Amino Acid Hot Spots of Halogen Bonding: A Combined Theoretical and Experimental Case Study of the 5-HT7 Receptor

Article abstract of DOI:10.1021/acs.jmedchem.8b00828

A computational approach combining a structure-activity relationship library of halogenated and the corresponding unsubstituted ligands (called XSAR) with QM-based molecular docking and binding free energy calculations was used to search for amino acids frequently targeted by halogen bonding (hot spots) in a 5-HT₇R as a case study. The procedure identified two sets of hot spots, extracellular (D2.65, T2.64, and E7.35) and transmembrane (C3.36, T5.39, and S5.42), which were further verified by a synthesized library of halogenated arylsulfonamide derivatives of (aryloxy)ethylpiperidines. It was found that a halogen bond formed between T5.39 and a bromine atom at 3-position of the aryloxy fragment caused the most remarkable, 35-fold increase in binding affinity for 5-HT₇R when compared to the nonhalogenated analog. The proposed paradigm of halogen bonding hot spots was additionally verified on D₄ dopamine receptor showing that it can be used in rational drug design/optimization for any protein target.

Full text of DOI:10.1021/acs.jmedchem.8b00828

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Article
Amino acid hot spots of halogen bonding–a combined
theoretical and experimental case study of the 5-HT7 receptor
Rafa# Kurczab, Vittorio Canale, Grzegorz Sata#a, Pawe# Zajdel, and Andrzej J. Bojarski
J. Med. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jmedchem.8b00828 • Publication Date (Web): 06 Sep 2018
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Amino acid hot spots of halogen bonding–a
combined theoretical and experimental case study
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of the 5ꢀHT receptor
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a,*
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Rafał Kurczab , Vittorio Canale , Grzegorz Satała , Paweł Zajdel , Andrzej J. Bojarski
a
Department of Medicinal Chemistry, Institute of Pharmacology, Polish Academy of
Sciences, 12 Smętna Street, 31ꢀ343 Krakow, Poland
b
Department of Medicinal Chemistry, Jagiellonian University Medical College, 9 Medyczna
Street, 30ꢀ688 Krakow, Poland
KEYWORDS:
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Halogen bonding, drug design, 5ꢀHT R, molecular interactions, medicinal chemistry
ABSTRACT
A computational approach combining a structureꢀactivity relationship library of halogenated
and the corresponding unsubstituted ligands (called XSAR) with QMꢀbased molecular
docking and binding free energy calculations was used to search for amino acids frequently
targeted by halogen bonding (hot spots) in a 5ꢀHT R as a case study. The procedure identified
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two sets of hot spots, extracellular (D2.65, T2.64, and E7.35) and transmembrane (C3.36,
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T5.39 and S5.42), which were further verified by a synthesized library of halogenated
arylsulfonamide derivatives of (aryloxy)ethyl piperidines. It was found that a halogen bond
formed between T5.39 and a bromine atom at 3ꢀposition of the aryloxy fragment, caused the
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most remarkable, 35ꢀfold increase in binding affinity for 5ꢀHT R when compared to the
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nonhalogenated analog. The proposed paradigm of halogen bonding hot spots was
additionally verified on D dopamine receptor showing that it can be used in rational drug
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design/optimization for any protein target.
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Introduction
In the range of intermolecular interactions, halogen bonding (XB) is one of the most
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intensively investigated in recent years. Halogen bonds are ruled by the same mechanism as
hydrogen bonds, i.e., they show mostly electrostatic character and are highly directional, and
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their length is shorter than the sum of the van der Waals radii of their constituent atoms. A
halogen bond can be defined as a directional bond between a covalently bound halogen atom
(acting as a donor) and a Lewis base, the bond acceptor. It originates from the anisotropy of
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the electron density distribution around the halogen atom,
in particular from the
fundamental properties of the covalent σꢀbond between atoms in the C–X group. Halogen
atoms have five electrons occupying the p atomic orbitals of their valence shell (according to
z
molecular orbital theory) and the single valence electron of the p orbital is involved in the
creation of a covalent σꢀbond with a carbon atom. As a result, the depopulation of this orbital
opposite the C–X σꢀbond leaves a hole that partially exposes the positive nuclear charge. This
soꢀcalled σꢀhole accounts for the electropositive crown and polar flattening associated with
polarization effects (anisotropy in charge distribution), whereas the four electrons remaining
x y
in the p and p orbitals account for the electronegative ring lying perpendicular to the σꢀbond.
This arrangement leads to attractive interactions between C–X moieties and classical
hydrogen bond acceptors (Figure 1).
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Halogen bonds are strong enough to control the aggregation of organic molecules in solid,
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liquid, and gas phases and have been intensively investigated in recognition processes.
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They are also considered a new tool in materials science or a novel interaction for rational
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drug design.
Among fourteen 5ꢀhydroxytryptamine receptor (5ꢀHTR) subtypes, 5ꢀHT R is the mostly
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recently identified. It is canonically coupled to Gαs or Gα12 proteins, promoting signal
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transduction through cAMP/PKAꢀ and ERKꢀdependent pathways. Distribution studies
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revealed a correlation between the localization of 5ꢀHT R in the central nervous system
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(CNS), especially in the thalamus, hypothalamus (suprachiasmatic nucleus), hippocampus and
cerebral cortex, and its functions, suggesting an involvement in physiological
(specifically,
regulation of sleep and circadian rhythm and learning and memory processes) as well as
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pathophysiological phenomena.
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Several studies have confirmed that 5ꢀHT R agonists may
produce beneficial effects in the treatment of dysfunctional memory in neurodegenerative
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disease (e.g., Alzheimer’s disease), X fragile syndrome, ADHD, and pain.
On the other
hand, preclinical findings revealed that the genetic inactivation or pharmacological blockade
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of 5ꢀHT
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R produced an antidepressantꢀlike effect.
A large body of evidence underlines
the involvement of 5ꢀHT
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R antagonists in improving memory processes, suggesting a
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potential therapeutic benefit in the treatment of cognitive impairment in depression and the
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negative symptoms of schizophrenia.
This work presents a universal computational algorithm developed to identify the
amino acids frequently targeted by halogen bonding (called hot spots) in the 5ꢀHT R binding
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site used as a case study. The theoretical predictions were evaluated experimentally by using
newly synthetized library of halogenated arylsulfonamide derivatives of (aryloxy)ethyl
piperidines. The results confirmed the existence of amino acids preferred for halogen bonding
and provide evidence for the rational design of new bioactive molecules using halogen atoms.
Results and Discussion
Study design
A computational workflow (Figure 2) was developed to identify amino acids that
frequently form halogen bonds with ligands. In the first stage, a library containing
unsubstituted and halogenated analog(s) (called XSAR) whose affinities for 5ꢀHT R are
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available in the ChEMBL database was built. Next, a positive subset of the XSAR library
(i.e., sets showing improved activity after halogenation) was used to probe the binding site
using a combination of QMꢀbased molecular docking (i.e., quantumꢀpolarized ligand docking,
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QPLD) to multiple 5ꢀHT R homology models and binding free energy (ꢁG) calculations (i.e.,
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generalizedꢀBorn/surface area, GBSA). In the final stage, all amino acids involved in the
formation of halogen bonds that yielded higher ꢁG values for halogenated analogs than
unsubstituted structures (ꢁꢁG<0) and fulfilled the geometric criteria for halogen bonding
(both distance and σꢀhole angle) were determined.
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The 5ꢀHT R amino acid hot spots identified by using XSAR sets were further verified
by the library containing newly synthesized halogenated compounds. This library was
designed based on previously reported series of arylsulfonamide derivatives of (aryloxy)ethyl
pyrrolidines classified as 5ꢀHT R ligands. Among them, one XSAR set was identified
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(
set24). This chemotype was modified at the central amine moiety by the replacement of
pyrrolidine with piperidine. Interestingly, the initially synthesized unsubstituted
arylsulfonamide derivative of (aryloxy)ethyl piperidine (58, Figure 3) showed low affinity for
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ꢀHT R but became a good starting point for a systematic investigation of fineꢀtuning the
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effects of halogen bonding on the affinity for 5ꢀHT R through the introduction of halogen
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atoms and hydrophobic substituents.
Using XSAR sets to evaluate the role of halogen atoms in ligand–protein complexes
The search of the ChEMBL database using the developed algorithm yielded 43 XSAR
sets (all sets are provided as a supporting materials), and in 25 of these sets, halogenation
improved activity relative to the unmodified structure (i.e., Xeffect > 1.00). The docking to 5ꢀ
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HT R homology models was performed by the use of the QPLD/GBSA procedure, which
showed very good performance in reproducing halogenated ligand–receptor (L–R) complexes
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stored in the protein database (PDB). An analysis of the best docking poses for each XSAR
set showed a common interaction pattern with 5ꢀHT R, i.e., a salt bridge with D3.32 and
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hydrophobic/aromatic interactions with an aromatic cluster consisting of F6.51, F6.52, and
W6.48. Additional contacts were specific and determined by the chemotype and substituents.
The selected XSAR sets highlight different roles of halogen atoms that result in the
halogenated analogs having higher activity than the nonhalogenated analogs (Figure 3). Set8
is represented by the 3ꢀ (magenta) and 4ꢀCl (cyan) derivatives of the Nꢀbiphenylꢀ2ꢀylmethyl
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2ꢀmethoxyphenylpiperazinylalkanamide chemotype and showed an Xeffect value slightly
greater than one. The binding mode revealed that no halogen bond was formed; however, the
position change in the chlorine atom decreased (3ꢀCl, approximately 11ꢀfold and ꢁꢁG =
+
3.04 kcal/mol) and increased (4ꢀCl, approximately 1.5ꢀfold and ꢁꢁG = –0.28 kcal/mol) the
activity. This change was caused by a change on the chlorobenzene ring orientation triggered
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by a steric interaction of the chlorine atom. Compounds belonging to set14 (with a
chlorinated fragment exposed toward the extracellular part of the receptor) had only slightly
higher activity for halogenated ligand (1.1ꢀfold and ꢁꢁG = –1.81 kcal/mol) than the
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nonhalogenated analog. Set11 displayed the highest Xeffect value (97.1ꢀfold higher activity
for the halogenated derivative and ꢁꢁG = –9.15 kcal/mol), which was related to the formation
of two halogen bonds, one with the backbone carbonyl oxygen of T5.39 (distance 3.15 Å, σꢀ
hole angle = 168.5°) and one with the backbone carbonyl oxygen of S5.42 (distance 2.95 Å,
σꢀhole angle = 155.4°). The halogenated derivatives of longꢀchain 4ꢀsubstituted piperazines
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linked to a quinazoline system (set15 ) confirmed that the T5.39 is a preferred amino acid for
the creation of halogen bonds and illustrates the high geometric preferences for their
formation. The 3ꢀCl derivative showed an approximately 7ꢀfold increase in affinity (ꢁꢁG = –
4
.78 kcal/mol) as a result of the formation of halogen bonding (distance 3.22 Å and σꢀhole
angle = 157.2°); however, when the chlorine atom was switched to the 4ꢀposition, the activity
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decreased approximately 8ꢀfold from that of the nonhalogenated form (ꢁꢁG = +13.05
kcal/mol). The reason for this lower activity by the 4ꢀCl derivative is steric hindrance that
leads to the destabilization of the complex.
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Based on the analysis of the interactions of all XSAR sets with the 5ꢀHT R (Figure S2,
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Figure S3 and Table S1), it can generally be concluded that the increases in the Xeffect value
resulting from steric (the median fold is 2.1, Table S1) or hydrophobic (the median fold
change is 1.75, Table S1) interactions of the ligand with the protein were smaller than those
originating from halogen bonding interactions (the median fold change is 5.5, Table S1). On
the other hand, the decrease in the activity of halogenated derivatives (Xeffect < 1.0) was
caused by unfavorable steric interactions (the median fold change is –5.0, Table S1) or a
docking failure (the median fold change is –5.0, Table S1) of a given derivative to the
receptor model(s).
The 5ꢀHT
The QPLD/GBSA docking procedure and XSAR data were used to probe the 5ꢀHT
binding site to determine the amino acids most frequently targeted by halogen bonding. Since
the 5ꢀHT R has not been crystallized, a set of homology models built on eight templates close
to the 5ꢀHT R was used. For each template, amino acids were classified into two categories,
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R halogen bonding hot spots
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namely, the primary (i.e., those commonly forming halogen bonding) and the secondary hot
spots (less frequently engaged). For each category, halogen bonding contacts with the
carbonyl oxygens of the protein backbone or with Lewis bases in side chains were
distinguished (Figure S4). All amino acids classified as halogen bond acceptors were
averaged over all templates, and a final hypothesis was generated (Figure 4) independently for
side chains and backbone carbonyl oxygens.
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We found 2 primary and 2 secondary halogen bonding hot spots targeting the backbone
carbonyl oxygen of amino acids, and 4 primary and 2 secondary halogen bonding contacts
targeting side chains. The most frequently engaged carbonyl oxygens were those of S5.42 and
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T5.39. Interestingly, S5.42 was indicated as a primary hot spot by 7 out of 8 sets of 5ꢀHT R
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homology models (for details see Table S4) and as a secondary hot spot by the remaining set.
Additionally, T2.64 and C3.36 were indicated to form halogen bonds with carbonyl oxygens
less frequently but at a significant level. For amino acid side chains as halogen bonding
acceptors, D2.65, C3.36, S5.42 and E7.35 were indicated as primary hot spots, and T2.64 and
S6.55 were indicated as secondary XB acceptors. In this category, the role of S5.42 was
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additionally highlighted as a key anchoring point for halogen bonding in the 5ꢀHT R binding
site (indicated by almost all homology models generated, Figure S4). We previously
suggested the potential role of the C3.36 side chain in interactions with halogenated 5ꢀHT R
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ligands. However, this interaction is limited by competitive contact with the carbonyl
oxygen of S5.42 or T5.39 (the detailed analysis is in the Supporting Information, Figure S5).
Published analyses of PDB LR complexes with halogen bonds showed that the most
1
,26,27,48
frequently observed halogen bonds are halogen−carbonyl oxygen,
followed by
interactions, while side chains are only rarely targeted. Additionally, current
experimentally identified halogen bonds in L–R complexes are mostly targeted to peptide
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halogen−π
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oxygens.
Moreover, due to the anisotropy of the electron density on halogens, they may
act as hydrogen bond acceptors. Thus, halogenated ligands compete with hydrogen bond
donors (e.g., the hydroxyl groups in serine, threonine, and tyrosine), and additionally, entropic
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disadvantages stemming from side chain flexibility significantly limit the number of
effective targetable side chains. Thus, in light of these findings, we can conclude that the most
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significant halogen bond acceptor in 5ꢀHT R is the carbonyl oxygens of T5.39 and S5.42.
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Synthesis of a library of halogenated derivatives
The library used to evaluate the predicted hot spots was designed on the basis of set24,
which had been identified in the XSAR library. The synthesis of designed compounds (58–
88) was performed according to a multistep procedure reported in Scheme 1. First, the
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alkylation of the commercially available phenols 1–19 under biphasic conditions in refluxing
acetone yielded (aryloxy)ethyl bromide derivatives 20–38. Next, these alkylating agents
reacted with Bocꢀprotected 4ꢀaminopiperidine, yielding intermediates 39–57. After the
removal of the Boc group, the final arylsulfonamides 58–88 were obtained upon treatment of
primary amines with the selected arylsulfonyl chlorides.
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Evaluation of 5ꢀHT R halogen bonding hot spots using synthesized library
An analysis of the binding mode for an unsubstituted compound (58) in multiple 5ꢀHT R
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homology models showed that the phenylsulfonyl fragment was generally exposed toward the
extracellular part of the receptor, whereas the aryloxy fragment was pointing into the binding
crevice formed by helices 3, 5 and 6 (Figure 5A). Thus, the introduction of a halogen or
hydrophobic substituents into different positions in both terminal aromatic fragments allows a
systematic validation of the halogen bonding hot spots located in different parts of the binding
site (Figure 4).
At first, the ability of the extracellular fragment (i.e., D2.65, T2.64, E7.35, and C45.x50)
of the 5ꢀHT
derivatives bearing Cl, Br, and I atoms in all positions at the phenylsulfonyl fragment. Each
compound was docked to a set of 5ꢀHT R homology models using a combination of QPLD
7
R to target the halogen bonding hot spots was evaluated by docking halogenated
7
and GBSA methods. The results indicated that only 2ꢀhalogenated analogs form halogen
bonds with either the D2.65 and/or T2.64 side chains from one side or C45.x50, which is
located in the ECL2 on another side (Figure 5B). For both 3- and 4-halogenated derivatives,
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only steric/hydrophobic interactions were found (Figure 5C, D). An energetic analysis showed
that the formation of halogen bonds increased the binding free energy (depending on the
binding pose, the ꢁꢁG ranged from –4.9 to –2.1 kcal/mol) more significantly than the
steric/hydrophobic interactions found for the 3- and 4ꢀanalogs (depending on the binding
pose, the ꢁꢁG ranged from –2.8 to –0.7 kcal/mol) relative to the unsubstituted analog (58).
These findings were confirmed by binding affinity results obtained for the synthesized
derivatives (Table 1). In general, all compounds with a halogen atom in the 2ꢀposition
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displayed higher affinity for 5ꢀHT R than their 4- and 3-halogenated analogs (59 vs 62 and
64, 60 vs 63 and 65). However, for 2ꢀhalogenated derivatives, the predicted increase in
affinity with increasing size of the halogen atom was not observed, i.e., the bromine
derivative is slightly preferred over derivatives with the larger iodine and smaller chlorine.
The experimental data highlight a plateau of affinity in this series and that the type of halogen
(Cl, Br, I) has an important influence on the affinity (Xeffect).
Next, a theoretical investigation of the derivatives with 2ꢀhalogenated aryloxy
fragments targeting the remaining XB hot spots (i.e., C3.36, T5.39 and S5.42) indicated that
no halogen bonds were formed (Figure 6A) and that the increase in the binding free energy is
a result of fitting to the volume and shape of the binding crevice formed by helices 3, 5 and 6
(Figure 6B). This hypothesis led to the calculation of the molecular volume (V
m
, Table 2) for
halogens (i.e., Cl, Br, and I) as well as several hydrophobic substituents (i.e., CH
3
, CF , iꢀPr,
3
tꢀbutyl, and phenyl). The results of these theoretical investigations showed that for halogens,
the increase in the atom size causes an increase in the binding free energy; however, for
hydrophobic substituents, this correlation was not so clear and probably depends on the shape
of the substituent (e.g., substitution with the larger tꢀbutyl gained less ꢁꢁG than that with the
smaller iꢀPr substituent). Interestingly, the binding results for synthesized 2ꢀsubstituted
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derivatives showed good correlation with theoretical indications – an increase in the volume
of the halogen atom improved the affinity for 5ꢀHT R (66 vs 67 vs 68). However, for the
7
hydrophobic substituents, the increase in the affinity was not directly correlated with the
volume, and the shape of the substituent can also have important contributions. This result is
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in line with our previously reported data, in which a compound with a methyl group
3
(
V = 1070.5 bohr /mol) displayed lower affinity than compounds with the sterically hindered
m
isopropyl and phenyl analogs (69 vs I and II, K = 534, and 36 and 45 nM, respectively).
i
Molecular modeling showed that the 3ꢀhalogenated derivatives can form halogen bonds and
adopt three orientations in the binding site (the same result was identified in an analysis of the
XSAR sets, see Figure S4), each being stabilized via halogen bonding (Figure 6C). The
binding free energy calculations indicated that the most preferred orientation is with these
derivatives halogen bonding with T5.39 (∆∆G = –4.84 kcal/mol), followed by S5.42 (∆∆G =
–3.20 kcal/mol) and C3.36 (∆∆G = –1.98 kcal/mol). In contrast, the presence of hydrophobic
substituents at the 3ꢀposition significantly decreased the binding free energy from the value in
the corresponding 2ꢀanalogs, which resulted from steric hindrances obstructing the ligand
from adopting the optimal position in the binding site. The binding of synthesized 3ꢀanalogs
revealed, however, that only the 3ꢀBr derivative (73) exhibited high affinity (K = 41 nM,
i
Xeffect = 34.6). Interestingly, in contrast to the theoretical predictions, experimental data of
this series of halogenated derivatives also indicated a plateau of affinity. Theoretical
predictions for hydrophobic substituents in the 3ꢀposition were in line with experimental
results, as these compounds showed substantially lower affinity than 2ꢀanalogs.
Finally, as docking results for 4ꢀsubstituted derivatives indicated unfavorable steric
interactions (positive ꢁꢁG), only two 4ꢀhalogenated derivatives (Cl and Br) were synthesized.
7
Indeed, the 5ꢀHT R affinity for 4ꢀCl and 4ꢀBr derivatives of 58 was significantly lower than
that of the parent structure (Xeffect = 0.6 and 0.4, respectively).
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Additionally, the interaction sphere plotted onto the backbone carbonyl oxygen of T5.39 was
used to explain the decrease in activity upon changing the location of the bromine atom in the
aryloxy fragment (Figure 6D). The generated interaction sphere confirmed that the Br atom in
the 3ꢀposition lies within the energetically favorable region of the sphere and the Br atoms in
the 2ꢀ and 4ꢀposition were outside the sphere, ruling out the formation of halogen bonds.
These experimental data are consistent with the calculated binding free energy values: the 3ꢀ
Br derivative (73) showed the highest gain in the binding free energy (∆∆G = −4.84
kcal/mol), followed by the 2ꢀBr and 4ꢀBr analogs (∆∆G = –2.55 and +6.14 kcal/mol,
respectively).
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Combined effect of two halogens
Based on the theoretical and experimental results obtained for monosubstituted aryloxy
and phenylsulfonyl fragments, compound 73 (with the preferred substitution pattern at the
aryloxy fragment, i.e., 3ꢀBr) was further modified to study additive effects resulting from the
presence of another halogen atom. For this purpose, selected derivatives containing an
additional halogen atom at either the aryloxy moiety or the terminal phenylsulfonyl fragment
were investigated theoretically and then experimentally (Table 3). The theoretical
investigation showed that the introduction of an additional halogen atom generally reduced
the binding free energy of the L–R interactions (Table 3) from its value for compound 73.
Halogen bonding between the carbonyl oxygen of T5.39 and the bromine atom of the aryloxy
fragment was detected for all studied derivatives (Figure 7A–C). For the phenylsulfonyl
fragment, only the 3ꢀBr analog (86) formed a halogen bond with the D2.64 side chain or the
carbonyl oxygen of E7.35 (Figure 7B), which may be associated with the 3ꢀBr analog having
a higher binding free energy than the 2ꢀ and 4ꢀBr derivatives (84 and 88, respectively). The
binding results showed that compounds containing two halogens in the aryloxy fragment also
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had slightly lower affinity for 5ꢀHT R than their monosubstituted derivatives (82 and 83 vs 68
7
and 73, Table 3). Moreover, the addition of a halogen atom at the arylsulfonyl fragment
7
decreased the affinity for 5ꢀHT R. Interestingly, in the case of compounds with halogen atoms
placed at two terminal positions (84–88), a halogen at the 3-position at the arylsulfonyl
fragment was more favorable for binding than a halogen at either the 2ꢀ or 4ꢀpositions (85 vs
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87 and 86 vs 84 and 88), which is in line with theoretical predictions.
Insight from molecular dynamics simulations into the plateau effect
The theoretical study indicated that a halogen at only the 3ꢀposition in aryloxy fragment
had suitable geometric conditions for halogen bonding; however, experimental tests showed
that increasing the size of the halogen atom did not improve the affinity (a plateau effect). To
obtain further insight into the potential molecular mechanism of this effect, molecular
dynamics (MD) simulations for complexes of 2ꢀBr/I and 3ꢀBr/I aryloxy analogs were
performed. Because the carbonyl oxygen of T5.39 was found as a target for halogen bonding,
the distance and the σꢀhole angle between the halogen atom and carbonyl oxygen of T5.39
were extracted from the MD trajectories. The results showed (Figure 8) that in the 2ꢀposition,
both bromine and iodine have unfavorable geometric parameters for halogen bonding with
T5.39, the closest identified hot spot. For the 3ꢀposition, a majority of XB geometric
parameters extracted from MD simulations of the Br analog are clustered in a favorable
region for halogen bonding; however, in the case of iodine, a weaker halogen bond appears to
be created with T5.39 (favorable angles but larger XB distances), probably due to its large
5
6
size. Another plausible explanation of the plateau effect was provided by Lange et al., who
suggested that dispersive CHꢀX interactions can affect the negative electrostatic potential of
the halogen and thus compensate for the loss of the halogen bond. For the smaller atom
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chlorine, these effects can even overcompensate for the halogen bond, while bromine is
indifferent, and the potential repulsion of the larger iodine leads to a reduced affinity.
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Evaluation of the impact of halogen bonding on 5ꢀHT7/1AR selectivity
The impact of halogen substitution pattern on selectivity over the 5ꢀHT1AR subtype
57
(which shows a high degree of amino acid homology to 5ꢀHT
7
R ) was also investigated. The
binding data showed that structural modifications at the arylsulfonamide fragment were not
crucial for binding to 5ꢀHT R and 5ꢀHT1A R selectively. In contrast, an increase in the
7
/
7
volume of halogen at the 2ꢀposition in the aryloxy fragment improved the selectivity ratio (66
vs 67 vs 68), and these parameters are even more strongly correlated for the hydrophobic
substituents (the best selectivity was obtained for the tꢀbutyl group, S1A/7 = 50.5). Among all
3ꢀsubstituted analogs, only compound 73, with a bromine atom, exhibited a significantly high
selectivity ratio. Since molecular modeling revealed that no compound from the whole series
docked in a proper way to 5ꢀHT1AR homology models, 73 having the highest selectivity (as
well as Xeffect) can be attributed to the creation of the halogen bond with T5.39 at the 5ꢀ
HT R binding pocket. The introduction of a second halogen atom into the compound
7
generally led to moderate 5ꢀHT
7
R affinity and selectivity, and only compound 83 (2ꢀI, 5ꢀBr)
showed a further improvement in selectivity for 5ꢀHT1AR (S1A/7 = 96.4).
4
XB hot spot strategy verification on the D dopamine receptor
To validate the developed algorithm and the XB hot spot paradigm, an experimentally
solved target structure was used. The dopamine D receptor was selected because (i) it
4
belongs to the same aminergic subfamily of class A GPCRs as the 5ꢀHT R, (ii) it has a high
7
resolution crystal structure (1.962 Å), (iii) it has an appropriate number of XSAR sets to
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determine the role of halogen atoms in L–R interactions, and (iv) a halogen bond is present in
the crystallized L–R complex.
4
Application of our algorithm to D receptor ligands stored in the ChEMBL database yielded
53 XSAR sets (all sets are provided in the Supporting Information), where halogenation
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improved the activity relative to the unsubstituted structure (i.e., Xeffect > 1.00). Structural
clustering of the XSAR library indicated 14 different clusters (molecular scaffolds), whose
centroids were next used to tune the crystal structure of the D receptor conformations using
4
an inducedꢀfit docking procedure, (described in the Experimental Section, all data are
provided in the Supporting Information). Based on the analysis of the interactions of all
4
XSAR sets with a set of D receptor conformations, a different role of halogen atoms in L–R
complexes was identified (Figure S6, Figure 9). First, the most frequently targeted amino
acids by halogen bonding were identified, i.e., the primary – V5.40 (c) and the secondary –
S5.43 (c), S5.461 (c, s) and H6.55 (s). The prediction of the primary XB hot spot (V5.40) was
confirmed by a majority of XSAR sets; however, the most significant evidence came from the
4
experimental structure of the D receptor complexed with nemonapride, where aromatic
chlorine forms a halogen bond to the backbone carbonyl of V5.40 (Figure 9A, distance 3.68
Å, σꢀhole angle = 163.2°). Worthy of note were L–R complexes of XSAR sets having a
particularly high Xeffect value (Figure S6; i.e., set44 and set51) because they all contained diꢀ
Cl derivatives which formed halogen bonds with the carbonyl oxygen of V5.40 (Figure 9B,
distance 3.37 Å, σꢀhole angle = 167.4°), and with the side chain of H6.55 (Figure 9B, distance
3.19 Å, σꢀhole angle = 148.5°). Moreover, the analysis also indicated that H6.55 was
generally targeted by 2ꢀhalogenated arylꢀpiperazine/piperidine derivatives. The last two
secondary XB hot spots were less accessible for a halogenated fragment of ligands and were
detected only for several chemotypes. For instance, in the case of set53 (Figure 9C), an
approximately 39ꢀfold increase of affinity for halogenated analog can result from the
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formation of two medium halogen bonds, i.e. with the backbone of S5.43 (distance 3.56 Å, σꢀ
hole angle = 142.6°), and the side chain of S5.461 (distance 3.41 Å, σꢀhole angle = 141.3°). In
XSAR sets, which had only a slightly higher activity for halogenated analogs and no
possibility to form halogen bonds, a visual inspection revealed that the halogenated fragment
of a ligand was usually exposed toward the extracellular part of the receptor (Figure 9D).
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Conclusions
The hypothesis of certain amino acids being targeted for halogen bonding (i.e., hot
spots) was examined first in silico and then verified experimentally. For this purpose, a new
computational approach was developed to search for hot spots of halogen bonding by probing
the binding site using a structureꢀactivity relationship library containing pairs of halogenated
7
and unsubstituted ligands (soꢀcalled XSAR) with known affinity for the 5ꢀHT R. The
algorithm identified a set of primary and secondary XB hot spots located in two distinct parts
of the receptor, namely, the extracellular (including D2.65, T2.64, and E7.35) and
transmembrane parts (i.e., C3.36, T5.39 and S5.42). To verify these hypotheses, Nꢀ[1ꢀ(2ꢀ
phenoxyethyl)piperidinꢀ4ꢀyl]benzenesulfonamide was used as a molecular framework for the
generation of a library of halogenated derivatives. The rationale behind the choice of this
7
structure resulted from its low affinity for 5ꢀHT R, its having a known synthetic route
enabling the facile generation of halogenated derivatives, and its binding mode exposing the
two terminal aromatic rings toward the part of the receptor where sets of XB hot spots were
found. Notably, a complementary strategy that uses halogenꢀenriched fragment libraries
58,59
(HEFLibs) has recently been developed and used for lead discovery.
HEFLibs contain
small halogenated fragments, which as molecular probes can explore binding sites for
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favorable halogen bond interactions to identify unique binding modes (halogen bonding hot
spots).
In general, the theoretical predictions made by the developed computational approach
were in good agreement with the experimental validation. However, among all identified XB
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hot spots for 5ꢀHT R, only several were found to make an important contribution to halogen
bonding (i.e., D2.65, T2.64, and T5.39). Although S5.42 was indicated by the XSAR library
to be the most frequently targeted XB hot spot (an amino acid neighboring T5.39 and buried
deeper than it in the binding site), T5.39 had the most significant contribution to the affinity
increase for the synthesized library. A plausible explanation for this difference may result
from the molecular scaffold influencing the spatial orientations and conformational
restrictions of a ligand in the binding site; moreover, it should be emphasized that the majority
of the XSAR subsets contained a halogenated arylpiperazine fragment that was more rigid
than the aryloxyethyl fragment. The lower impact of extracellular XB hot spots than
transmembrane regions on the affinity change can be explained by the higher flexibility of the
extracellular fragment and its greater exposure to the solvent, which can lead to the creation
of weaker and less frequent XB contacts.
The detailed analysis of molecular interactions involved in the stabilization of the L–R
complex of both XSAR and synthesized libraries revealed that halogen atoms can play
different roles in the L–R interaction, i.e., they can halogen bond and provide hydrophobic
interactions and steric hindrance. The interplay between halogen bonding and
hydrophobic/steric interactions is difficult to quantify; thus, hydrophobic substituents with a
diverse range of volumes and shapes were used to verify the differences in XB vs.
hydrophobic effects. Interestingly, this approach showed that in the case where XB was
detected in L–R complexes, the affinity increase was significantly higher for derivatives
containing halogen than those containing hydrophobic substituents, and in the case where
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only steric/hydrophobic effects dominated the L–R complexes, the gain in affinity was well
correlated with the volume and shape of the substituent.
Besides the evaluation of L–R interactions with halogenated derivatives, other
important effects, i.e., the synergy of halogen bonding, the plateau of an affinity, and the
selectivity for the similar subtype receptor 5ꢀHT1AR, were considered in this study. The initial
hypothesis of halogen bonding being additive was investigated using diꢀsubstituted
derivatives targeting hot spots belonging to the different regions (i.e., extracellular and
transmembrane). Interestingly, the theoretical method indicated that two halogen bonds were
formed (86); however, probably due to induced conformational changes, the L–R complex
with 86 had a lower binding free energy than the complex with monosubstituted compound
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73, which was in line with experimental data.
A purely theoretical assumption states that halogen bonding strength increases from chlorine
to bromine to iodine; however, among derivatives with a halogen atom localized in a
favorable position to form a halogen bond (2- and 3ꢀpositions at the phenylsulfonyl and
aryloxy fragments, respectively), a plateau of affinity was reached with bromine.
Unfortunately, in both series (for aryloxy and phenylsulfonyl fragments), iodine provided no
significant increase in affinity, which means that in this system, other factors counteracted.
The results of MD simulations supported the experimental data for these findings and showed
that steric restrictions have a key impact on the stabilization of the L–R complex by halogen
bonding. Moreover, to the best of our knowledge, this report was the first use of MD
simulations to study the plateau effect in halogen bonding.
Finally, among all synthesized monohalogenated derivatives, the most selective also showed
the highest affinity gain from halogenation. Unfortunately, due to its very low affinity to the
second receptor, no coherent binding mode was obtained, and thus it cannot be concluded that
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halogen bonding in one receptor is crucial for selectivity over the second one. However, it
2
should be noted that halogen bonding was previously verified as a selectivity trigger.
Analysis of the DrugBank database for the presence of halogen atoms in drug
molecules shows that they are a frequently used modification by medicinal chemists (the
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percentages of all drug molecules containing –Cl, –Br, –I, –CH , –OCH , –iꢀPr, and –tꢀbutyl
groups are 11.1, 2.6, 1.3, 4.7, 6.3, 1.2 and 0.5%, respectively). The computational algorithm
developed and tested in this study showed a high potential to indicate the most favorable
halogen substitution position in the aromatic ring to efficiently maximize biological activity.
Thus, this algorithm might be used to rationalize synthetic protocols and to improve virtual
screening for any target.
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Experimental Section
Workflow for searching for halogen-bonding hot spots
A calculation procedure (Figure 2) was developed to identify key amino acids that
improve the activity of a ligand by participating in the formation of halogen bonding with it.
The first step was to create a library (called XSAR) containing sets, each containing an
unsubstituted molecule and all of its halogenated analogs, whose biological activity data for a
given receptor are available. Next, the XSAR sets that showed greater activity for the
halogenated derivative(s) were used to probe the binding site using QMꢀbased molecular
docking and the binding free energy (ꢁG) calculations. In the final stage, all amino acids (XB
hot spots) involved in the formation of halogen bonding contacts that resulted in greater ꢁG
values for halogenated analogs than for their corresponding unsubstituted structure and
fulfilled the geometric criteria for halogen bonding (both in terms of distance and σꢀhole
angle) were identified.
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The JChem Suite v17.23.0 and MayaChemTools v9 libraries for computational drug
discovery were used.
Generation of structure-activity relationship datasets for halogenated analogs (XSAR)
Compounds whose activity for 5ꢀHT R had been determined were fetched from the
7
40
ChEMBL v22 database. However, only molecules whose activities were quantified by K
i
,
pK , IC50 or pIC50 and had been tested in human protein assays were taken into account. Next,
i
an algorithm was developed and used to find all pairs containing halogenated structures and
their corresponding unsubstituted structures (a detailed description of the algorithm is in the
Supporting Information, Figure S1). To describe the influence of halogenation on the
biological activity of the unsubstituted (parent) molecule, the Xeffect parameter was
calculated as a ratio of parent compound to its halogenated derivative activity. Xeffect values
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between 0 and 1 denote the negative influence of halogenation (a decrease in the activity upon
halogenation), whereas values higher than 1 mean that the activity increased after halogen
substitution. To visualize the collected XSAR data, an R script was prepared and used to
generate a heat matrix. For individual XSAR subsets, the influence of halogenation (both the
type of halogen and the place of substitution) was represented by a field whose spectrum of
colors (purple to blue to red) were assigned to denote increases in the Xeffect level. The field
was black when the Xeffect had been decreased by halogenation. The columns of the XSAR
matrix indicate the Xeffect value of the halogenation type in the aromatic ring. A single row
shows the Xeffect value for a given substitution position in the aromatic ring; however, if an
XSAR set contains more than one halogenation position, the halogenation at each position
was written in a separate row.
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Homology modeling of 5-HT
7
R
Building of homology models. The sequence of the human 5ꢀHT
7
receptor (ID: P34969) was
obtained from the UniProtKB/SwissꢀProt database. Homology models of the 5ꢀHT receptor
were built based on class A GPCR crystal structures retrieved from the Protein Data Bank
Table S2, Similarity/identity scores before sequences are shown in Figure S7). Sequences of
62
7
(
the modeled receptor and selected templates were aligned manually (Figure S8) using
Accelrys Discovery Studio v3.0, making sure that the most conserved amino acids in each
helix and motifs characteristic for class A GPCRs were in equivalent positions. Ranges of
helices were determined on the basis of crystal structures; loop regions were modeled, but not
refined. For each aligned template, a series of 200 models were generated using Modeller 9v8
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64,65
software employing an approach previously utilized in our laboratory.
Validation. The modeled structures were validated using a flexible ligand docking method
(performed using Glide software in XP precision mode) and enrichment calculations. Sets of
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ligands with known activities (K 5ꢀHT < 100 nM) and inactivities (K 5ꢀHT > 1000 nM)
i
7
i
7
40
were retrieved from the ChEMBL database (version 22). All active compounds were
hierarchically clustered using Moldprint2D, the Tanimoto metric and the Complete Cluster
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Linking Method implemented in Canvas v2.0. The centroid was selected from each cluster
0
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containing more than two members. Finally, all centroids of active compounds (121 for 5ꢀ
HT R) and the whole set of inactive compounds (1634) constituted the input for docking. The
7
6
7
3ꢀdimensional structures of the synthesized compounds were prepared using LigPrep v3.0
6
8
and the appropriate ionization states at pH = 7.4±1.0 were assigned using Epik v2.8. Protein
Preparation Wizard was used to assign the bond orders, check for steric clashes and assign
appropriate amino acid ionization states for each receptor model. The receptor grids were
69
generated (the OPLS3 force field ) by centering the grid box of the size of 12 Å on the
70
D3.32. Automated docking was performed using Glide v6.3 at the XP level with the flexible
docking option turned on.
Selection of final models. The homology models were evaluated by calculating the ROC
curve based on the Glide Score values of docked compounds (the undocked actives and
inactives were assigned as false negatives and true negatives, respectively). The final model
quality was determined by the area under the ROC curve (AUROC), based on which ten
models per template with the highest AUROC value were selected for further studies.
QM-polarized ligand docking
Quantum mechanic/molecular mechanic (QM/MM) docking was performed using the
71
QPLD implemented in Schrödinger Suite. QPLD combines the Glide docking algorithm
72,73
74
with QM/MM calculations performed by the QꢀSite program,
which uses the Jaguar and
Impact programs for the QM (ligand) and MM (protein) regions, respectively. At the initial
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stage of the QPLD procedure, the ligands were docked into a rigid protein using Glide SP.
Next, the resulting binding poses were used to calculate the partial atomic charges of the
75–78
ligand by a singleꢀpoint calculation in QꢀSite. The B3PW91 functional,
which was
79–82
applied in several theoretical studies of halogen bonding systems,
was used in conjunction
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with the ccꢀpVTZ basis set for Cl and Br and the ccꢀpVTZꢀpp basis set for Iꢀcontaining
8
3
ligands. Thus, the effect of the polarization of the charges on the ligand by the receptor was
considered in the final docking stage, where the partial charges derived from the QM
calculations of the ligand were used. During the QPLD calculations, no protein flexibility was
present; however, the ligands are treated as flexible in each of the two docking stages. The
number of returned poses per ligand in each docking stage was set to 10.
Binding free energy calculations
GBSA was used to calculate the binding free energy based on the L–R complexes
generated by the QPLD procedure. The ligand pose energies were minimized using the local
optimization feature in Prime, the flexible residue distance from a ligand pose was set to 4.0
Å, and the ligand charges obtained in the QPLD stage were used. The energies of complexes
6
9
were calculated with the OPLS3 force field and GBSA continuum solvent model. To assess
the influence of a given substituent on the binding, the ∆∆G was calculated as a difference
between the binding free energy (∆G) of a halogenated compound and its unsubstituted
(parent) analog.
Identification of halogen bonding hot spots
The docking results for the XSAR sets (which showed that the activity of the
halogenated derivatives was greater than that of the parent) were used to determine the
number of halogen bonding interactions with the side chains and carbonyl oxygen atoms of
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amino acids. Only amino acids forming a halogen bond with a distance lower than 4.00 Å, a
σꢀhole angle larger than 140° and a ∆∆G lower than 0 were accepted. For individual receptor
conformations, the halogen bonding interaction frequency (calculated as a number of halogen
bonds formed by a given amino acid divided by all halogen bonds detected overall) was
obtained to distinguish the most commonly interacting amino acids, which were depicted as
hot spots (a frequency > 40% threshold was used), and those that were involved in the
formation of the halogen bonding less frequently (20% < frequency < 40%). All other amino
acids were rejected as insignificant (mainly singletons). In the next step, the results of amino
acid classification were averaged over all the models generated on a given template using the
same thresholds as were used in the first step.
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Plotting interaction spheres for halogen bonding
To visualize (plotting interaction spheres) the possible contribution of halogen
bonding to L–R complexes, the halogen bonding web server was used (accessed 01ꢀ02ꢀ2018,
http://www.halogenbonding.com/).
Molecular dynamics simulations
MD simulations (60 ns) were performed using Schrödinger Desmond software. The
L–R complexes, selected in molecular docking analysis, were immersed into a
phosphatidylcholine (POPC, 300 K) membrane bilayer and positioned using the PPM web
84
server (http://opm.phar.umich.edu/server.php, accessed 05ꢀ12ꢀ2017). Each system was
solvated by water molecules described by the TIP4P potential, and the OPLS3 force field
parameters were used for all atoms. Additionally, 0.15 M NaCl was added to mimic the ionic
strength inside the cell.
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Optimization of the binding site of the D receptor using an induced-fit docking procedure
8
5
The dopamine 4 receptor (PDB ID: 5WIU ) was retrieved from the PDB database and
was then optimized using the inducedꢀfit docking (IFD) protocol from Schrödinger. The IFD
combines flexible ligand docking (using the Glide algorithm) and side chain refinement in
Prime. A set of halogenated analogs representing each XSAR set and exhibiting an Xeffect >
1
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1.0 was hierarchically clustered using Moldprint2D, the Tanimoto metric and the Complete
Cluster Linking Method implemented in Canvas v2.0. The centroid was selected from each
cluster and used as input for IFD. In each case, the grid box was anchored on D3.32 and
allowed on residues refinement within 12 Å from ligand. Then, for each centroid the ten topꢀ
scored L–R complexes were inspected visually to select those showing the closest compliance
85
with the common binding mode for D receptor ligands. The final validation of the selected
4
receptor conformations was performed by QPLD docking of the XSAR library, retaining at
least one receptor conformation per cluster centroid from the XSAR library.
Chemistry
Organic syntheses were carried out at ambient temperature, unless otherwise indicated.
The organic solvents used in this study (SigmaꢀAldrich and Chempur) were of reagent grade
and were used without purification. All other commercially available reagents were of the
highest purity (from SigmaꢀAldrich, Fluorochem, and TCI). All workup and purification
procedures were performed with reagentꢀgrade solvents under ambient atmosphere. Column
chromatography was performed using Merck 60 silica gel (70–230 mesh ASTM).
Mass spectra were recorded on a UPLCꢀMS/MS system consisting of a Waters
ACQUITY® UPLC® (Waters Corporation, Milford, MA, USA) coupled to a Waters TQD
mass spectrometer (electrospray ionization (ESI)ꢀtandem quadrupole). Chromatographic
separations were performed using an Acquity UPLC BEH (bridged ethyl hybrid) C18 column
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(
2.1 × 100 mm, 1.7ꢀµm particle size) equipped with an Acquity UPLC BEH C18 VanGuard
preꢀcolumn (2.1 × 5 mm, 1.7ꢀµm particle size). The column was maintained at 40°C, and
elution was performed under gradient conditions from 95% to 0% of eluent A (water/formic
acid (0.1%, v/v); eluent B was acetonitrile/formic acid (0.1%, v/v)) over 10 min at a flow rate
of 0.3 mL minꢀ1. Chromatograms were obtained using a Waters eλ PDA detector. The spectra
were analyzed in the 200–700 nm range with a 1.2 nm resolution and a sampling rate of 20
points/s. The MS detection settings of the Waters TQD mass spectrometer were as follows:
source temperature, 150°C; desolvation temperature, 350°C; desolvation gas flow rate, 600 L
hꢀ1; cone gas flow, 100 L hꢀ1; capillary potential, 3.00 kV; and cone potential, 40 V. Nitrogen
was used as both the nebulizing gas and the drying gas. The data were obtained in a scan
mode ranging from 50 to 2000 m/z at 1.0 s intervals. MassLynx V 4.1 (Waters) was used as
the data acquisition software. The UPLC/MS purity of all the final compounds was confirmed
to be 95% or higher.
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13
H NMR and C NMR spectra were obtained with a Varian BB 200 spectrometer
using TMS (0.00 ppm) as the internal standard in CDCl and were recorded at 300 and 75
3
MHz, respectively. The J values are reported in Hertz (Hz), and the splitting patterns are
designated as follows: s (singlet), br.s. (broad singlet), d (doublet), t (triplet), dd (doublet of
doublets), dt (doublet of triplets), dq (double of quartets), td (triplet of doublets), ddd (doublet
of doublet of doublets), dtd (doublet of triplets of doublets), and m (multiplet).
The general procedures used for the synthesis of intermediate and final compounds
86,87
were in accordance with previously reported methodology.
Characterization data for representative final compounds
2
-Iodo-N-[1-(2-phenoxyethyl)piperidin-4-yl]benzenesulfonamide (61)
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Brown oil, 110 mg (yield 70%) following chromatographic purification over silica gel with
CH Cl /MeOH (9/0.7 v/v); UPLC/MS purity 97%, t = 4.69, C H IN O S, MW 486.37,
2
2
R
19 23
2
3
+
1
Monoisotopic Mass 486.05, [M+H] 487.2. H NMR (300 MHz, CDCl
.71–1.80 (m, 2H), 2.11–2.21 (m, 2H), 2.74 (t, J = 5.9 Hz, 2H), 2.78–2.85 (m, 2H), 3.13–3.23
m, 1H), 4.03 (t, J = 5.6 Hz, 2H), 5.11 (d, J = 7.6 Hz, 1H), 6.83–6.89 (m, 2H), 6.90–6.97 (m,
3
) δ 1.47–1.60 (m, 2H),
1
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(
1H), 7.22–7.30 (m, 2H), 7.38–7.51 (m, 2H), 7.71–7.75 (m, 1H), 8.16 (dd, J = 7.6, 1.8 Hz,
1H).
3-Chloro-N-[1-(2-phenoxyethyl)piperidin-4-yl]benzenesulfonamide (62)
Yellow oil, 120 mg (yield 82%) following chromatographic purification over silica gel with
CH Cl /MeOH (9/0.7 v/v); UPLC/MS purity 96%, t = 4.61, C19 S, MW 394.92,
Monoisotopic Mass 394.11, [M+H] 395.1. H NMR (300 MHz, CDCl ) δ 1.43–1.58 (m, 2H),
2
2
R
2 3
H23ClN O
+
1
3
1.73–1.85 (m, 2H), 2.14–2.27 (m, 2H), 2.76 (t, J = 5.8 Hz, 2H), 2.85 (dt, J = 12.2, 3.3 Hz,
2H), 3.15–3.30 (m, 1H), 4.05 (t, J = 5.8 Hz, 2H), 4.59 (d, J = 7.7 Hz, 1H), 6.85–6.89 (m, 2H),
6.94–6.96 (m, 1H), 7.24–7.29 (m, 2H), 7.29–7.41 (m, 1H), 7.69 (ddd, J = 7.9, 1.9, 1.0 Hz,
1H), 7.78–7.83 (m, 1H), 8.03 (t, J = 1.8 Hz, 1H).
N-[1-(3-Bromophenoxyethyl)piperidin-4-yl]benzenesulfonamide (73)
Brown oil, 90 mg (yield 78%) following chromatographic purification over silica gel with
CH
Monoisotopic Mass 438.06, [M+H] 439.0. H NMR (300 MHz, CDCl
.77 (dd, J = 12.9, 4.1 Hz, 2H), 2.12–2.22 (m, 2H), 2.73 (t, J = 5.9 Hz, 2H), 2.76–2.85 (m,
2H), 3.13–3.26 (m, 1H), 4.01 (t, J = 5.9 Hz, 2H), 4.45 (d, J = 7.6 Hz, 1H), 6.77–6.82 (m, 1H),
2
Cl
2
/MeOH (9/0.7 v/v); UPLC /MS purity 97%, t
R
= 4.61, C19
H
23BrN
2
O
3
S, MW 439.37,
+
1
3
) δ 1.40–1.55 (m, 2H),
1
13
7.02–7.08 (m, 2H), 7.08–7.15 (m, 1H), 7.48–7.61 (m, 3H), 7.86–7.91 (m, 2H). C NMR (75
MHz, CDCl ) δ 29.7, 32.9, 50.5, 51.7, 56.8, 66.1, 113.0, 117.8, 122.8, 123.9, 126.8, 129.1,
30.5, 132.6, 141.2, 159.4.
3
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2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
5
5
5
5
5
5
5
5
5
5
6
N-{1-[2-(3-Tolyloxy)ethyl]piperidin-4-yl}benzenesulfonamide (75)
Brown oil, 80 mg (yield 65%) following chromatographic purification over silica gel with
CH
2
Cl
2
/MeOH (9/0.7 v/v); UPLC/MS purity 97%, t
R
= 4.03, C21
H
26
N
2
O
3
S, MW 374.50,
+
1
Monoisotopic Mass 374.17, [M+H] 361.1. H NMR (300 MHz, CDCl
3
) δ 1.45–1.56 (m, 2H),
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1.72–1.84 (m, 2H), 2.13–2.23 (m, 2H), 2.31 (s, 3H), 2.74 (t, J = 5.8 Hz, 2H), 2.83 (dt,
J = 12.1, 3.3 Hz, 2H), 3.14–3.25 (m, 1H), 4.02 (t, J = 5.8 Hz, 2H), 4.58 (br.s., 1H), 6.64–6.70
(m, 2H), 6.73–6.79 (m, 1H), 7.14 (t, J = 7.9 Hz, 1H), 7.47–7.61 (m, 3H), 7.86–7.92 (m, 2H).
N-{1-[2-(3-Isopropylphenoxy)ethyl]piperidin-4-yl}benzenesulfonamide (77)
Brown oil, 80 mg (yield 65%) following chromatographic purification over silica gel with
2 2 R 30 2 3
CH Cl /MeOH (9/0.7 v/v); UPLC/MS purity 96%, t = 4.09, C22H N O S, MW 402.55,
+
1
Monoisotopic Mass 402.20, [M+H] 403.3. H NMR (300 MHz, CDCl ) δ 1.22 (d, J = 6.5
3
Hz, 6H), 1.41–1.55 (m, 2H), 1.69–1.82 (m, 2H), 2.12–2.22 (m, 2H), 2.74 (t, J = 5.9 Hz, 2H),
2.80–2.90 (m, 3H), 3.15–3.25 (m, 1H), 4.03 (t, J = 5.6 Hz, 2H), 4.47 (br.s., 1H), 6.68 (dd,
J = 8.1, 2.3 Hz, 1H), 6.74–6.76 (m, 1H), 6.81 (d, J = 7.6, 1H), 7.18 (t, J = 7.9 Hz, 1H), 7.47–
13
7
5
.61 (m, 3H), 7.85–7.91 (m, 2H). C NMR (75 MHz, CDCl
3
) δ 23.9, 32.9, 34.2, 50.6, 52.3,
7.1, 65.7, 111.3, 113.1, 119.1, 126.9, 129.1, 129.2, 132.6, 141.2, 150.6, 158.7.
N-(1-{2-[3-(tertbutyl)phenoxy]ethyl}piperidin-4-yl)benzenesulfonamide (78)
Brown oil, 80 mg (yield 65%) following chromatographic purification over silica gel with
CH
2
Cl
2
/MeOH (9/0.7 v/v); UPLC/MS purity 97%, t
R
= 5.35, C23
H
32
N
2
O
3
S, MW 416.58,
) δ 1.29 (s, 9H), 1.44–
.56 (m, 2H), 1.73–1.83 (m, 2H), 2.12–2.22 (m, 2H), 2.75 (t, J = 5.9 Hz, 2H), 2.80–2.89 (m,
+
1
Monoisotopic Mass 416.21, [M+H] 417.3. H NMR (300 MHz, CDCl
3
1
2
6
H), 3.16–3.25 (m, 1H), 4.04 (t, J = 5.9 Hz, 2H), 4.44 (br.s., 1H), 6.65–6.70 (m, 1H), 6.90–
.92 (m, 1H), 6.98 (dd, J = 7.0, 1.8 Hz, 1H), 7.17–7.23 (m, 1H), 7.48–7.58 (m, 3H), 7.86–
7.91 (m, 2H).
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Journal of Medicinal Chemistry
1
2
3
4
5
6
7
8
9
N-[1-(4-Chlorophenoxyethyl)piperidin-4-yl]benzenesulfonamide (80)
Brown oil, 110 mg (yield 69%) following chromatographic purification over silica gel with
CH
2
Cl
2
/MeOH (9/0.7 v/v); UPLC/MS purity 97%, t
R
= 4.53, C19
H23ClN
2
O
3
S, MW 394.92,
+
1
Monoisotopic Mass 394.11, [M+H] 395.2. H NMR (300 MHz, CDCl
3
) δ 1.45–1.55 (m, 2H),
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
5
5
5
5
5
5
5
5
5
5
6
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1.73–1.83 (m, 2H), 2.12–2.22 (m, 2H), 2.73 (t, J = 5.8 Hz, 2H), 2.78–2.86 (m, 2H), 3.14–3.27
(m, 1H), 4.00 (t, J = 5.8 Hz, 2H), 4.55 (br.s., 1H), 6.71–6.80 (m, 2H), 7.32–7.39 (m, 2H),
1
3
7
6
.48–7.61 (m, 3H), 7.86–7.91 (m, 2H). C NMR (75 MHz, CDCl ) δ 32.8, 50.5, 52.3, 56.9,
3
5.4, 115.8, 125.7, 126.8, 128.7, 129.3, 132.6, 141.2, 157.23.
N-{1-[2-(3-Bromo-2-iodophenoxy)ethyl]piperidin-4-yl}benzenesulfonamide (82)
Brown oil, 120 mg (yield 73%) following chromatographic purification over silica gel with
CH Cl /MeOH (9/0.5 v/v); UPLC/MS purity 97%, t = 5.08, C H BrIN O S, MW 565.26,
2
2
R
19 22
2
3
+
1
Monoisotopic Mass 563.96, [M+H] 565.0. H NMR (300 MHz, CDCl ) δ 1.41–1.55 (m, 2H),
3
1
.77 (dd, J = 12.9, 3.5 Hz, 2H), 2.19–2.30 (m, 2H), 2.79–2.85 (m, 2H), 2.85–2.92 (m, 2H),
.10–3.26 (m, 1H), 4.07 (t, J = 5.3 Hz, 2H), 4.75 (d, J = 7.0 Hz, 1H), 6.65 (dd, J = 8.2, 1.2
3
Hz, 1H), 7.08–7.15 (m, 1H), 7.22–7.29 (m, 1H), 7.46–7.62 (m, 3H), 7.83–7.94 (m, 2H).
1
3
C NMR (75 MHz, CDCl ) δ 33.0, 50.5, 52.5, 56.6, 68.4, 94.9, 109.9, 110.0, 125.3, 126.9,
3
129.1, 130.1, 131.1, 132.6, 141.1, 159.3.
2-Bromo-N-{1-[2-(3-bromophenoxy)ethyl]piperidin-4-yl}benzenesulfonamide (84)
Brown oil, 110 mg (yield 74%) following chromatographic purification over silica gel with
CH Cl /MeOH (9/0.5 v/v); LC/MS purity 98%, t = 4.94, C19 S, MW 518.26,
Monoisotopic Mass 519.97, [M+H] 519.1. H NMR (300 MHz, CDCl ) δ 1.46–1.56 (m, 2H),
2
2
R
2 2 3
H22Br N O
+
1
3
1.70–1.80 (m, 2H), 2.10–2.20 (m, 2H), 2.72 (t, J = 5.7 Hz, 2H), 2.78–2.83 (m, 2H), 3.13–3.23
(m, 1H), 4.00 (t, J = 5.7 Hz, 2H), 5.10 (br.s., 1H), 6.77–6.81 (m, 1H), 7.02–7.08 (m, 2H),
7.09–7.15 (m, 1H), 7.39–7.51 (m, 2H), 7.73 (dd, J = 7.7, 1.5 Hz, 1H), 8.16 (dd, J = 7.7, 1.5
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