4
A. Adamska et al. / Bioorg. Med. Chem. xxx (2016) xxx–xxx
DOR) or adult male Dunkin Hartley guinea pigs (for
j
-opioid recep-
The evolution of secondary structure of the peptides along each
trajectory was analyzed with the STRIDE algorithm28 and Perl
scripts written in-house. The analysis programs of the GROMACS
5.0.4 program suite was used for the measurement of the C(1)–
tor, KOR). The opioid receptor binding affinities for MOR, DOR and
KOR were determined by radioligand competition analysis using
[3H]DAMGO, [3H][Ile5,6]deltorphin-2 and [3H]nor-BNI, respectively.
Three independent experiments for each assay were carried out in
duplicate. The data were analyzed by a nonlinear least square
regression analysis computer program Graph Pad PRISM 6.0
(Graph Pad Software Inc., San Diego, USA).
C (2)–C (3)–N(4) virtual dihedral angle and the distance between
a
a
the terminal C atoms. A bend structure was assigned when this
a
dihedral angle was between ꢁ80° and 80° and the distance was
less than 10.0 Å.29
2.3. Calcium mobilization assay
2.5. Docking studies
Chinese Hamster Ovary (CHO) cells stably co-expressing human
recombinant MOR or KOR and the C-terminally modified Gaqi5 and
The crystallographic structure of the active murine MOR (PDB
code: 5C1M)13 was used as docking target after missing side chains
were added. Dockings were performed with the Autodock 4.2 soft-
ware. Side chains in contact with the bound ligand, observed in the
crystal complex of MOR and BU72 were kept flexible as well as all
CHO cells co-expressing the human recombinant DOR receptor and
the GaqG66Di5 chimeric protein were generated as previously
described.22–24
Agonist potencies were given as pEC50 representing a negative
logarithm of the molar concentration of an agonist that produces
50% of the maximal possible effect. Concentration response curves
were fitted with the four parameter logistic nonlinear regression
model:
U, w
and v1 ligand torsions. Blind docking of morphiceptin and
derivatives 1–4 were performed using the Lamarckian genetic
algorithm in a 80 Å ꢀ 80 Å ꢀ 80 Å grid volume, large enough to
cover the whole receptor region accessible from the extracellular
side. The spacing of grid points was set at 0.375 Å and 1000 dock-
ings were done for all ligands. The resultant ligand–receptor com-
plexes were clustered and ranked according to the corresponding
binding free energies. In silico inhibitory constants were calculated
Emax ꢁ baseline
Effect ¼ baseline þ
50ꢁXÞꢂn
1 þ 10ðlogEC
according to the following equation:
DG = RTlnKi. The pool of
where X is the agonist concentration and n is the Hill coefficient.
ligand–receptor complexes was reduced by excluding the bound
states in which specific, conserved ligand–receptor interactions
observed in the crystallographic structures of the MOR com-
plexes14,15 were not present.
Ligand efficacy was expressed as intrinsic activity (a) calculated
as the Emax of the ligand to Emax of the standard agonist ratio. Curve
fittings were performed using GraphPad PRISM 6.0 (GraphPad Soft-
ware Inc., San Diego, USA).
2.4. MD simulations
3. Results and discussion
3.1. Peptide synthesis
MD simulations of compounds 1–4 were started from extended,
energy minimized geometries and executed using the GROMACS
5.0.4 program package and the AMBER ff03 force field parameter
set.25 Parameters for unnatural amino acid residues were supple-
mented from the generalized Amber force field (gAFF)26 and partial
charges were determined at the HF/6-31G(d) level using the
restrained electrostatic potential (RESP) method with the same
force field parameters as described above. Each starting structure
was immersed in a cubic box (35 Å ꢀ 35 Å ꢀ 35 Å) of pre-equili-
brated TIP3P27 water molecules. Solvent molecules were removed
from the box when the distance between any atom of the solute
and solvent molecules was less than the sum of their van der Waals
radii. Protonated N-termini of peptides were neutralized by replac-
ing solvent molecules by Cl-ions at a position with the most favor-
able electrostatic potential. All systems were then subjected to
1000 steps of steepest descent, followed by 1000 steps conjugate
gradient energy minimization with 0.001 kJ molꢁ1 convergence
criteria. In order to allow the solvent density to equilibrate,
0.5 ns NVT MD simulations at 300 K were performed while the
position of the solute was fixed in the center of the box with a force
constant of 1000 kJ molꢁ1 Å2 on each heavy atom. Subsequently,
200.5 ns NPT MD simulations were performed for the four pep-
tides, each at constant temperature (300 K) and pressure (1 bar),
with the following parameters: the time step was set to 2 fs, the
LINCS algorithm was used to constrain all bonds to their correct
lengths, temperature was regulated with the v-rescale algorithm
with a coupling constant of 0.1 ps, constant pressure was main-
tained using isotropic scaling with a relaxation constant of 1.0 ps
and 4.5 ꢀ 10ꢁ5 barꢁ1 isothermal compressibility. Non-bonded
interactions were calculated using the PME method with all cut-
off values set at 12 Å. The coordinates were stored after every
1000 steps to yield a total of 100,000 sampled conformations for
each trajectory, after excluding the first 0.5 ns of equilibration.
Peptides were synthesized by the conventional solid-phase pro-
cedure on the MBHA Rink Amide resin, using techniques for Fmoc-
protected amino acids. High resolution mass spectrometry (ESI-
MS) confirmed the identity of all synthesized peptides (see Supple-
mentary material). RP-HPLC analyses of the final purified products
indicated purity of 97% or greater (Table 1).
3.2. Opioid receptor binding studies
Opioid receptor binding affinities of peptides for the MOR, DOR
and KOR were determined by radioligand competition analysis
using [3H]DAMGO, [3H][Ile5,6]deltorphin-2 and [3H]nor-BNI,
respectively. The IC50 values were determined from logarithmic
dose–displacement curves, and the values of the inhibitory
Table 1
Physicochemical data of new opioid peptide analogs
b
No. Sequence
Formula
m/z [M+H]+a
Calcd Obsd
HPLC tR
(min)
1
2
3
4
Tyr-
Pro-NH2
Tyr-Pro-Phe-
F2Pro-NH2
Tyr-F2Pro-Phe-
F2Pro-NH2
Tyr-F2Pro-Phe-
F2Pro-NH2
D
-F2Pro-Phe-
C28H34F2N5O5 558.252 558.252 14.10
C28H34F2N5O5 558.252 558.271 14.22
C28H32F4N5O5 594.233 594.244 14.56
C28H32F4N5O5 594.233 594.247 14.99
D-
D-
a
Mass was measured using ESI-MS.
b
tR with Vydac C18 column (5
lm, 4.6 ꢀ 250 mm) using the solvent system of
0.1% TFA in water (A) and 80% acetonitrile in water containing 0.1% TFA (B) and a
linear gradient of 0–100% solvent B over 50 min, with the flow rate 1 ml/min.