Engineering strategy to improve peptide analogs: From structure-based computational design to tumor homing

Article abstract of DOI:10.1007/s10822-012-9623-5

We present a chemical strategy to engineer analogs of the tumor-homing peptide CREKA (Cys-Arg-Glu-Lys-Ala), which binds to fibrin and fibrin-associated clotted plasma proteins in tumor vessels (Simberg et al. in Proc Natl Acad Sci USA 104:932-936, 2007) w

Full text of DOI:10.1007/s10822-012-9623-5

J Comput Aided Mol Des
DOI 10.1007/s10822-012-9623-5
Engineering strategy to improve peptide analogs: from structure-
based computational design to tumor homing
•
David Zanuy Francisco J. Sayago Guillem Revilla-Lopez Gema Ballano
•
•
•
´
Lilach Agemy Venkata Ramana Kotamraju Ana I. Jimenez Carlos Cativiela
•
•
•
•
´
Ruth Nussinov April M. Sawvel Galen Stucky Erkki Ruoslahti
•
•
•
•
´
Carlos Aleman
Received: 9 October 2012 / Accepted: 4 December 2012
Ó Springer Science+Business Media Dordrecht 2012
Abstract We present a chemical strategy to engineer
analogs of the tumor-homing peptide CREKA (Cys-Arg-
Glu-Lys-Ala), which binds to fibrin and fibrin-associated
clotted plasma proteins in tumor vessels (Simberg et al. in
Proc Natl Acad Sci USA 104:932–936, 2007) with
improved ability to inhibit tumor growth. Computer mod-
eling using a combination of simulated annealing and
molecular dynamics were carried out to design targeted
replacements aimed at enhancing the stability of the bio-
active conformation of CREKA. Because this conforma-
tion presents a pocket-like shape with the charged groups
of Arg, Glu and Lys pointing outward, non-proteinogenic
amino acids a-methyl and N-methyl derivatives of Arg,
Glu and Lys were selected, rationally designed and incor-
porated into CREKA analogs. The stabilization of the
bioactive conformation predicted by the modeling for the
different CREKA analogs matched the tumor fluorescence
results, with tumor accumulation increasing with stabil-
ization. Here we report the modeling, synthetic procedures,
and new biological assays used to test the efficacy and
utility of the analogs. Combined, our results show how
studies based on multi-disciplinary collaboration can con-
verge and lead to useful biomedical advances.
Keywords Computational design ꢀ Bioactive
conformation dynamics ꢀ Tumor-homing peptide ꢀ
Peptide synthesis ꢀ Tumor growth inhibitors
Electronic supplementary material The online version of this
article (doi:10.1007/s10822-012-9623-5) contains supplementary
material, which is available to authorized users.
´
´
R. Nussinov
D. Zanuy (&) ꢀ G. Revilla-Lopez ꢀ C. Aleman (&)
Department of Human Genetics, Sackler, Medical School,
Tel Aviv University, 69978 Tel
Aviv, Israel
Department of Chemical Engineering, ETSEIB,
`
Universitat Politecnica de Catalunya, Diagonal 647,
08028 Barcelona, Spain
e-mail: david.zanuy@upc.edu
A. M. Sawvel ꢀ G. Stucky
´
C. Aleman
e-mail: carlos.aleman@upc.edu
Department of Chemistry and Biochemistry, University
of California, Santa Barbara,
CA 93106, USA
´
F. J. Sayago ꢀ G. Ballano ꢀ A. I. Jimenez ꢀ C. Cativiela
Department of Organic Chemistry, ISQCH,
University of Zaragoza–CSIC, 50009 Zaragoza, Spain
E. Ruoslahti
Cancer Center, Sanford-Burnham Medical Research Institute,
La Jolla, CA 92037, USA
L. Agemy ꢀ V. R. Kotamraju ꢀ E. Ruoslahti
Center for Nanomedicine, Sanford-Burnham Medical Research
Institute, Burnham Institute for Medical Research at UCSB,
University of California, 3119 Biology II Bldg.,
Santa Barbara, CA 93106-9610, USA
´
C. Aleman
Center for Research in Nano-Engineering, Universitat
`
Politecnica de Catalunya, Campus Sud, Edifici C,
C/Pasqual I Vila s/n, 08028 Barcelona, Spain
R. Nussinov
Basic Science Program, Center for Cancer Research
Nanobiology Program, SAIC-Frederick, Inc., NCI,
Frederick, MD 21702, USA
123

J Comput Aided Mol Des
Introduction
distinctive features in each case. The bioactive conforma-
tion is displayed in Fig. 1a and features both a b-turn motif
and strong interactions involving the side groups of Arg,
Glu and Lys. Additional MD simulations showed that this
conformation is very stable, and its pocket-like shape with
the charged groups pointing outwards allows formation of
intermolecular interactions.
The tumor-homing pentapeptide CREKA (Cys-Arg-Glu-
Lys-Asp) specifically homes to tumors by binding to fibrin
and fibrin-associated clotted plasma proteins (e.g. fibro-
nectin) in tumor vessels [1]. The peptide, which was
identified by screening phage-display libraries to discover
specific targets in tumor vessels [2], does not recognize
tumor growth in mutant mice null for fibrogen or in mice
lacking plasma fibronectin, which becomes covalently
bound to fibrin during blood clotting. In addition, CREKA
linked to amino dextran-coated superparamagnetic iron
oxide (SPIO) nanoparticles not only binds to blood and
plasma but also induces further localized tumor clotting
[1]. This amplification system enhanced the homing of the
nanoparticles in a mouse tumor model, and the tumor
imaging, without causing clotting or other obvious side
effects elsewhere in the body.
Next, we used this bioactive conformation of CREKA to
design some analogs using molecular modeling, which
were generated by replacing an amino acid in the sequence
by a non-proteinogenic counterpart [5]. Our initial aims
were to enhance the tumor imaging activity of CREKA by
stabilizing the bioactive conformation and to impart
protection against proteolytic resistance by incorporating
non-proteinogenic amino acids. The combination of the
self-amplifying homing system formed by elongated iron
oxide nanoparticles (hereafter denoted ‘‘nanoworms’’,
NWs) individually coated with CREKA and another tumor-
homing peptide allowed not only effective imaging of the
tumors but also produced extensive inhibition of tumor
growth by obstructing tumor circulation through blood
clotting. The efficacy of this theranostic nanosystem was
increased by selectively replacing some residues in CRE-
KA by their non-proteinogenic counterparts, which
increased the stability of the peptide. The CREKA analogs
substantially improved the tumor-homing efficiency and
increased the blockage of tumor vessels. Treatment of
prostate cancer mice with multiple doses of the theranostic
nanoparticles with CREKA analogs induced tumor necrosis
and significant reduction in tumor growth [5].
Recently, we determined the energy landscape and
bioactive conformation of CREKA on its own and labeled
with fluorescein (FAM), with the fluorescent dye attached
to the Cys through a flexible linker, using a multiple con-
formational search strategy based on molecular dynamics
(MD) simulations [3, 4]. Even though the straightforward
approach would have been modeling the peptide dynamics
within its targeted receptor, the lack of crystallographic
information about the receptor structure made us to follow
an alternative path. In addition to the previous simulated
conditions, we considered a system that mimicked the
peptide attached to the nanoparticle by tethering it to
the surface of spherical particles [3]. Results indicated that
the conformational profile of the REKA sequence is similar
in all simulated cases, with the Cys residue providing the
After reporting these biomedical achievements [5],
herein we describe the strategy, its rationale and the find-
ings obtained for the CREKA analogs from a chemical
Fig. 1 a Bioactive
conformation of CREKA.
b Chemical structure and name
to identify the a-methyl
(top row) and N-methyl
(bottom row) amino acids used
to replace Arg, Glu and Lys in
CREKA analogs
(a)
(b)
123

J Comput Aided Mol Des
point of view. Below, we discuss the design of the chem-
ical modifications in CREKA, the intensive modeling to
determine the energy landscape and bioactive conforma-
tions of the resulting CREKA analogs, the synthetic
methods, and the application of the modified peptides as
imaging agents. These are described in the framework of
our efforts to increase the activity of natural CREKA and
its resistance to endogenous proteases. Therefore, in order
to overcome the inexistent crystal structure of the CREKA
receptors, we use experimental binding assays to corrobo-
rate the predicted bioactivity for the different proposed
CREKA analogs.
The pocket shape and the orientation of the charged side
groups in the bioactive conformation of CREKA suggest that
the three central residues (REK) are crucial for the biological
activity of this peptide. After examining the conformational
characteristics of different families of non-coded amino
acids (i.e. a-tetrasubstituted, dehydro, N-substituted and
thio-a-amino acids), we selected the a-methyl and N-methyl
derivatives of Arg, Glu and Lys as the most appropriate for
the rational design of CREKA analogs. The name and
chemical structure of these non-coded amino acids are dis-
played in Fig. 1b.
Recent studies indicated that a-methyl a-amino acids, in
which the a-hydrogen atom has been replaced by a methyl
group, tend to overwhelmingly stabilize folded b-turn-like
secondary structures versus extended conformations
[20–23]. The incorporation of the methyl group not only
produces steric hindrance but also reduces the flexibility of
the backbone, the conformational freedom of the a-methyl
a-amino acid being more restricted than that of its natural
counterpart. Accordingly, the incorporation of a-methyl
Arg, Glu and Lys (aMeArg, aMeGlu and aMeLys, respec-
tively) is expected to enhance significantly the stability of the
bioactive conformation. On the other hand, the conforma-
tional preferences of N-methyl a-amino acids are dictated by
increased steric hindrance, which produces a destabilization
of the extended conformations, and lack of hydrogen bond
donor ability associated with the replacement of the hydro-
gen atom by a methyl group [24–26]. Therefore, replacement
of Arg and Glu by their corresponding N-methylated coun-
terparts (NMeArg and NMeGlu, respectively) in CREKA are
not expected to alter those structural features considered to
be essential for its tumor-homing activity. A different sce-
nario can be expected when N-methyl Lys (NMeLys) is
incorporated into CREKA as a Lys substitute, since the
backbone hydrogen bond of the b-turn motif is not possible
in the analog. In spite of this, we have also considered this
targeted replacement to obtain further insight into the
influence of such a hydrogen bond on the pocked-like shape
conformation of CREKA.
Rational design of chemical modifications in CREKA
Stabilization of structural motifs is made possible by spe-
cific interactions and constraints. In particular, incorpora-
tion of conformationally constrained amino acids into a
peptide has been shown to be a powerful method to confer
selectivity and stability [6–19]. Appropriate constraints
may not only promote the stability of the bioactive con-
formation with respect to other structural motifs present in
the potential energy landscape of the natural peptide, but
also reduce the entropy change during the binding to the
active site of a receptor or enzyme [14–19]. Constraints
limit the degrees of freedom, reducing the conformational
flexibility and the dynamic motion of peptide analogs prior
to their complexation. An implicit reasoning is that,
although the solvent and proteins may interact in a similar
way with the natural peptide and the constrained analogs
(i.e. no significant change in the binding enthalpy is
expected), the pre-organization required by the parent
peptide to reach the biologically active conformation
reduces its efficacy and binding affinity, resulting in a less
favorable entropy of binding.
In the bioactive conformation proposed for CREKA
(Fig. 1a), the backbone defines a b-type turn motif with a
hydrogen bond between the C=O(Cys) and N–H(Lys) and
the side chains of the central charged residues (Arg, Glu
and Lys) face the same side of the molecule forming salt
bridges. It should be noted that the turn conformation of the
backbone makes possible salt bridges between the car-
boxylate of the Glu and the positively charged side chains
of Arg and Lys. Other conformations (e.g. extended) would
place the charged side groups pointing towards opposite
sides. These salt bridges present multiple interaction pat-
terns, the atoms involved in such interactions changing
with the environment and the dynamic motion. This bio-
active conformation was identified not only for the free
peptide but also for the peptide attached to the surface of a
nanoparticle and for the peptide inserted in a phage display
protein.
Methods
Computational methods
The sequences of the six CREKA analogs investigated in
this work are: Cys-aMeArg-Glu-Lys-Ala (CRaEKA), Cys-
Arg-aMeGlu-Lys-Ala (CREaKA), Cys-Arg-Glu-aMeLys-
Ala (CREKaA), Cys-NMeArg-Glu-Lys-Ala (CRNEKA),
Cys-Arg-NMeGlu-Lys-Ala (CRENKA) and Cys-Arg-Glu-
NMeLys-Ala (CREKNA), where the superscripts a and N
refer to the a-methyl and N-methyl residues, respectively.
The energy landscape of the six peptides was examined
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J Comput Aided Mol Des
using the sampling technique previously employed for
CREKA [3], which consists of modified simulated
annealing combined with MD (SA-MD) [27, 28]. This
procedure is based on the minimization of structures gen-
erated in the initial and intermediate states of several SA-
MD cycles. The starting temperature is gradually reduced
during the simulation, thus allowing the system to sur-
mount energy barriers. Early studies showed that very low
energies are obtained by minimizing the structures
extracted from SA-MD processes [29, 30]. In our previous
study with CREKA [3] this sampling technique was found
to be robust when 500 structures were submitted to energy
minimization from each SA-MD cycle.
parameters taken from the AMBER libraries. Atom pair
˚
distance cutoffs were applied at 14.0 A to compute the van
der Waals and electrostatic interactions. Both temperature
and pressure were controlled by the weak coupling method,
the Berendsen thermo-barostat [34], using a time constant
for heat bath coupling and a pressure relaxation time of
1 ps. Bond lengths were constrained using the SHAKE
algorithm [35] with a numerical integration step of 2 fs.
The list of unique minimum energy conformations was
generated by comparing the 500 minimized structures pro-
vided by each cycle of modified SA-MD among themselves
and with unique minima generated in previous cycles. The
list was organized by rank ordering all the unique minimum
energy conformations found in an increasing energy, dis-
carding only those conformations that had already appeared.
Unique minimum energy conformations were identified
based on the virtual dihedral angles which characterize the
peptide backbone conformation and on hydrogen-bond and
salt-bridge interactions. Five virtual dihedral angles were
defined considering the a-carbon atoms of the five residues
and the end capping atoms. The existence of interactions
was accepted on the basis of the following geometric cri-
teria: (a) for salt bridges: distance between the centers of the
The sulfhydryl group of the Cys residue was used to
tether each analog to a surface formed by 100 spherical
particles, which were distributed in a 10 9 10 square
2
˚
˚
(47.5 A ), with van der Waals parameters [R = 2.35 A and
e = 0.90 kcal/mol] and without electric charge. The whole
system, which is identical to that used for mimicking
CREKA bound to the surface of a nanoparticle, was placed
˚
in the center of a cubic simulation box (a = 47.5 A) filled
with at least 3,217 explicit water molecules, that were
represented using the TIP3 model [31]. One negatively
charged chloride and two positively charged sodium atoms
were added to the simulation box to reach electric neu-
trality (net charges were considered for side groups of the
a-methyl and N-methyl Arg, Lys and Glu at neutral pH).
Prior to the production cycles with the modified SA-
MD, the simulation box was equilibrated. Each system was
initially minimized to relax the conformational and struc-
tural tensions using the conjugate gradient method. After
this, 0.5 ns of NVT-MD at 500 K were used to homoge-
neously distribute the solvent and ions in the box. Next,
0.5 ns of NVT-MD at 298 K (thermal equilibration) and
0.5 ns of NPT-MD at 298 K (density relaxation) were run.
The last snapshot of the NPT-MD was used as the starting
point for the conformational search process. This initial
structure was quickly heated to 900 K at a rate of 50 K/ps
to force the molecule to jump to a different region of the
conformational space. Along 10 ns, the 900 K-structure
was slowly cooled to 500 K at a rate of 1 K per 25 ps.
A total of 500 structures were selected and subsequently
minimized during the first cycle of modified SA-MD. The
minimization process was performed under the same sim-
ulation conditions, i.e., using the existing water box. The
resulting minimum energy conformations were stored in a
rank-ordered library of low energy structures. The lowest
energy minimum generated in a modified SA-MD cycle
was used as the starting conformation of the next cycle.
The 100 spherical particles used to construct the surface
were kept fixed at the initial positions in all MD simula-
tions and energy minimizations. The energy was calculated
using the AMBER force-field [32, 33], with the required
˚
interacting groups shorter than 4.50 A; (b) for hydrogen
˚
bonds: HꢀꢀꢀO distance shorter than 2.50 A and \N–HꢀꢀꢀO
angle higher than 120.0°. Two structures were considered
different when differing in at least one of their virtual
dihedral angles by more than 60° or in at least one of the
above interactions. All the structures classified as different
were subsequently clustered based on salt bridges and
hydrogen bonds.
Amino acids synthesis
All non-proteinogenic amino acids were prepared as opti-
cally pure L enantiomers suitably protected for use in Fmoc-
based solid-phase peptide synthesis. The N-methyl amino
acids were prepared following reported procedures [36–39],
they are also commercially available. The oxazolidinone
used as starting material for the synthesis of a-methyl amino
acids was obtained from Z-D-Ala-OH as described by Akaji
et al. [40]. All synthetic intermediates provided satisfactory
physical and spectroscopic data. Melting points were
determined on a Gallenkamp apparatus. Optical rotations
were measured at room temperature using a JASCO P-1020
polarimeter. High-resolution mass spectra were obtained on
a Bruker Microtof-Q spectrometer. IR spectra were regis-
tered on a Nicolet Avatar 360 FTIR spectrophotometer; mmax
1
is given for the main absorption bands. H and 13C NMR
spectra were recorded on a Bruker AV-500 or AV-400
instrument at room temperature using the residual solvent
signal as internal standard; chemical shifts (d) are expressed
in ppm and coupling constants (J) in Hz.
123

J Comput Aided Mol Des
Fmoc-(aMe)Arg(Mtr)-OH
The coupling of amino acids except Arg and Cys was done
for 5 min with 25 W microwave energy at 75 °C under
nitrogen. Fmoc-Arg(Pbf)-OH was double coupled with 0 W
microwave for 25 min and for 5 min with 20 W microwave
energy at 75 °C. All the residues on the N-terminus of the a-
methylated residues were coupled twice for 5 min with
25 W microwave energy at 75 °C under N2. All the Cys
residues were double coupled with a total of six minutes at
50 °C with 0 W and 20 W microwave energy for 2 and
4 min, respectively, each time. The protected peptide resins
were then cleaved with TFA:TIS:water (95 %:2.5 %:2.5 %)
to yield the crude peptides which were analyzed by reverse
phase (RP) HPLC using Gilson Analytical HPLC (Phe-
nomenex Jupiter Proteo, 250 9 4.60 mm column) and
purified on Gilson Semi-Preparative HPLC (Phenomenex,
Jupiter Proteo, 250 9 15 mm column). The solvents used
were A: 0.1 % TFA in water and B: 0.1 % TFA in 60 %
acetonitrile in water. The peptides were characterized by
electron spray ionization mass spectroscopy (ESI-MS) on a
Waters micromass QTOF2 tandem mass spectrometer.
Mp 116–118 °C. [a]D = ? 1.2 (c 0.41, MeOH). IR (KBr) m
3,700–2,700, 1,718, 1,641 cm-1 1H NMR (400 MHz,
.
DMSO-d6) d (major rotamer) 12.23 (bs, 1H), 7.92–7.83
(m, 2H), 7.71–7.62 (m, 2H), 7.45–7.27 (m, 4H), 7.11–6.91
(m, 2H), 6.69–6.63 (m, 1H), 6.56 (bs, 2H), 4.35–4.16 (m, 3H),
3.77 (s, 3H), 3.11–2.92 (m, 2H), 2.59 (s, 3H), 2.52 (s, 3H),
2.04 (s, 3H), 1.86–1.61 (m, 2H), 1.41–1.17 (m, 2H) over-
lapped with 1.29 (s, 3H). 13C NMR (100 MHz, DMSO-d6) d
(major rotamer) 176.10, 157.39, 156.19, 153.99, 143.88,
140.69, 137.60, 135.53, 134.58, 127.57, 127.04, 125.10,
123.49, 120.09, 111.69, 64.87, 58.49, 55.43, 46.79, 40.96,
33.55, 25.19, 23.62, 23.42, 17.99, 11.73. HRMS (ESI)
C32H39N4O7S [M ? H]?: calcd. 623.2534, found 623.2559.
Fmoc-(aMe)Glu(OtBu)-OH
Mp 85–87 °C. [a]D = ? 4.2 (c 0.41, CHCl3). IR (KBr) m
3,650–2,800, 1,724 cm-1. 1H NMR (400 MHz, DMSO-d6)
d 12.51 (bs, 1H), 7.92–7.85 (m, 2H), 7.70–7.62 (m, 2H),
7.44–7.29 (m, 4H), 7.13 (bs, 1H), 4.31–4.17 (m, 3H),
2.12–1.85 (m, 4H), 1.38 (s, 9H), 1.30 (s, 3H). 13C NMR
(100 MHz, DMSO-d6) d 175.20, 172.23, 153.87, 143.90,
140.71, 127.57, 127.02, 125.09, 120.11, 79.36, 64.87,
58.09, 46.81, 31.22, 30.47, 27.75, 23.27. HRMS (ESI)
C25H28NO6 [M - H]-: calcd. 438.1922, found 438.1923.
Biological assays
Nanoworms (NWs) and nanoworms coated with peptides
(i.e. CREKA-NWs, CRNEKA-NWs, CRENKA-NWs and
CREKaA-NWs) were prepared as described previously
[41]. Synthetic peptides labeled with fluorescein (FAM)
were injected intravenously into mice bearing B16F1
tumors, the protocol being the same as in previous work
[5]. Similarly, analyses, protocols and procedures to
examine the nanoworm biodistribution were identical to
those described in Ref. [5].
Fmoc-(aMe)Lys(Boc)-OH
Mp 75–77 °C. [a]D = ? 1.9 (c 0.62, MeOH). IR (Nujol) m
3,700–2,790, 1,707 cm-1. 1H NMR (500 MHz, DMSO-d6)
d 12.36 (bs, 1H), 7.92–7.87 (m, 2H), 7.75–7.69 (m, 2H),
7.44–7.30 (m, 5H), 6.77 (bs, 1H), 4.32–4.15 (m, 3H), 2.89
(m, 2H), 1.83–1.70 (m, 1H), 1.70–1.58 (m, 1H), 1.40–1.29
(m, 2H) overlapped with 1.37 (s, 9H), 1.32 (s, 3H),
1.25–1.10 (m, 2H). 13C NMR (100 MHz, DMSO-d6) d
175.37, 155.59, 154.80, 143.85, 140.71, 127.62, 127.07,
125.29, 120.09, 77.34, 65.25, 58.27, 46.72, 36.55, 29.77,
28.28, 27.61, 22.25, 20.53. HRMS (ESI) C27H33N2O6
[M - H]-: calcd. 481.2344, found 481.2349.
Results and discussion
The energy landscape of CREKA analogs
The evolution of the number of unique minimum energy
conformations against the number of SA-MD cycles for
CREKA and its analogs, which are compared in Fig. 2a,
indicates that the conformational search converges after
only 7 cycles. The number of unique minima is very
similar for CREKA and its a-methylated analogs (i.e.
1,323, 1,325, 1,316 and 1,310 for CREKA, CRaEKA,
CREaKA and CREKaA, respectively), whereas this num-
ber decreases by 13–22 % for the N-methylated ones (i.e.
1,038, 1,163 and 1,113 for CRNEKA, CRENKA and
CREKNA, respectively) reflecting a reduction in the con-
formational flexibility. Figure 2b indicates that the energy
distribution of the unique minima identified for CREKA is
largely influenced by the Ca- and N-methylation of the
charged residues. More specifically, the increment in the
Peptide synthesis
Peptides were synthesized on solid phase using the Fmoc/t-
Bu strategy on a microwave assisted automated peptide
synthesizer (Liberty, CEM corporation, Matthews, NC,
28105). Couplings were performed using HATU-collidine
reagent system in N,N0-dimethyl formamide (DMF) with
fivefold excess of appropriately protected amino acid
derivatives. Fmoc deprotection was performed with 5 %
piperazine in NMP containing 0.1 M HOBt with two
microwave energy cycles for 30 and 180 s at 75 °C under N2.
123

J Comput Aided Mol Des
profiles of both CREKA and CREKNA are remarkably
similar. Thus, the conformational agreement between the
two peptides extends not only to the positively charged
residues but also to the two residues located at the ends, Cys
and Ala. Indeed, the only difference affects the central Glu,
which does not seem significant.
1400 (a)
1200
1000
800
CREKA
CR EKA
CRE KA
600
CREK
A
Table 1 summarize the results of the clustering analysis
based on the presence of specific interactions (i.e. hydrogen
bonds and salt bridges). Of the 1,323 unique minima of
CREKA, 90.52 % involves a total of 3,115 specific interac-
tions (i.e. 1,198 minima with an average of 2.60 interactions
per minimum), which are distributed as follows: 57.6 % main
chainꢀꢀꢀmain chain (mc–mc) hydrogen bonds, 17.4 % side
chainꢀꢀꢀmain chain (scꢀꢀꢀmc) hydrogen bonds, 13.3 % side
chainꢀꢀꢀside chain (sc–sc) hydrogen bonds and 11.7 % sc–sc
salt bridges. According to the similarities in the interaction
pattern, the 1,198 minima with specific interactions were
categorized into 687 clusters, even though only 17 of them
contained more than 10 minima.
400
N
CR EKA
N
CRE KA
200
N
A
CREK
0
1
2
3
4
5
6
7
8
# SA-MD cycles
(b)
180
CREKA
150
120
90
CR EKA
CRE KA
CREK
A
N
CR EKA
N
CRE KA
N
A
CREK
60
Considering only the unique minima containing specific
interactions, the average number of interactions per mini-
mum in a-methyl analogs is similar to that in CREKA with
the exception of CRaEKA, which shows a higher value (i.e.
3.26 interactions per minimum). Moreover, the distribution
of interactions in such analogs also resembles that of CRE-
KA. Thus, mc–mc hydrogen bonds are the most frequent
interactions with populations ranging between 58.3 and
61.8 %. The only quantitative discrepancy between the
distributions found for the a-methylated analogs and CRE-
KA corresponds to CRaEKA, in which the population of mc-
sc is smaller than those of sc–sc salt bridges and sc–sc
hydrogen bonds. The unique minima of CRaEKA, CREaKA
and CREKaA with specific interactions are distributed in
909, 792 and 767 clusters, respectively, even though only 10,
15 and 12 clusters involve more than 10 structures. More-
over, the largest number of unique minima in a given cluster
is 34, 35 and 46 for CRaEKA, CREaKA and CREKaA,
respectively, while it was only 27 for CREKA. Although the
number of unique minimum with specific interactions in
a-methyl analogs and CREKA is very similar, the number of
clusters in CREKA is 222, 105 and 80 lower than in
CRaEKA, CREaKA and CREKaA, respectively. This fea-
ture suggests that Ca-methylation does not restrict the con-
formational flexibility or the ability to form intramolecular
interactions of the peptide.
30
0
0
5
10
15
20
25
Relative energy (kcal/mol)
Fig. 2 a Number of unique minimum energy conformations found
for CREKA and its a- and N-methyl analogs against the number of
SA-MD cycles used in the conformational search. b Distribution of
relative energies for the minimum energy conformations found for
CREKA and its analogs
steric hindrance produced by the replacement of the
hydrogen atom by a methyl group not only alters the shape
of the profile but also shifts the distribution towards lower
energy values (i.e. the highest energy bordering decreases
by about 2–6 kcal/mol).
Figure 3 compares the distribution of the virtual dihedral
angles, used to define the conformation in all the identified
unique minima, of CREKA and its Ca- and N-methyl ana-
logs. As can be seen, the conformational profiles of the three
central residues in CREKA are similar or very similar to
those obtained in CRaEKA, CREaKA, CRNEKA and
CRENKA. Incorporation of aMeLys produces some changes
in the conformational profile of the Glu residue. Thus,
although the preferences of the other four residues of CRE-
KA remain practically the same as in CREKaA, the inter-
actions required to stabilize the bioactive conformation may
be affected by such variation. On the other hand, the con-
formational profile obtained for CREKNA deserves special
attention. Even though the replacement of Lys by NMeLys
was initially expected to perturb the conformational prefer-
ences of the peptide because of the impossibility to form the
intramolecular hydrogen bond found in the bioactive b-turn
motif, i.e. (Cys)C = OꢀꢀꢀH–N(Lys), the conformational
Inspection of results derived from the clustering analysis
of N-methyl analogs reveals significant differences. In all
cases both the number of unique minima with specific
interactions (i.e. 879, 967 and 913 for CRNEKA, CRENKA
and CREKNA, respectively) and the average number of
interactions per minimum (i.e. 2.34, 2.32 and 2.20 for
CRNEKA, CRENKA and CREKNA, respectively) are
smaller in the N-methyl analogs than in the parent peptide.
123

J Comput Aided Mol Des
(a)
100
80
60
40
20
0
0-60
60-120
120-180
180-240 240-300 300-360
C
R
E
K
A
Virtual dihedral angle of residue # (º)
(b)
0-60
(c)
0-60
100
100
80
60
40
20
60-120
120-180
60-120
120-180
80
60
40
20
0
180-240 240-300 300-360
180-240 240-300 300-360
0
C
E
K
A
R
RN
Virtual dihedral angle of residue # (º)
C
E
K
A
Virtual dihedral angle of residue # (º)
100
80
60
40
20
0
100
80
60
40
20
0
0-60
60-120
120-180
0-60
60-120
120-180
180-240 240-300 300-360
180-240 240-300 300-360
EN
Virtual dihedral angle of residue # (º)
C
R
K
A
E
C
R
K
A
Virtual dihedral angle of residue # (º)
100
80
60
40
20
0
100
80
60
40
20
0
0-60
60-120
120-180
0-60
60-120
120-180
180-240 240-300 300-360
180-240 240-300 300-360
KN
C
R
E
A
C
R
E
CametK
K
A
Virtual dihedral angle of residue # (º)
Virtual dihedral angle of residue # (º)
Fig. 3 Distribution of virtual dihedral angles used to define the conformation in the unique minima obtained for: a CREKA; b Ca-methyl
CREKA analogs; and c N-methyl CREKA analogs
Moreover, the unique minima of CRNEKA, CRENKA and
CREKNA are distributed in 537, 453 and 493 clusters,
respectively, which represent a drastic decrease with
respect to the Ca-methyl analogs. Similarly, the number of
clusters with more than ten unique minima goes from 17 in
CREKA to 11, 13 and 11 in CRNEKA, CRENKA and
CREKNA, respectively. Combined, these results indicate
that N-methylation reduces significantly the conforma-
tional flexibility of the peptides and, consequently, the
variability of hydrogen bonding and salt bridges interac-
tions. On the other hand, it is worth noting that sc–sc salt
bridges are more frequent than sc–sc hydrogen bonds in the
three N-methyl analogs (Table 1), which represents a
remarkable change in the interaction pattern with respect to
CREKA and the Ca-methyl analogs. Indeed, the percentage
of sc–sc salt bridges shown by CREKNA is even larger than
that of the mc-sc hydrogen bonds. These results suggest
that the side groups of the three charged residues may
interact more favorably with the receptor in the N-methyl
analogs, especially in CREKNA, than in CREKA and the
Ca-methyl analogs.
Figure 4a shows the distribution of the backbone dihe-
dral angles in the u,w-Ramachandran map of the five
residues of CREKA considering all the minima included in
the clustered analyses, whereas Figs. 4b, c display the
distribution for the three a-methylated and N-methylated
123

J Comput Aided Mol Des
Table 1 Results of the clustering analysis for CREKA and its Ca- and N-methyl analogs (see text)
CREKA CRaEKA CREaKA CREKaA CRNEKA CRENKA CREKNA
Total number of unique minima
Number of minima with hydrogen bonds and/or salt bridges 1,198
(Nhb/sb
1,323
1,325
1,266
1,316
1,232
1,310
1,220
1,038
879
1,163
967
1,113
913
)
Number of interactions per minimum included in Nhb/sb
Number of clusters found in the Nhb/sb minima
2.60
687
17
3.26
909
10
2.73
792
15
2.65
767
12
2.34
537
11
2.32
463
13
2.20
493
11
Number of clusters with more than 10 unique minima
Percentage of main chain–main chain hydrogen bonds (%)
Percentage of main chain–side chain hydrogen bonds
Percentage of side chain–side chain hydrogen bonds (%)
Percentage of side chain–side chain salt bridges (%)
57.6
17.4
13.3
11.7
58.3
8.2
61.8
17.8
10.1
10.3
58.9
18.7
13.0
9.4
55.6
24.1
8.4
57.3
12.6
13.8
16.3
50.9
14.0
15.0
20.1
19.9
13.6
11.9
residues, respectively, as derived from the minimum
energy conformations of the corresponding analogs. The
distributions obtained for Arg, Glu and Lys are very similar
to those obtained for their a-methyl and N-methyl coun-
terparts. Thus, the substitutions engineered in this work are
not expected to damage the biological activity of CREKA.
deprotection of the amino and carboxylic acid groups and
simultaneous reduction of the double bond in the side
chain. Protection of the amino function with Fmoc under
standard conditions provided the desired amino acid,
Fmoc-aMeGlu(OtBu)-OH (9). A similar protocol was used
to transform 6 into Fmoc-aMeLys(Boc)-OH (11), which
involved an additional step to eliminate one of the Boc
side-chain protecting groups. The synthesis of aMeArg
from 7 required the introduction of a guanidinium function.
To this end, a side-chain amino moiety was first incorpo-
rated. The terminal alkene in 7 was submitted to hydrob-
oration and the hydroxyl group thus introduced was
displaced with bis(tert-butoxycarbonyl)amide. The oxazo-
lidinone ring was then cleaved under basic conditions and
the Boc groups were eliminated by acidic treatment to
yield 12, which bears a free side-chain amino function
adequate to introduce the guanidinium moiety. The latter
was accomplished by reaction with N,N0-bis(tert-butoxy-
carboyl)-N00-trifylguanidine. Subsequent replacement of
side-chain Boc protection by Mtr (4-methoxy-2,3,6-tri-
methylbenzenesulfonyl) followed by Z-to-Fmoc exchange
afforded the target amino acid, Fmoc-aMeArg(Mtr)-OH
(13).
Synthesis of non-proteinogenic amino acids
Preparation of CREKA analogs required the availability of
a-methylated and N-methylated Arg, Glu and Lys. Because
of their wide use in biochemistry and medicinal chemistry,
great efforts have been devoted to the development of
methods for the synthesis of a-methyl [42, 43] and
N-methyl [36–39, 44] a-amino acids. For the present work,
the target amino acids have been prepared in enantiome-
rically pure form (L configuration) and suitable protected
for use in solid phase peptide synthesis using Fmoc
chemistry, that is, with the main-chain amino moiety
bearing an Fmoc group and the side chain functionality
protected with an acid-labile group. Efficient procedures to
access N-methyl amino acids have been reported [36–39,
44] and were applied to synthesize those used in the present
work (they are also available from commercial sources). To
obtain a-methylated Arg, Glu, and Lys, synthetic routes
were developed using oxazolidinone 1 as a common sub-
strate (Scheme 1). This oxazolidinone [45] was prepared in
enantiomerically pure form by condensation of Z-D-Ala-
OH with benzaldehyde dimethyl acetal as described by
Akaji et al. [40] Reaction of 1 with bromide 2, 3, or 4
afforded the corresponding a-methylated oxazolidinones 5,
6, and 7 as single stereoisomers (Scheme 1), which were
used as precursors of aMeGlu, aMeLys, and aMeArg,
respectively. These synthetic intermediates bear the main-
chain amino and carboxylic acid functions masked as an
oxazolidinone while the substituent introduced in each case
can be elaborated to generate the desired side chain
(Scheme 1). Thus, catalytic hydrogenation of 5 resulted in
cleavage of the oxazolidinone ring with concomitant
Biological activity of CREKA analogs
The biological activity and resistance against proteolytic
degradation of CREKA analogs was reported in our previous
study [5]. FAM-labeled peptides incorporating a-methyl and
N-methyl analogs showed higher tumor fluorescence than
the FAM-labeled parent peptide. Quantitative comparison
with CREKA indicated that accumulation in nude mice
bearing orthotropic 22Rv1 xenograft tumors was around
threefold higher for CREKaA and CRENKA, and more than
twofold higher for CREaKA. In particular, CRNEKA was the
only analog with tumor fluorescence weaker than CREKA.
On the other hand, it was reported that the fluorescence in the
tumors 3 h after injection remained practically unaltered for
123

J Comput Aided Mol Des
Fig. 4 Ramachandran plot
distribution for: a the five
residues of CREKA; b the
aMeArg, aMeGlu and aMeLys
residues of CRaEKA, CREaKA
and CREKaA, respectively; and
c the NMeArg, NMeGlu and
NMeLys of CRNEKA,
CRENKA and CREKNA,
respectively. The unique
minimum energy conformations
were considered for each case
CREKA analogs whereas decreased 70 % for CREKA,
indicating that the stability of the analogs is remarkably
higher than that of the unmodified peptide [5].
active conformation of CREKA, which was among the 5
lowest energy conformations of the free peptide [3]. The
comparison of this specific conformation of CREKA with
the results obtained for each analog exploration would
indicate how far each analog is from the targeted confor-
mation. In the most ideal case, the lowest energy conformer
The activity prediction follows the same rational pre-
viously discussed and successfully used for other studied
potential analogs [4]: we had indirectly established the
123

J Comput Aided Mol Des
Scheme 1 Synthetic routes to
protected derivatives of
enantiopure aMeGlu, aMeLys,
and aMeArg
N
a
˚
˚
for each analog would provide a similar conformation to
the CREKA biological one. The more dissimilar the ana-
logs absolute minimum is with respect the CREKA bio-
active conformation, the lower is the chances of obtaining
an active analog. We can assess this dissimilarity on basis
of the RMSD difference between each analog absolute
minimum and the conformation that the most resembles
active conformation of CREKA. This assessment will tell
how far the targeted conformation is from the lowest
energy conformation in each studied analog [46–48]. This
strategy is reliable since all the studied conformers in this
last step for each analog belong to clusters that present a
potential energy that is bellow the margin 5 kcalꢀmol-1
from each respective absolute minimum (Fig. 2b).
(Drmsd = 0.41 A)\CREK A (Drmsd = 0.74 A)\ CR EKA
N
˚
˚
(Drmsd = 0.84 A)\CR EKA (Drmsd = 0.92 A). This order is
fully consistent with the tumor fluorescence observed for
CREKA analogs, i.e. the tumor accumulation of the peptide
increases when Drmsd decreases. Thus, the variation in
tumor accumulation determined for the different CREKA
analogs was ranked as follows: CREKaA [ CRENKA [
CREaKA [ CREKNA [ CRNEKA (biological assays were
not carried out with CRaEKA) [5]. This success allows us
to propose Drmsd as a useful parameter, which can provide a
reliable estimate of the stabilization induced in the bioac-
tive conformation.
Complementary data indicate that this molecular engi-
neering procedure helps to target tumor recognition. We
compare the efficacy of nanoworms (NWs) coated with
CREKA and different analogs homing to tumors by binding
to fibrin and fibrin-associated clotted plasma proteins in
tumor vessels. Figure 6 shows the quantification of the
fibrin(ogen) accumulation obtained for CRNEKA-NWs,
CRENKA-NWs and CREKaA-NWs, which is compared
with that of CREKA-NWs, results that are complementary to
those already shown [5]. Replacement of Glu and Lys by
NMeGlu and aMeLys, respectively, enhances clotting by
twofold, while substitution of Arg by NMeArg does not alter
this activity. Obviously, these results are less striking than
those obtained by combining CREKA analogs-NWs with
CRKDKC-NWs (i.e. clotting increased four- or even five-
times when two types of coated nanoparticles were used) [5].
Figure 5 shows the superimpositions of two selected
structures of CREKA with the lowest energy conformation
of each analog. The two structures of the parent peptide are
the lowest energy conformation (left side of each pair),
which was proposed as the bioactive conformation [3], and
the minimum energy conformation of the parent peptide
showing the highest resemblance to the lowest energy
conformation of each analog (right side of each pair). The
root mean square deviation (rmsd) between each pair of
conformations is also displayed. The parameter Drmsd
,
which is defined for each analog as the absolute difference
between the rmsd values determined for the two pairs of
superimposed structures, increases as follows: CREKaA
N
a
˚
˚
(Drmsd = 0.28 A)\CRE KA (Drmsd = 0.32 A)\CRE KA
123

J Comput Aided Mol Des
(rmsd=
(rmsd= 0.95
(rmsd= 0.85
(rmsd= 0.44
CR EKA
CRE KA
(rmsd= 0.70
(rmsd= 0.42
(rmsd= 1.96
(rmsd= 1.04
CREK A
CRNEKA
(rmsd= 0.88
(rmsd= 0.56
(rmsd= 1.68
(rmsd= 0.94
CRENKA
CREKNA
Fig. 5 Superimpositions of two selected structures of CREKA with
the lowest energy conformation of each analog: the lowest energy
conformation (left side of each pair) and the minimum energy
conformation showing the highest resemblance with each analog
(right side of each pair). The root mean square deviation (rmsd)
between each pair of conformations is also indicated
Nonetheless, they clearly indicate that many of the targeted
AAAAAAAAAA substitutions designed following this
engineering protocol improve the biological activity of
CREKA. Moreover, the substitution does not deter the
clotting, with the results being practically identical to those
obtained for CREKA-NWs.
Supplementary Material). Comparison of the binding
obtained for CREKA and CREKA-NWs with that of
CRENKA and CRENKA-NWs, respectively, shows that the
accumulation of the peptide analog in B16F1 tumors is
higher, independently of whether the peptide is presented
individually or coating nanoworms. More detailed infor-
mation about the binding affinity, homing to tumors, lack
of homing to normal organs (non-tumor tissues) was
reported in our previous work and its corresponding sup-
porting information [5], the biomedical implications of
these findings being beyond the scope of this work.
Finally, the observed improvement in the tumor delivery
observed for CREKA analogs is not due to the nanoworms
but it is an intrinsic property, related to the stabilization of
the bioactive conformation through a restriction of the
conformational space (Imaging details are provided in
123

J Comput Aided Mol Des
endorsement by the U.S. Government. This research was supported [in
part] by the Intramural Research Program of the NIH, National Cancer
Institute, Center for Cancer Research. The work developed by the
Spanish groups has been supported by MICINN and FEDER
(MAT2009-09138 and CTQ2010-17436), by the Generalitat de Ca-
talunya (research group 2009 SGR 925 and XRQTC), and Gobierno de
Aragon-FSE (research group E-40). Support for the research of C.A.
was received through the prize ‘‘ICREA Academia’’ for excellence in
research funded by the Generalitat de Catalunya. Research in the Ru-
oslahti laboratory is supported by grants from the NIH/NCI 5 P30
CA30199-28, awarded to the Sanford-Burnham Medical Research
Institute, Cancer Center, and a DOD/CDMRP grant W81XWH-10-1-
0199.
Fig. 6 Iron oxide nanoworms coated with FAM-labeled CREKA
peptide and its analogs were intravenously injected (5 mg iron per kg
body weight) into nude mice bearing orthotropic 22Rv1, human
prostate tumors. The mice had been pre-injected with Ni-liposomes to
reduce uptake by the reticulo-endothelial system. Tumors were
harvested 5 h later, and tumor sections were stained with anti-
fibrin(ogen) antibody. The stained sections were subjected to image
analysis using Scanscope to quantify fibrin(ogen)-positive areas
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