Predicting and improving the membrane permeability of peptidic small molecules

Article abstract of DOI:10.1021/jm201634q

We evaluate experimentally and computationally the membrane permeability of matched sets of peptidic small molecules bearing natural or bioisosteric unnatural amino acids. We find that the intentional introduction of hydrogen bond acceptor-donor pairs in

Full text of DOI:10.1021/jm201634q

Article
pubs.acs.org/jmc
Predicting and Improving the Membrane Permeability of Peptidic
Small Molecules
Salma B. Rafi,† Brian R. Hearn,‡ Punitha Vedantham,‡ Matthew P. Jacobson,*,† and Adam R. Renslo*,†,‡
†Department of Pharmaceutical Chemistry and ‡Small Molecule Discovery Center, University of California, San Francisco, California,
United States
ABSTRACT: We evaluate experimentally and computationally the membrane permeability of matched sets of peptidic small
molecules bearing natural or bioisosteric unnatural amino acids. We find that the intentional introduction of hydrogen bond
acceptor−donor pairs in such molecules can improve membrane permeability while retaining or improving other favorable drug-
like properties. We employ an all-atom force field based method to calculate changes in free energy associated with the transfer of
the peptidic molecules from water to membrane. This computational method correctly predicts rank order experimental
permeability trends within congeneric series and is much more predictive than calculations (e.g., clogP) that do not consider
three-dimensional conformation.
Various reports of improved membrane permeability
resulting from intramolecular hydrogen bonding have appeared
in the recent literature.1−3 For example, in a series of small
molecule neurokinin receptor antagonists, the introduction of
an HBA-bearing side chain led to notably improved
INTRODUCTION
■
Short peptides and peptidic small molecules are useful both as
probes to interrogate biological pathways and as lead
compounds for the discovery of new therapeutics. Unfortu-
nately, the utility of such molecules is often limited by poor
pharmacokinetic profiles resulting from poor membrane
permeability, low solubility, and proteolytic or metabolic
instability. Many of these undesirable features stem from
physiochemical properties that can be altered through structural
modification. The introduction of basic and/or hydrophilic
atoms generally improves solubility and reduces metabolism,
but these improvements often come at the expense of
membrane permeability. Conversely, masking hydrogen bond
donor (HBD) functions by N- or O-alkylation increases
lipophilicity and often improves permeability, but frequently
at the expense of solubility and binding affinity to the intended
biological target. Chemical strategies that can improve
membrane permeability without negatively impacting solubility
or target binding affinity are therefore of significant interest.
An attractive alternative to the permanent removal (e.g.,
alkylation) of HBD functionality is the introduction of
complementary hydrogen bond acceptor (HBA) functionality.
Through the formation of intramolecular hydrogen bonds, the
HBD and HBA atoms are effectively shielded, thereby reducing
the energetic penalty of desolvation required in moving from an
aqueous environment to a lipophilic membrane interior.
Importantly, the formation of such HBD/HBA contacts when
the peptide is within the membrane does not preclude the
adoption of very different conformations upon binding to the
intended biological target.
permeability across the blood−brain barrier in animals.4
A
recent systematic analysis of orally available drugs suggested
that those lying well outside rule-of-five chemical space (e.g.,
cyclosporine A) are often capable of forming intramolecular
hydrogen bonding interactions.5 Lokey and Jacobson recently
showed with diastereomeric cyclic peptides that those peptides
capable of forming intramolecular hydrogen bonds were more
permeable that those that cannot.3,6 These permeability trends
could be predicted de novo using an all-atom force field based
method to calculate changes in free energy (ΔGtr) associated
with the transfer of the peptides from water to membrane.2
This same computational approach has also been used to
predict the permeability of a set of approved small molecule
drugs for which experimental permeability values are available.7
Several predictive models to study permeability trends have
been reported. In the quantitative structure permeability
relationship models,8−15 statistical relationships are derived
between various molecular descriptors (molecular weight, polar
surface area, hydrogen bond donor/acceptor counts, octanol−
water partition coefficients, etc.) and the experimentally
determined permeability for a training set of compounds.
The performance of these empirical scoring models depends on
the chemical similarity of the test compounds and the training
Received: December 2, 2011
Published: March 6, 2012
© 2012 American Chemical Society
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Table 1. Experimental Permeability in MDR1-MDCK Cell Monolayers and Calculated ΔGtr and logS Values for Compounds 1−
16
set, and therefore the transferrability of such methods is an
issue. The physics-based models,16−20 on the other hand, seek
to employ the physics underlying the permeation process and
generally do not employ empirical data from a compound
training set. Physics-based models are therefore more general
and transferable to diverse set of molecules. Depending on the
particular task at hand, either of the two approaches can return
favorable results.
To more systematically explore the possible role of
intramolecular hydrogen bonding in facilitating permeability,
we designed and synthesized a set of small molecules
containing bioisosteric amino acids in which a HBA atom is
positioned within intramolecular hydrogen bonding distance
(5−6 atoms) of backbone N−H functions. Analogues
containing either HBA-bearing or unmodified amino acids
were tested for permeability by employing MDR1-MDCK cell
monolayers expressing the drug transporter P-gp. Blinded
predictions of passive permeability were made using the
previously described physics-based computational approach,7
and these could be correlated with the experimental
permeability values. Our results suggest that suitably positioned
HBA atoms can in some cases improve the membrane
permeability of peptidic small molecules without increasing
overall lipophilicity or removing otherwise important HBD
functions. Because the bioisosteric amino acids are typically less
lipophilic than their natural counterparts, this chemical strategy
can potentially afford peptidic molecules with improved
membrane permeability and solubility.
RESULTS AND DISCUSSION
■
The requisite HBA-containing amino acids (HBA-AA) were
prepared using the general approach described by Vederas for
the synthesis of β amino acids.21 Briefly, the β-lactone derived
from Cbz-L-serine was reacted with amine nucleophiles,
resulting in the formation of the desired HBA-AA and varying
amounts of undesired amide side product resulting from
reaction at the β-lactone carbonyl function. Consistent with
earlier reports,21 we found that the chemoselectivity of ring-
opening varies depending on the amine nucleophile and solvent
employed. This issue was of little practical consequence
however because only carboxylic acid containing products can
participate in the subsequent coupling reaction to afford the
desired C-terminal carboxamide or glycine nitrile analogues
(Table 1). A variety of aliphatic, anilinic, and heteroaromatic
amines participated in the ring-opening reaction to afford novel
amino acids that were converted to the final analogues 2, 4−5,
8−9, 11, and 13. The remaining analogues were prepared in a
single step from known or commercially available Cbz-
protected amino acids.
Permeability of test compound in the apical to basolateral
(A→B) and basolateral to apical (B→A) directions was
determined in MDR1-MDCK cell monolayers. The ratio of
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permeability values (the efflux ratio) provides a measure of the
extent of active transport by the drug transporter P-
glycoprotein (P-gp), which is expressed in this cell line. This
additional information is useful insofar as P-gp mediated efflux
impacts drug action, but in correlating experimental and
predicted permeability it is the Papp(A→B) value that is most
representative of intrinsic passive permeability.
In the prediction algorithm, a systematic conformational
search is first conducted for each compound and the resulting
low energy conformations clustered. The structure closest to
the geometric center of the cluster is chosen as representative
and the single-point energy is calculated in an implicit solvent
model meant to mimic chloroform (low dielectric medium to
represent membrane). The single-point energy of this same
conformation is then calculated in water. The computational
evidence suggests that treating these particular peptides with
single conformations is a reasonable approximation in most
cases (see Experimental Section). To the difference between
the membrane energy and water energy is added a
neutralization penalty calculated using the pKa values of any
titratable groups, as estimated by Epik.22 The rationale for
adding this penalty is that charged compounds permeate
through membranes much more slowly than neutral species.
The resulting value for transfer of the compound from
membrane to water (ΔGtr) is employed as a predictor of
relative permeability: lower ΔGtr values predict for higher
permeability.
Calculations of ΔGtr were performed blind of the
experimental results. A comparison of these predicted ΔGtr
values and the experimentally determined Papp(A→B) values
yielded a reasonable correlation coefficient r2 = 0.61 (Figure
1A). Accounting for the free energy cost of neutralization at pH
7.4 did improve the r2 value slightly (from 0.56 to 0.61). As a
point of comparison, correlation of the experimental Papp(A→B)
values with clogP (calculated in QikProp), molecular weight,
SASA, or HBD/HBA count, produced r2 values respectively of
0.26 (Figure 1B), 0.00007, 0.01, and 0.005 (data not shown).
Conformational sampling is an important aspect of our
prediction protocol that improves the predictive power of the
method as compared to clogP, which does not consider
conformational information. Not surprisingly, the calculated
hydrophilic surface area of the low energy conformers used in
the ΔGtr calculation was better correlated to experimental
permeability than clogP (r2 = 0.41 vs 0.26) but still inferior to
ΔGtr (Figure 1). Thus, the best predictive methods include
both conformational sampling and a measure of hydrophobicity
that depends on the three-dimensional structure. A comparison
of predicted solubility (clogS, determined in QikProp) with
ΔGtr values is also provided (Figure 2). From this plot, it is
apparent that analogues bearing HBA-AA (colored red in
Figure 2) are in general predicted to be more permeable than
unmodified comparators, while at the same time spanning a
more favorable range of clogS values.
Examining the matched analogue pairs, we see that the
measured permeability rate of leucine analogue 1 is about twice
that of its bioisostereic analogue 2; both analogues are highly
permeable and neither appears to be subject to P-gp mediated
efflux. Both experimental and computational prediction are in
agreement concerning the greater permeability of 1, despite the
fact that an intramolecular hydrogen bond is observed in the
lowest energy conformer of 2 (Table 1). The presence of an
intramolecular hydrogen bond is supported experimentally by
the observed chemical shift of the amide N−H signal, which
Figure 1. Plots correlating predicted and measured values for
compounds 1−16. (A) Experimentally derived permeabilities,
−logPe(A→B) and the calculated ΔGtr; (B) −logPe(A→B) and the
calculated value logP(oct/wat) (QikProp); (C) −logPe(A→B) versus
calculated hydrophilic surface area (QikProp) of each low energy
conformer. Data points are colored red for analogues with HBA-AA
and green for control analogues without HBA-AA. Data points are
shaped according to chemotype as follows: compounds 1−2 (square),
3−5 (circle), 6−9 (inverted triangle), 10−11 (diamond), 12−13
(triangle), 14−16 (hexagon).
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Table 2. Low Energy Conformations of Selected Analogues,
Calculated As Described in the Text and Experimental
a
Section
Figure 2. Plot of predicted solubility (clogS calculated using QikProp)
against the calculated ΔGtr values for the compounds 1−16.
Compound numbers are included alongside data points, which are
colored and shaped as in Figure 1.
falls at 7.57 ppm for 1 and 9.09 ppm for 2 (both spectra
recorded in CDCl3). Apparently, an intramolecular hydrogen
bond in 2 is not sufficient to shield the excess polar surface area,
as compared to 1, which lacks the hydrophilic nitrogen atom
present in 2. Another important factor undoubtedly is the
presence of a basic amine in 2 that would be significantly
protonated under the aqueous conditions of the permeability
assay.
A fairer comparison is that of 3 with its anilinic HBA-AA
analogues 4 and 5, neither of which should be significantly
protonated under the assay conditions. Compounds 3−5 show
very similar experimental permeability values and efflux ratios.
Consistent with this finding are the similar ΔGtr values
obtained for 3−5. Thus in the case of 3−5, a hydrophilic but
nonbasic HBA atom can be introduced (in 4 and 5) without
negatively impacting permeability. As with analogue 2, the low
energy conformers of both 4 and 5 possess the expected
intramolecular hydrogen bonding interaction. While no
significant improvement in permeability is realized in this
case, compounds 4 and 5 do possess improved clogS value as
compared to compound 3 (Table 1 and Figure 2).
Much more compelling effects were observed in the
compound set comprising tryptophan analogues 6 and 7 and
bioisosteric congeners 8 and 9. Hence compound 6 has the
lowest intrinsic permeability (A→B) in this set and also an
unfavorable efflux ratio of ∼9.0; in a separate experiment, this
compound was found to be a substrate for P-gp.23 N-
Methylation of the indole ring (compound 7) improves passive
permeability and also reduces the efflux ratio to ∼2.1. The
HBA-AA bearing analogues 8 and 9 are both more permeable
and exhibit improved efflux ratios as compared to 6. The
relative permeability of 6 as compared to 7−9 are correctly
predicted by the ΔGtr values, and the expected intramolecular
hydrogen bond is present in the low energy conformer of
indazole 9 (Table 2). The increased permeability of 9 is similar
to that achieved by N-methylation (as in 7) but is accompanied
a
Predicted intramolecular hydrogen bonds are indicated with dashed
lines.
in 9 by a superior clogS value as compared to either 6 or 7
(Table 1).
The histidine analogue 10 exhibited the poorest intrinsic
permeability of all the compounds examined and, like
tryptophan analogue 6, was subject to P-gp mediated efflux.
The isosteric pyrazole analogue 11 was >15-fold more
permeable than 10, and this large difference in Papp(A→B) values
is reflected in the divergent ΔGtr values obtained for these
analogues (8.7 and 13.0 kcal/mol, respectively). Importantly,
the dramatically improved permeability of HBA-AA bearing
analogue 11 was achieved without a significant increase in clogS
or clogP values as compared to 10.
The final set of analogues 12−16 possess a C-terminal
carboxamide function and thus possess one additional HBD not
present in 1−11. As with anilinic analogues 4 and 5, the anilinic
side chain in 13 afforded no notable improvement in
permeability over the comparator 12, and this was reflected
in similar ΔGtr values. The 2-pyridyl and 4-pyridyl regioisomers
15 and 16 present an interesting comparison as only the former
can possibly form an intramolecular hydrogen bond involving
the pyridine nitrogen atom. Indeed, 2-pyridyl analogue 15 was
both predicted and found experimentally to be more permeable
than 16. Unexpectedly, the unmodified phenylalanine com-
parator 14 was found experimentally (and also predicted) to be
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The efflux ratio (ER) was calculated using the equation:
more permeable than either 15 or 16. Inspection of the
predicted low energy conformations of 14−16 provides a
possible explanation for this result (Table 2). The low energy
conformer of 15 possesses the expected intramolecular
hydrogen bond involving the pyridine nitrogen atom, an
interaction that is not possible in its regioisomer 16. In the low
energy conformation of 14, and to a lesser degree 16, the aryl
ring is turned to face the N−H function in a putative N−H−π
interaction that might partially shield the N−H function from
solvent. In conformers 14, 15, and 16, we measure the
distances between N−H hydrogen atom and the center of the
aromatic ring to be 3.2, 3.5, and 3.4 Å, respectively, and the
angle between N, H, and the center of the ring to be 126.5°,
118.9°,121.5°, respectively. The values for compound 14 are in
agreement with the typical distance and angle for an N−H−π
interaction.24 In support of this hypothesis, we find that the
rank-order experimental permeability of 14−16 is correctly
predicted by calculating the hydrophilic surface area of these
low energy conformers.
ER = P (BA)/P (AB)
app
app
Percent recovery was calculated using the equation:
%recovery = 100 × [(V × C ) + (V × C )]/(V × C )
r
r
d
d
d
0
%total recovery = 100 × [(V × C ) + (V × C ) + (V × C )]
r
r
d
d
c
c
/(V × C )
d
0
Where Vd is the volume in the donor chambers (0.075 mL on the
apical side, 0.25 mL on the basolateral side), Cd and Cr are the final
concentrations of transport compound in donor and receiver
chambers, respectively. Cc is the compound concentration in the cell
lysate solution (μM). Vc is the volume of insert well (0.075 mL in this
assay).
Permeability determinations were performed in triplicate and are
reported as mean values. The mean total recovery was greater than
90% in both directions for all compounds tested, with the exception of
compound 7 where recovery was 85% (A→B) and 93% (B→A).
Calculation of ΔGtr values. All compounds studied in this work
were constructed using Maestro ligand building panel and they were
subsequently energy minimized using Ligprep (Schrodinger software,
version 8.5). For each of the compounds, parameters were generated
using a utility named hetgrp_ffgen (a part of Schrodinger software).
The force field was OPLS 2005.25,26 The neutralization penalty for
each of the compounds was calculated using Epik22 at pH 7.4.
Conformational sampling and calculation of all energies was done
using Protein Local Optimization Program (PLOP) using OPLS-AA
force field and the surface generalized Born implicit solvent model.27
The conformational sampling for each ligand was carried out using the
“tether pred” functionality of PLOP. This was done by systematically
varying the rotatable dihedral angles. The “overlap factor”, a criterion
defined by the user (set to 0.65, in this case) computed the distance
between two atoms divided by the sum of their radii and eliminated
any conformational clashes. The conformational search was performed
in an exhaustive fashion with a maximal resolution of 10° (36
conformations per rotatable dihedral angle). Subsequently, the
generated conformations were clustered. In this work, 400 clusters
were generated and the representative member was chosen as the one
closest to the geometric center of the cluster. The lowest energy
conformer was selected as the final conformer, and the single-point
energy was calculated in chloroform28 (low dielectric medium to
represent membrane). The single-point energy of this structure was
then calculated in water. To this difference between the membrane
energy and the water energy was added the neutralization penalty
calculated earlier using the Epik. This was the ΔG of transfer (ΔGtr) of
the compound from membrane to water. This was used as a predictor
of relative permeability within a chemical series: the lower the ΔGtr,
the higher the permeability.
Prompted by reviewer comments, we performed additional analysis
to confirm that treating the peptides described herein as single
conformations is indeed a reasonable approximation for the purposes
of the ΔGtr calculation. For example, we found that in the low
dielectric calculations the key hydrogen bonds are invariably conserved
across the lowest energy clusters of conformations. The structures
observed in these low-energy clusters differ slightly in their backbone
and side chain conformations, but the hydrogen bond is still present.
Other conformations that break these hydrogen bonds tend to be
significantly higher in energy. Thus, selection of a single (centroid)
conformation from the lowest energy cluster is justified.
While the ΔGtr calculation does not involve a conformational search
in high dielectric (water), we thought this would be an interesting
question to explore. Using the same protocol to perform a
conformational search in implicit water, we found that of the eight
analogues bearing HBA groups, six of them (2, 4, 5, 9, 11, and 15) do
possess an internal hydrogen bond in the lowest energy conformer in
water, while analogues 8 and 13 do not form the hydrogen bond in the
lowest energy conformer in water.
CONCLUSIONS
■
In conclusion, the introduction of suitably positioned hydrogen
bond acceptor functionality can in some cases improve
membrane permeability in peptidic molecules that otherwise
retain favorable clogP and clogS values. In other cases,
permeability rates are merely retained while clogP and clogS
values can be nudged into more favorable ranges. Thus, this
approach may prove useful in improving the drug-like
properties of peptidic small molecules. We advise, however,
that the approach be applied in combination with robust
conformational analysis. The all-atom force-field based method
applied herein provides accurate rank-order permeability
prediction within congeneric analogue sets and is much more
predictive than simple clogP calculations. The appropriate
shielding of hydrophilic functionality is an important factor to
consider when addressing poor membrane permeability; the
introduction of intramolecular hydrogen bonding interactions is
one viable means to achieving this end.
EXPERIMENTAL SECTION
■
MDR1-MDCK Monolayer Permeability Assay. MDR1-MDCK
cells (obtained from Piet Borst at The Netherlands Cancer Institute)
were seeded onto polyethylene membranes (PET) in 96-well BD
insert systems at 2 × 105 cells/cm2 for 4−6 days for confluent cell
monolayer formation. Test compounds were diluted with the transport
buffer (HBSS, pH 7.4) from a 10 mM stock solution to a
concentration of 2 μM and applied to the apical or basolateral side
of the cell monolayer. Permeation of the test compounds from A to B
direction or B to A direction was determined in triplicate over a 150
min incubation at 37 °C and 5% CO2 with a relative humidity of 95%.
In addition, the efflux ratio of each compound was also determined.
Test and reference compounds were quantified by LC-MS/MS
analysis based on the peak area ratio of analyte/IS.
The apparent permeability coefficient Papp (cm/s) was calculated
using the equation:
P
= (dC /dt) × V /(A × C )
r r 0
app
Where dCr/dt is the cumulative concentration of compound in the
receiver chamber as a function of time (μM/s), Vr is the solution
volume in the receiver chamber (0.075 mL on the apical side, 0.25 mL
on the basolateral side), A is the surface area for the transport, i.e.,
0.084 cm2 for the area of the monolayer, and C0 is the initial
concentration in the donor chamber (μM).
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1
Synthesis. H NMR spectra were recorded on a Varian INOVA-
separated, dried over MgSO4, filtered, and concentrated via rotary
evaporation. The resulting oil was purified by silica gel column
chromatography eluting with ethyl acetate in hexanes to provide 6.3
400 400 MHz spectrometer. Chemical shifts are reported in δ units
(ppm) relative to the residual NMR solvent peak. Coupling constants
(J) are reported in hertz (Hz). Compounds 1−6 and 8−11 were
prepared as described previously.23 All other reagents and solvents
were purchased from Aldrich Chemical or Acros Organics and used as
received. Column chromatography was carried out using a Biotage SP1
flash chromatography system and silica gel cartridges from Biotage or
Silicycle. Analytical TLC plates from EM Science (Silica Gel 60 F254)
were employed for TLC analyses. Preparative HPLC purifications
were performed using a Biotage Parallex Flex equipped with Waters
Xbridge 19 mm × 50 mm C18 5 μM OBD columns.
Compound Purity. Compounds 1−16 were judged to be of 95%
or higher purity based on analytical LC/MS analysis. LC/MS analyses
were performed on a Waters Micromass ZQ/Waters 2795 separation
module/Waters 2996 photodiode array detector system controlled by
MassLynx 4.0 software. Separations were carried out on an XTerra MS
C18 5 μm 4.6 mm × 50 mm column at ambient temperature using a
mobile phase of water−methanol containing 0.2% formic acid.
Gradient elution was employed wherein the methanol−water ratio
was increased linearly from 5 to 95% methanol over 8 min, then
maintained at 95% methanol for 1.5 min, and then decreased to 5%
methanol over 0.5 min and maintained at 5% methanol for 0.5 min.
Compound purity was determined by integrating peak areas of the
liquid chromatogram, monitored at 254 nm.
(2S)-2-{[(Benzyloxy)carbonyl]amino}-3-(1-methyl-1H-indol-
3-yl) Propanoic Acid (17). 1-Methyl-L-tryptophan (0.40 g, 1.8
mmol) was added to a suspension of NaHCO3 (0.38 g, 4.6 mmol) in
THF/water (1:2, 4 mL) at ambient temperature. The mixture was
stirred for 5 min, and then benzyl chloroformate (0.26 mL, 1.8 mmol)
was added dropwise. After stirring for 1 h, the reaction mixture
extracted three times with 15 mL of diethyl ether. The aqueous phase
was acidified to pH 2 by addition of HCl (1N), and the slurry was
extracted three times with 15 mL of ethyl acetate. The combined
organic phases were washed with 1N HCl (2 × 15 mL) and brine (25
mL). The crude mixture was dried (MgSO4), filtered, concentrated,
and the resulting residue purified by silica gel chromatography to
1
mg of the title compound (20 μmol, 40%). H NMR (400 MHz,
CDCl3) δ 7.09−7.39 (m, 10H), 5.94 (br s, 1H), 5.49 (br s, 1H), 5.34
(d, J = 7.5 Hz, 1H), 5.10 (m, 2H), 4.19 (m, 1H), 2.69 (app t, J = 7.8
Hz, 2H), 2.18 (dtd, J = 13.7, 7.9, 6.2 Hz, 1H), 1.95 (dq, J = 14.1, 7.1
Hz, 1H). MS: m/z = 313 [M + H]+.
Benzyl {(2S)-1-Amino-3-[methyl(phenyl)amino]-1-oxopro-
pan-2-yl}carbamate (13). To a solution of (2S)-2-{[(benzyloxy)-
carbonyl]amino}-3-[methyl(phenyl)amino]propanoic acid potassium
hydrogen sulfate23 (23 mg, 50 μmol) in THF (0.5 mL) were added
sequentially 1-hydroxybenzotriazole (9.5 mg, 70 μmol) and 1-ethyl-3-
[3-dimethylaminopropyl]carbodiimide hydrochloride (12 mg, 60
μmol). The mixture was stirred at ambient temperature for 10 min.
Ammonium hydroxide (30% aq, 0.2 mL) was then added, and the
reaction was stirred at ambient temperature for 2.5 days. The reaction
mixture was diluted in ethyl acetate and washed sequentially with
saturated aqueous Na2CO3, saturated aqueous NaHCO3, and brine.
The organic layer was separated, dried over MgSO4, filtered, and
concentrated via rotary evaporation. The resulting oil was purified by
silica gel column chromatography eluting with ethyl acetate in hexanes
1
to provide 6.0 mg of the title compound (18 μmol, 37%). H NMR
(400 MHz, CDCl3) δ 7.19−7.41 (m, 7H), 6.84−6.96 (m, 2H), 6.79 (t,
J = 7.1 Hz, 1H), 6.13 (br s, 1H), 5.66 (br s, 1H), 5.57 (br s, 1H), 5.11
(s, 2H), 4.44 (br m, 1H), 3.74 (br d, J = 13.7 Hz, 1H), 3.45 (dd, J =
14.5, 9.3 Hz, 1H), 2.95 (s, 3H). MS: m/z = 328 [M + H]+.
Benzyl [(2S)-1-Amino-1-oxo-3-phenylpropan-2-yl]-
carbamate (14). To a solution of N-α-Cbz-L-phenylalanine (100
mg, 0.33 mmol) in THF (2 mL) were added sequentially 1-
hydroxybenzotriazole (63 mg, 0.47 mmol) and 1-ethyl-3-[3-
dimethylaminopropyl]carbodiimide hydrochloride (77 mg, 0.40
mmol). The reaction mixture was stirred at ambient temperature for
15 min. Ammonium hydroxide (30% aq, 0.4 mL) was then added, and
the reaction was stirred at ambient temperature overnight. The
reaction was diluted in ethyl acetate and washed sequentially with
KHSO4 (10% aq), saturated aqueous Na2CO3, and brine. The organic
layer was separated, dried over MgSO4, filtered, and concentrated via
rotary evaporation. The resulting oil was purified by silica gel column
chromatography eluting with ethyl acetate in hexanes to provide 58 mg
of the title compound (0.19 mmol, 58%). 1H NMR (400 MHz,
CDCl3) δ 7.14−7.39 (m, 10H), 5.60 (br s, 1H), 5.29 (br s, 1H), 5.08
(s, 2H), 4.42 (m, 1H), 3.13 (dd, J = 13.9, 6.0 Hz, 1H), 3.04 (dd, J =
13.7, 7.3 Hz, 1H). MS: m/z = 299 [M + H]+.
Benzyl [(2S)-1-Amino-1-oxo-3-(pyridine-2-yl)propan-2-yl]-
carbamate (15). To a suspension of N-α-Cbz-3-(pyridine-2-yl)-
alanine (25 mg, 83 μmol) in THF (1 mL) was added N-methyl
morpholine (30 μL, 92 μmol). The solution was cooled in a 0 °C
water/ice bath. Isobutyl chloroformate (13 μL, 0.10 mmol) was added,
and the reaction was stirred at 0 °C for 5 min. Ammonium hydroxide
(30% aq, 0.4 mL) was then added, and the reaction was stirred at
ambient temperature for 4 h. The reaction was diluted in ethyl acetate
and washed sequentially with saturated aqueous NH4Cl, saturated
aqueous NaHCO3, and brine. The organic layer was separated, dried
over MgSO4, filtered, and concentrated via rotary evaporation. The
resulting oil was purified by silica gel column chromatography eluting
with acetone in dichloromethane to provide 6.0 mg of the title
compound (20 μmol, 24%). 1H NMR (400 MHz, CDCl3) δ 8.46 (d, J
= 4.2 Hz, 1H), 7.61 (t, J = 7.3 Hz, 1H), 7.34 (br s, 4H), 7.23 (m, 1H),
7.16 (app t, J = 5.3 Hz, 2H), 6.73 (br s, 1H), 5.35 (br s, 1H), 5.12 (d, J
= 12.5 Hz, 1H), 5.09 (d, J = 12.5 Hz, 1H), 4.64 (m, 1H), 3.34 (br d, J
= 14.7 Hz, 1H), 3.24 (dd, J = 14.8, 6.0 Hz, 1H). MS: m/z = 300 [M +
H]+.
1
afford 180 mg of the title compound (0.51 mmol, 30%). H NMR
(400 MHz, CDCl3) δ 8.69 (br s, 1 H), 7.59 (d, J = 7.87 Hz, 1 H), 7.34
(br s, 3 H), 7.19−7.31 (m, 2 H), 7.08 (m, 1 H), 6.86 (s, 1 H), 5.44 (d,
J = 7.69 Hz, 1 H), 4.94−5.18 (m, 2 H), 4.75 (m, 1 H), 3.65 (s, 3 H),
3.24−3.43 (m, 2 H). MS m/z: [M + H]+ = 352.
Benzyl N-[(1S)-1-[(Cyanomethyl)carbamoyl]-2-(1-methyl-1H-
indol-3-yl)ethyl]carbamate (7). To a solution of 17 (50 mg, 140
μmol) in DMF (0.4 mL) was added aminoacetonitrile bisulfate (44
mg, 280 μmol), [dimethylamino(triazolo[4,5-b]pyridin-3-yloxy)-
methylene]-dimethyl-ammonium hexafluorophosphate (0.108 g, 280
μmol), and N,N-diisopropylethylamine (150 μL, 280 μmol). The
reaction was stirred at ambient temperature overnight. The reaction
mixture was then poured into ethyl acetate, and the resulting organic
solution washed in succession with 1N HCl (25 mL), 50% saturated
aqueous NaHCO3 (25 mL), and brine (25 mL). The organic layer was
then dried (MgSO4), filtered, and concentrated via rotary evaporation.
The crude product was purified by preparative HPLC to afford 32 mg
of the title compound (82 μmol, 58%). 1H NMR (400 MHz, CDCl3)
δ 7.55 (d, J = 7.51 Hz, 1H), 7.18−7.38 (m, 6H), 7.08 (m, 1H), 6.89 (s,
1H), 6.33 (br s, 1H), 5.44 (br s, 1H), 5.03 (s, 2H), 4.49 (d, J = 5.1 Hz,
1H), 3.97 (dd, J = 17.3, 5.4 Hz, 1H), 3.86 (dd, J = 17.3, 5.4 Hz, 1H),
3.71 (s, 3H), 3.32 (dd, J = 14.4, 5.2 Hz, 1H), 3.13 (dd, J = 14.4, 7.8
Hz, 1H). MS: m/z = 391 [M + H]+.
Benzyl [(2S)-1-Amino-1-oxo-4-phenylbutan-2-yl]carbamate
(12). To a solution of N-α-Cbz-L-homophenylalanine (16 mg, 50
μmol) in THF (0.5 mL) were added sequentially 1-hydroxybenzo-
triazole (9.5 mg, 70 μmol) and 1-ethyl-3-[3-dimethylaminopropyl]-
carbodiimide hydrochloride (12 mg, 60 μmol). The mixture was
stirred at ambient temperature for 10 min. Ammonium hydroxide
(30% aq, 0.2 mL) was then added, and the reaction was stirred at
ambient temperature for 2.5 days. The reaction mixture was diluted in
ethyl acetate and washed sequentially with saturated aqueous Na2CO3,
saturated aqueous NaHCO3, and brine. The organic layer was
Benzyl [(2S)-1-Amino-1-oxo-3-(pyridine-4-yl)propan-2-yl]-
carbamate (16). To a solution of N-α-Cbz-3-(pyridine-4-yl)alanine
(0.25 mmol) in DMF (2.5 mL) were sequentially added 1-
hydroxybenzotriazole (36 mg, 0.27 mmol), N,N-diisopropylethyl
amine (100 μL, 0.60 mmol), and [dimethylamino(triazolo[4,5-
b]pyridin-3-yloxy)methylene]-dimethyl-ammonium hexafluorophos-
phate (103 mg, 0.271 mmol). After 10 min, NH4OH (30% aq, 0.8
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dx.doi.org/10.1021/jm201634q | J. Med. Chem. 2012, 55, 3163−3169

Journal of Medicinal Chemistry
Article
mL) was added, and the reaction was stirred overnight. The solution
was diluted in ethyl acetate and washed sequentially with water,
saturated aqueous NaHCO3, and water. The organic layer was
separated, dried over MgSO4, filtered, and concentrated via rotary
evaporation. The crude material was purified via preparative HPLC to
structure−permeability relationship analysis for a series of inhibitors
of rhinovirus replication. J. Chem. Inf. Comput. Sci. 2001, 41, 1578−
1586.
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1
provide 3.0 mg of the title compound (10 μmol, 4%). H NMR (400
MHz, CD3CN) δ 8.47 (d, J = 5.7 Hz, 2H), 7.25−7.51 (m, 7H), 6.02
(br s, 1H), 5.86 (br s, 1H), 5.04 (d, J = 12.6 Hz, 1H), 4.98 (d, J = 12.5
Hz, 1H), 4.42 (td, J = 9.1, 4.9 Hz, 1H), 3.26 (dd, J = 13.8, 4.5 Hz, 1H),
2.96 (dd, J = 13.6, 9.8 Hz, 1H). MS: m/z = 300 [M + H]+.
AUTHOR INFORMATION
Corresponding Author
■
*For M.P.J.: phone, (415) 514-9811; fax, (415) 502-4222; E-
mail, matt.jacobson@ucsf.edu. For A.R.R.: phone, (415) 514-
9698; fax, (415) 514-5407; E-mail, adam.renslo@ucsf.edu.
(13) Acharya, C.; Seo, P. R.; Polli, J. E.; MacKerell, A. D.
Computational model for predicting chemical substituent effects on
passive drug permeability across parallel artificial membranes. Mol.
Pharmaceutics 2008, 5, 818−828.
Notes
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Predicting drug absorption from molecular surface properties based on
molecular dynamics simulations. Pharm. Res. 1998, 15, 972−978.
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Guldbrandt, M.; Christensen, M. S. In silico prediction of membrane
permeability from calculated molecular parameters. J. Med. Chem.
2005, 48, 805−811.
The authors declare no competing financial interest.
ACKNOWLEDGMENTS
■
This work was supported by NIH grant R01-GM86602
(M.P.J.) and by a grant from the Sandler Foundation
(A.R.R.). We thank Drs. Siegfried Leung, Joseline Ratnam,
and Michelle Arkin for helpful conversations. M.P.J. is an
advisor to Schrodinger LLC.
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solutes and large drugs in a lipid bilayer from computer simulations.
Biochem. Biophys. Acta, Biomembr. 2005, 1718, 1−21.
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ABBREVIATIONS USED
■
HBD, hydrogen bond donor; HBA, hydrogen bond acceptor;
P-gp, P-glycoprotein; HBA-AA, amino acid containing a
hydrogen bond acceptor atom in the side chain
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