID (4NIID) moiety of compound
NIT is similar to the molecular probe, 5NI, which was observed to
occupy the Eye site of an apo HIV-1p crystal structure in semiopen
conformation.[2] Docking of NIT to the Eye
site with FRED generated poses with contacts to HIV-1p similar to
5NI (Figure 3D). The 4NIID moiety forms hydrophobic
contacts with Val32, Ile47, Ile54, Pro81, and Ile84 and a hydrogen
bond with the amide of Ile50 through the nitro group, similar to the
interactions seen in the 5NI–protease complex crystal structure.
The benzothiazole-2-thione moiety of NIT forms hydrophobic contacts
with Val32, Ile47, and Leu76 and hydrogen bonds with Asp30 and Gly48.
These additional interactions likely explain the slight difference
in orientation of the 4NIID moiety of compound NIT, relative to the
posing of 5NI in the crystal structure (Figure 3D).
NIT Affects Michaelis–Menten Kinetics
To determine
the effect of compound NIT on the kinetics of the HIV-1p, we determined
the protease activity at various substrate concentrations (2.5–100
μM) using several concentrations of NIT. We obtained the Km and Vmax parameters
of the HIV-1p through fitting the measured initial velocities to the
Michaelis–Menten kinetics model using nonlinear, least-squares
regression. We observed dose-dependent changes in the Km and Vmax of WT HIV-1p after
the introduction of NIT. The result is consistent with mixed competitive
inhibition kinetics, where the apparent Km increases as NIT concentration increases, while Vmax decreases concurrently (Table 1). The same trend is also observed in the MDR HIV-1p. This suggests
NIT may be able to bind to both apo and substrate-bound HIV-1p and
may bind to an allosteric site as a mixed competitive inhibitor rather
than binding to the catalytic site as a competitive inhibitor.
Table 1
Effects of Compound NIT on the Michaelis–Menten
Kinetics of WT and MDR HIV-1p
compound NIT (μM)
0
100
150
WT
Vmax (nM/s)
44 ± 3
35 ± 3
34 ± 3
Km (μM)
91 ± 8
144 ± 18
184 ± 26
MDR
Vmax (nM/s)
42 ± 6
30 ± 2
30 ± 4
Km (μM)
171 ± 36
246 ± 21
359 ± 66
Ruling Out
NIT as Dimerization Inhibitor
Although compound NIT may not
act on the HIV-1p through the catalytic site, it is possible that
NIT can modulate HIV-1p activity through an alternative site such
as the dimer interface. To examine if NIT modulated the observed HIV-1p
activity through disrupting the dimer interface, we determined the
rate of protease-catalyzed hydrolysis (v) of the fluorogenic substrate at various protease
concentrations for both WT and MDR strains of HIV-1p, ranging from
0.5 to 30 nM. The resulting initial velocities of the reaction were
plotted as [E]0/√v vs √v according to the Zhang–Poorman equation.
We observed lines with increasing slope as the ligand concentration
increased (Figure 4). The same variation in
slope was also observed when pepA, a competitive inhibitor, was used
as a nondimer inhibitor control (Figure 4;
insert). Hence, we determined that NIT does not act as a dimerization
inhibitor to HIV-1p as it does not generate the typical parallel lines
seen in classical dimer inhibitors in the Zhang–Poorman plot.[37]
Figure 4
Zhang–Poorman analysis of compound NIT (0.5–30
nM HIV-1p; 5 μM substrate) with (A) WT and (B) MDR HIV-1p. Compound
NIT concentrations: ■, 0 μM; Δ, 90 μM; ▼,
120 μM; ○, 150 μM; ●, 180 μM. Nonparallel
linear fits of compound NIT at various concentrations indicates the
small molecule does not act as a dimerization inhibitor. The small
insert in WT shows the Zhang–Poorman plot of PepA, a nondimerization
inhibitor (●, 0 nM; ▼, 150 nM; ○, 300 nM).
Zhang–Poorman analysis of compound NIT (0.5–30
nM HIV-1p; 5 μM substrate) with (A) WT and (B) MDR HIV-1p. Compound
NIT concentrations: ■, 0 μM; Δ, 90 μM; ▼,
120 μM; ○, 150 μM; ●, 180 μM. Nonparallel
linear fits of compound NIT at various concentrations indicates the
small molecule does not act as a dimerization inhibitor. The small
insert in WT shows the Zhang–Poorman plot of PepA, a nondimerization
inhibitor (●, 0 nM; ▼, 150 nM; ○, 300 nM).
Interaction of NIT and
Competitive Inhibitor Pepstatin A
As compound NIT does not
affect HIV-1p activity through the dimerization interface and appears
as a mixed competitive inhibitor to HIV-1p in the Michaelis–Menten
kinetics model, this indicates that NIT can bind to the protease while
the substrate is bound to the protease catalytic site. To test how
compound NIT interacts with the protease in relation to the substrate,
we performed a cross-competitive assay of NIT with PepA. We used the
Yonetani–Theorell plot in the form of eq1 to evaluate the binding mode of the small molecule.[42,43,67]By rearranging eq 1 and plotting the data into eq 2, we obtained factor γ, which represents the degree of mutual
influence of the two inhibitors on the binding of each other. In principal,
the Yonetani–Theorell plot of v0/v vs [I1] at various fixed [I2] will
give a series of parallel lines when the two ligands bind to the enzyme
in a mutually exclusive manner (γ = ∞). If the two ligands
bind to the enzyme simultaneously, the lines will intercept (∞
> γ > 0) and the type and strength of mutual interference
(facilitation when 0 < γ < 1; hindrance when 1 < γ
< ∞) can be assessed by the numerical value of γ.
In the case when γ = 1, the two ligands bind in an independent
manner.Compound NIT at fixed concentrations
was assayed against the competitive inhibitor PepA at various concentrations,
and the kinetic data was visualized with the Yonetani–Theorell
plot. Intercepting lines of fixed NIT concentration were observed,
indicating that NIT does not bind mutually exclusively to the substrate
hydrolysis site where PepA binds competitively. NIT yields a γ
value that is approximately 1.0 ± 0.2 with both WT and MDR HIV-1p
(Figure 5). NIT likely binds independently
to a separate site and does not interfere with the binding of competitive
inhibitors to the substrate hydrolysis site.
Figure 5
Cross-competitive inhibition
analysis of compound NIT (30 nM HIV-1p, 5 μM substrate) against
known competitive inhibitor, PepA. (A) WT HIV-1p with compound NIT
at concentrations: ●, 0 μM; ○, 90 μM; ▼,
150 μM; and Δ, 200 μM. (B) MDR protease with compound
NIT at concentrations: ●, 0 μM; ○, 50 μM;
▼, 100 μM; and Δ, 150 μM. The interaction
term γ determined from the curves is approximately 1.0 for both
WT and MDR HIV-1p.
Cross-competitive inhibition
analysis of compound NIT (30 nM HIV-1p, 5 μM substrate) against
known competitive inhibitor, PepA. (A) WT HIV-1p with compound NIT
at concentrations: ●, 0 μM; ○, 90 μM; ▼,
150 μM; and Δ, 200 μM. (B) MDR protease with compound
NIT at concentrations: ●, 0 μM; ○, 50 μM;
▼, 100 μM; and Δ, 150 μM. The interaction
term γ determined from the curves is approximately 1.0 for both
WT and MDR HIV-1p.In summary, NIT exhibits
mixed inhibition kinetics in the Michaelis–Menten kinetics
model, binds independently to a separate site, does not compete with
PepA for the substrate hydrolysis site, and does not modulate HIV-1p
activity through the dimerization interface. These kinetics data support
the idea that NIT binds to an allosteric site and modulates HIV-1p
catalytic activity through a noncompetitive binding mode. Additionally,
NIT is topologically similar to compound 1 that fits
the MPS pharmacophore,[1] while it is structurally
similar to 5NI that overlays to part of the MPS pharmacophore model
and is seen crystallographically bound to the Eye site.[2] These data strongly suggest that NIT targets
the Eye site of HIV-1p and modulates the protein in a novel allosteric
manner. Furthermore, NIT is more attractive chemically because it
is more soluble than compound 1 and does not contain
an easily cleaved ester linker like 1. Furthermore, it
is equipotent against WT and MDR HIV-1p, which underscores the promise
of alternate modes of inhibition to overcome existing clinical resistance.
Dynamics Studies of NIT–Protease Complex
To further
examine the interactions between compound NIT and the Eye site of
HIV-1p, five independent runs of 20 ns MD simulations were performed
(100 ns total). Compound NIT was initially docked into one of the
two Eye sites of the homodimeric HIV-1p with Glide, and the docked
conformation of NIT with the best score was used as the starting conformation
in HIV-1p for simulations. The NIT–protease complex was stable
throughout the simulations (see Figure S2A, Figure
S2B, and Table S2 in the Supporting Information). During the
MD simulations, NIT adjusted its position and remained in the Eye
site throughout most of the simulation trajectories. In one of the
five trajectories, NIT briefly left the Eye site for 2 ns but returned
to the Eye site and remained there for the rest of the trajectory.
This rebinding behavior was seen in our previous study of compound 1.The median RMSD of NIT throughout the simulation
trajectories when compared to the starting frame of the trajectory
is 5.1 Å and 50% of the trajectories have RMSD ranging between
3.9 Å to 6.1 Å (Figure S2C, Table S3). NIT remained in the site with a median center-of-mass (COM) distance
of 4.7 Å when measuring the distance between all atoms of NIT
and the Eye site residues. To put this value in perspective, the COM
distance in Figure 3C is 3.6 Å. The COM
distance is between 3.3 Å to 5.9 Å in 50% of the analyzed
MD trajectories (Figure 6). This demonstrates
that NIT binds stably to the Eye site of HIV-1p.
Figure 6
Distribution of distance
(Å) between the center-of-mass (COM) of NIT and HIV-1p Eye site
in MD and LD simulations. In MD simulations (red line), NIT remained
in HIV-1p Eye site throughout all trajectories.
Distribution of distance
(Å) between the center-of-mass (COM) of NIT and HIV-1p Eye site
in MD and LD simulations. In MD simulations (red line), NIT remained
in HIV-1p Eye site throughout all trajectories.Additionally, five independent runs of 20 ns Langevin dynamics
(LD) simulations of the NIT–protease complex were conducted.
As there is no dampening effect from the explicit solvent molecules,
NIT and HIV-1p alike had more atomic fluctuations compared to the
MD simulations (Supporting Information, Figure
S3, Table S4). Whereas compound NIT mostly remained in the
Eye site of the HIV-1p throughout the trajectory of the MD simulations,
NIT in all five independent LD simulations would exit the Eye site,
sample conformations along the protein surface, and rebind to one
of the 2 Eye sites of HIV-1p (Figure 7). Two
possible paths of NIT transition from one Eye site to another are
observed; one path moves along across the active site without full
dissociating from the HIV-1p as seen previously in Damm et al.[1] The other path involves a full exit of the HIV-1p,
sampling the surface of the flaps and rebinding the Eye site on the
opposite monomer (Figure 7B). This indicates
that NIT is able to sample both of the available Eye sites. Overall,
compound NIT is within the monomer 1’s Eye site during ∼40%
of the trajectories at 7.0 Å COM distance cutoff and within the
monomer 2’s Eye site ∼28% at 7.0 Å COM distance
cutoff. Combined, at a 7.0 Å COM distance cutoff, NIT occupied
Eye sites in HIV-1p monomer 1 or 2 during ∼68% of the trajectory.
The remaining time, it mostly sampled along the surface of the flap
region. The COM distance ranged between 4.7 and 7.7 Å and a median
distance of 5.6 Å for 50% of the analyzed trajectories. The high
frequency of sampling at the Eye sites demonstrates that it is viable
for ligand binding (Figure 6).
Figure 7
Paths of NIT transition
between two Eye sites of HIV-1p. (A) NIT traveled across the active
site from one Eye site to the other without complete dissociation
from the protease. (B) NIT dissociates from one Eye site and travels
along to surface of the flaps before binding to the opposite Eye site.
Paths of NIT transition
between two Eye sites of HIV-1p. (A) NIT traveled across the active
site from one Eye site to the other without complete dissociation
from the protease. (B) NIT dissociates from one Eye site and travels
along to surface of the flaps before binding to the opposite Eye site.Throughout the MD trajectories,
NIT interacted primarily (>50% of the trajectory) with the flap
residues (Ile47, Gly48, Gly49, Ile50, Ile54) and with the bottom of
the Eye site (Val32, Gly78, Pro79, Thr80, Pro81, Ile84). These residues
were frequently with a heavy-atom cutoff distance of 4.1 Å (Figure 8). Of the residues that NIT consistently interacted
with, Gly49, Gly78, Pro79, Thr80, and Pro81 are known to be highly
conserved;[68,69] most importantly, Thr80 has such
a strong influence on the flap region’s flexibility that a
mutation of this invariant residue results in a deleterious effect
on HIV-1p catalytic activity.[38] Four residues
that NIT interacts with are known to have conservative mutations that
maintain the hydrophobic nature of the side chains: Val32(I), Ile47(V/A),
Gly48(V), and Ile50(V/L).[68,69] Ile54 and Ile84, which
have relatively low frequency of contact with the ligand (Figure 8), are known to have nonconservative mutations although
the most common clinically observed mutations maintain the hydrophobic
character of the side chain: Ile54(V) and Ile84(V/A).
Figure 8
HIV-1p residues in contact
with compound NIT. Residues with over 30% of the trajectory in contact
with NIT (heavy-atom cutoff distance 4.1 Å) during MD simulations
are colored, where blue is below the threshold 30% and red is the
maximum 80% of the simulations. Bolded and underlined residues are
found to be highly conserved, and those with name in bold and bracket
are found to have conservative mutations in the clinic.
HIV-1p residues in contact
with compound NIT. Residues with over 30% of the trajectory in contact
with NIT (heavy-atom cutoff distance 4.1 Å) during MD simulations
are colored, where blue is below the threshold 30% and red is the
maximum 80% of the simulations. Bolded and underlined residues are
found to be highly conserved, and those with name in bold and bracket
are found to have conservative mutations in the clinic.To examine the change in the dynamic behaviors
of HIV-1p due to the binding of NIT to the Eye site, essential dynamics
analysis was applied to analyze the MD trajectories of NIT–protease
complex and an apo protease. Essential dynamics analyzes the protein
dynamics by performing an orthogonal transformation of a covariance
matrix of the MD trajectories and isolates the collective modes of
motion of the protein. An individual mode of motion, or eigenvector,
contains the collective motion of the residues of the examined protein
while the associating eigenvalue quantifies the contribution of the
eigenvector in the examined trajectories. Each of these eigenvectors
can be visualized and inspected separately to distinguish the main
modes of collective motion from the more localized fluctuations. The
first few eigenvectors, or modes of motion, usually describe the global,
dynamic motions of the protein (i.e., domain movement and change in
protein conformation), while the higher-order modes of motion usually
describe the local dynamic motions (i.e., residue side chain movements).To compare the essential dynamics of NIT–protease complex
to apo-protease, a dot-product was calculated between the eigenvectors
as a measurement of the degree of overlap between the examined vectors.
Visual inspection of the MD and comparison of the first eigenvector
of both systems, as shown in Figure 9, indicates
a significant conformational change to the flap in contact with NIT,
for which the motion of the flap in NIT–protease complex and
in apo protease is strongly anticorrelated (the rest of the protein
remains relatively correlated). Furthermore, both first eigenvectors
have significant contribution to the overall dynamic motion of the
protease in each respective trajectory; the first eigenvector of NIT–protease
complex has a normalized eigenvalue of 0.403, while apo-protease has
a normalized eigenvalue of 0.540. This strongly suggests that the
influence of the extensive interactions with compound NIT in the Eye
site has a profound effect on the dynamic motion the flap throughout
the trajectory, as one might expect.
Figure 9
ED indicates how the binding of NIT influences
HIV-1p flap movement. The first eigenvector of the ED of (A) apo HIV-1p
MD simulation and (B) NIT–protease MD simulations indicates
the most significant motions of the protease. Vectors of the flap
residue are colored: monomer A is in red and monomer B is in blue.
The presence of NIT in the Eye site induces significant localized
change in flap movements. (C) Quantitative comparison of the eigenvectors
is done through the calculation of the dot-product of (A) and (B).
In this last frame, the blue color indicates strong correlation while
red color indicates strong anticorrelation for residue motion in the
two eigenvectors.
ED indicates how the binding of NIT influences
HIV-1p flap movement. The first eigenvector of the ED of (A) apo HIV-1p
MD simulation and (B) NIT–protease MD simulations indicates
the most significant motions of the protease. Vectors of the flap
residue are colored: monomer A is in red and monomer B is in blue.
The presence of NIT in the Eye site induces significant localized
change in flap movements. (C) Quantitative comparison of the eigenvectors
is done through the calculation of the dot-product of (A) and (B).
In this last frame, the blue color indicates strong correlation while
red color indicates strong anticorrelation for residue motion in the
two eigenvectors.Another observation is
the change in the flap openness of HIV-1p in the MD trajectories through
binding of NIT to the Eye site (Table 2). The
degree of flap openness can be described by the Cα distance measured between catalytic Asp25 and
flap-tipIle50.[70] The flap-opening distance
in 50% of the trajectories ranges between 13.7 and 15.8 Å with
a median of 14.8 Å, and the opposite monomer with no NIT bound
to the Eye site has a similar flap opening distance between 13.0 and
16.1 Å with a median of 14.3 Å (Table 2). This is compared to the apo HIV-1p MD trajectory where 50% of
the trajectory has a flap opening distance of 11.9–17.3 Å
and a median of 15.1 Å. The flaps under the influence of NIT
remain in the semiopen conformation states comparable to the semiopen
conformational states observed in apo HIV-1p (median of 14.8 Å
with NIT and 14.3 Å without NIT vs 15.1 Å in apo HIV-1p)
and has a smaller range of motion compared to the apo HIV-1p (RMS
distance ∼2.7 Å for NIT–protease complex vs ∼3.8
Å for apo HIV-1p).
Table 2
Distribution of Flap
Openness and Width of Eye Site of NIT–Protease MD Simulations,
Shown in Percentiles of the Population Similar to Box Plots
flap openness (Asp25 Cα–Ile50 Cα) (Å)
2.5%
25.0%
50.0%
75.0%
97.5%
A (NIT)
11.0
13.7
14.8
15.8
24.4
B (none)
11.4
13.0
14.3
16.1
20.1
apo
10.0
11.9
15.1
17.3
25.7
We also observed a change in the width of the Eye
site relative to the apo HIV-1p, which can be measured by the Cα distance between Gly51 and Thr80 (Table 2). In the NIT–protease complex simulations,
the Eye site with NIT bound has a width that ranges between 11.3 and
14.4 Å and a median width of 12.8 Å, while the opposite
Eye site with no bound NIT has width between 10.6 and 13.6 Å
and a median of 12.1 Å. The two Eye sites of the apo HIV-1p MD
trajectory have a similar width distribution that ranges between 8.4
and 11.9 Å and a median width of 9.7 Å. As such, the width
of the Eye site in the NIT–protease complex simulations is
notably larger than the Eye site in the apo HIV-1p simulation (median
of 12.8 Å with NIT and 12.1 Å without NIT vs 9.7 Å
in apo HIV-1p). This demonstrates that the presence of NIT affects
the flap mobility and flap conformation through its binding to the
Eye site.
Conclusion
We have described the
discovery of a novel small molecule that likely probes the allosteric
Eye site of HIV-1p. Compound NIT, with a novel scaffold, demonstrates
an allosteric mechanism in modulating the HIV-1p proteolytic activity.
It has a mixed competitive inhibition character in the Michaelis–Menten
enzymatic kinetics, demonstrating its potential to act on the HIV-1p
through a mechanism other than competing for the active site. It is
likely that NIT modulates HIV-1p proteolytic activity through the
allosteric Eye site of the protease, as shown in the Yonetani–Theorell
experiment. MD simulations of a NIT–protease complex show that
NIT remains stably bound in the Eye site and affects the dynamics
of the β-hairpin flaps when compared to an apo HIV-1p simulation.
Moreover, compound NIT has chemical features and binding modes that
closely resemble compound 5NI bound in the Eye site, as seen by crystallography.These data support compound NIT’s ability to allosterically
modulate HIV-1p proteolytic activity through binding to the Eye site
of HIV-1p and altering its dynamics. Most importantly, this new inhibitor
is equipotent against WT and MDR HIV-1p. This new mode of inhibition
has the promise of overcoming existing clinical resistance, and we
believe this is the first small, drug-like molecule reported to do
so.
Authors: H M Berman; J Westbrook; Z Feng; G Gilliland; T N Bhat; H Weissig; I N Shindyalov; P E Bourne Journal: Nucleic Acids Res Date: 2000-01-01 Impact factor: 16.971
Authors: Ragul Gowthaman; Sven A Miller; Steven Rogers; Jittasak Khowsathit; Lan Lan; Nan Bai; David K Johnson; Chunjing Liu; Liang Xu; Asokan Anbanandam; Jeffrey Aubé; Anuradha Roy; John Karanicolas Journal: J Med Chem Date: 2015-07-10 Impact factor: 7.446
Authors: Matthew Brecher; Zhong Li; Binbin Liu; Jing Zhang; Cheri A Koetzner; Adham Alifarag; Susan A Jones; Qishan Lin; Laura D Kramer; Hongmin Li Journal: PLoS Pathog Date: 2017-05-25 Impact factor: 7.464