Enrico Margiotta1,2, Stephanie C C van der Lubbe1, Lucas de Azevedo Santos1,3, Gabor Paragi1,4,5, Stefano Moro2, F Matthias Bickelhaupt1,6, Célia Fonseca Guerra1,7. 1. Department of Theoretical Chemistry and Amsterdam Center for Multiscale Modeling, Vrije Universiteit Amsterdam, De Boelelaan 1083, 1081 HV Amsterdam, The Netherlands. 2. Molecular Modeling Section (MMS), Dipartimento di Scienze del Farmaco, Università di Padova, via Marzolo 5, 35131 Padova, Italy. 3. Department of Chemistry, Federal University of Lavras, CEP 37200-000 Lavras, Minas Gerais, Brazil. 4. MTA-SZTE Biomimetic Systems Research Group, Dom ter 8, 6720 Szeged, Hungary. 5. Institute of Physics, University of Pecs, Ifjusag utja 6, 7624 Pecs, Hungary. 6. Institute of Molecules and Materials, Radboud University, Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands. 7. Leiden Institute of Chemistry, Leiden University, P.O. Box 9502, 2300 RA Leiden, The Netherlands.
Abstract
Halogen bonds are highly important in medicinal chemistry as halogenation of drugs, generally, improves both selectivity and efficacy toward protein active sites. However, accurate modeling of halogen bond interactions remains a challenge, since a thorough theoretical investigation of the bonding mechanism, focusing on the realistic complexity of drug-receptor systems, is lacking. Our systematic quantum-chemical study on ligand/peptide-like systems reveals that halogen bonding is driven by the same bonding interactions as hydrogen bonding. Besides the electrostatic and the dispersion interactions, our bonding analyses, based on quantitative Kohn-Sham molecular orbital theory together with energy decomposition analysis, reveal that donor-acceptor interactions and steric repulsion between the occupied orbitals of the halogenated ligand and the protein need to be considered more carefully within the drug design process.
Halogen bonds are highly important in medicinal chemistry as halogenation of drugs, generally, improves both selectivity and efficacy toward protein active sites. However, accurate modeling of halogen bond interactions remains a challenge, since a thorough theoretical investigation of the bonding mechanism, focusing on the realisticcomplexity of drug-receptor systems, is lacking. Our systematic quantum-chemical study on ligand/peptide-like systems reveals that halogen bonding is driven by the same bonding interactions as hydrogen bonding. Besides the electrostatic and the dispersion interactions, our bonding analyses, based on quantitative Kohn-Sham molecular orbital theory together with energy decomposition analysis, reveal that donor-acceptor interactions and steric repulsion between the occupied orbitals of the halogenated ligand and the protein need to be considered more carefully within the drug design process.
Halogen
bonding (XB) is commonly defined as the interaction occurring
between the electrophilic region on a halogen atom and a nucleophilic
region on another atom.[1] The first concrete
approach to halogen bonding was suggested in the 50’s of the
last century when Mulliken theorized that a charge transfer (CT) process
was the basis of the UV absorption spectra observed for iodine in
both acetone and aromatic solvents.[2] He
was the first to consider these systems as Lewis acid–base
pairs, in which orbital interactions would mediate the CT from the
base to the acid, the halogen.[3] Such phenomena,
based on spectroscopic observations, were then confirmed by the work
of Odd Hassel about CTcomplexes.[4]In 2005, Clark et al. proposed a different understanding of halogen
bonding by the so-called σ-hole model.[5] Starting from a BLYP NBO analysis on halomethanes, the theory assumes
the presence of a positive electrostatic potential surface, calculated
on the halogen atom, to be the driving force of XB. Albeit still using
the Lewis acid–base definition, it treats XB as a noncovalent
electrostatic interaction, ignoring the importance of the CT phenomena
proposed by Mulliken. Similarly, hydrogen bonding (HBs) have been
considered as electrostatic noncovalent bonds for a long time, mainly
because of their relatively weak bond strength.[6] However, both experimental and theoretical studies have
already pointed out the covalent contribution to their interaction
mechanism.[7−9]Interestingly, for both XBs and HBs, ab initio
calculations confirm
the involvement of stabilizing molecular orbital (MO) interactions[10,11] and the CT mechanism.[12,13] Thus, electrostatics
cannot be the only driving force of halogen bonding, and even exchange–repulsion,
induction, and dispersive effects are important.[14,15] Electrostatics, indeed, are not enough to explain bond directionality[16] or to predict the structure of the complex in
a variety of cases for which the final geometry cannot be rationalized
by σ-hole.[17] Predicting the stability
and geometry of XBs deserves great attention in drug design,[18,19] where accurate analyses can improve the predictive power of computations.
There is an increasing need for modeling drug–receptor XBs
appropriately, as the latter has turned out to be the key to selectivity
and efficacy toward a wide range of protein therapeutic targets.[20,21] One of the first and most representative examples of XBs in medicinal
chemistry derives from the work of Sandler et al., by which it was
possible to elucidate the interaction mechanism of the iodinated thyroid
hormones (T3 and T4) and the related selectivity toward the nuclear
receptors TRα and TRβ.[22] Not
surprisingly, many computational methods have been developed to improve
XB modeling.[23,24] The σ-hole model has been
extensively used to give indications about the ideal interaction geometry
between halogenated ligands and simple backbone monopeptide (N-methyl-acetamide) or sidechain models,[25] but generally by paying more attention to the electrostatic
properties of ligands rather than to the chemical–structural
complexity of the protein target.[26] Moreover,
in the available protein databases, only a few ligands adopt the bond
geometries classically predicted by σ-hole theory,[27,28] indicating the concrete necessity of a more accurate and reproducible
XB model for drug design.In the present work, we provide a
deeper understanding of the XB
mechanism in ligand–protein systems, by means of Kohn–Sham
MO theory and quantitative energy decomposition analysis (EDA). Starting
from the simplest model of interaction (Figures and 2), we inspected
the effect of the local backbone environment on the XBcomplex geometry
and energy. Bromobenzene (PhBr) was used as the basic model of halogenated
ligands. In fact, after a “chemical structure search”
on the Protein Data Bank database,[29] 67.33%
of the latter showed at least a halobenzene moiety (including also
fluorine). Among the elements that are able to donate XBs, bromine
was chosen due to its atomic properties, ranging between chlorine
and iodine, although its relative abundance in the available crystal
structures is 4 times lower than that of chlorine (Cl 76.36%, Br 18.52%,
I 5.10%). Based on the insights emerging from our analyses, we support
the potential use of bromine in drug design. Finally, we have investigated
the resemblances between halogen bonding and hydrogen bonding.
Figure 1
Molecular orbital
interactions between a carbonyl electron donor
and a halogenated benzene electron acceptor forming a halogen bond
complex.
Figure 2
Optimized three-dimensional (3D) models used
in the present work;
XB interaction angles and bond distances are reported.
Molecular orbital
interactions between a carbonyl electron donor
and a halogenated benzene electron acceptor forming a halogen bond
complex.Optimized three-dimensional (3D) models used
in the present work;
XB interaction angles and bond distances are reported.
Methodology
Computational Settings
Density functional
theory (DFT) calculations were performed with the Amsterdam density
functional 2018.105 (ADF).[30−32] Optimized geometries and energies
were calculated in the gas phase. The dispersion-corrected BLYP-D3(BJ)
functional was used[33,34] for all energies and geometries.
The Kohn–Sham molecular orbitals (KS MOs) were constructed
from a linear combination of Slater-type orbitals (STOs), having correctcusp behavior and long-range decay. The TZ2P basis set was used.[35] This is a triple-ζ quality basis set for
all atoms, augmented with two sets of polarization functions: 2p and
3d on H, 3d and 4f on C and O, and 5d and 6f on Br. Such combination
has been reported to be accurate in reproducing the structural and
energy properties of related noncovalent bonds.[36,37] Neither frozen core approximation nor symmetry constraints were
used. Three-dimensional (3D) molecular structures were generated by
the ADF program. All of the plots were obtained using GNUPLOT 4.6.[38] The PyFrag 2019 program was used to perform
energy calculations as a function of distances and angles.[39] Two-dimensional structures were drawn using
Marvin Sketch,[40] ChemDraw Professional
16.0,[41] and Chimera 1.11.2 software.
Energy Decomposition Analysis (EDA)
Energy
decomposition analysis is a valuable method to separate individual
energetic terms.[42,43] The bond energy of complexes
was decomposed into the strain (or preparation) energy ΔEStrain and the interaction energy ΔEIntΔEStrain is the energy necessary
to deform the optimized separated monomers
into their geometry in the final complex. The term ΔEInt accounts for the effective interaction energy
between monomers in the complex state and can be further decomposed
into four physically meaningful termsThe term ΔVElstat represents the
classical electrostatic interactions between charge
distributions related to the deformed monomers. The orbital interaction
energy term, ΔEOi, contains charge
transfer (donor–acceptor interactions) and polarization effects
(electron density redistribution on one monomer in the presence of
the other monomer). The Pauli repulsion ΔEPauli accounts for the destabilization due to the overlap between
the monomers’ occupied orbitals and is responsible for steric
repulsion. The term ΔEDisp is added
for dispersion corrections.
Voronoi Deformation Density
(VDD) Charge
VDD charge accumulation, ΔQA,
has been calculated for halogen bonding as the change in electron
density between the isolated monomers 1 and 2 and the complex, giving indications about charge transfer processes[44]A positive VDD charge corresponds to the loss
of electrons, whereas a negative charge is related to the gain of
electrons.
Results and Discussion
Bonding Energies and Geometries
The
bonding energy and the geometry of each complex presented in Scheme were calculated
to understand how the gradual substitution at the carbonyl acceptor
toward realistic model systems affects the mutual orientation of the
XB partners and the overall stability. The local protein environment
and even small geometrical deformations of the target site, in fact,
can be crucial for the perfect fit of the ligand and its bound-state
stability. Solvation and entropiccontributions were not considered,
to evaluate only the intrinsic nature of halogen bonding as related
to the chemical partners.
Scheme 1
Schematic Representation of the Halogen-Bond
Donor and Halogen-Bond
Acceptors in This Study
Either methyl and amino (−CH3 and −NH2, highlighted in red) or formyl
(−CHO, highlighted in blue) groups were added stepwise to formaldehyde.
Each set is distinguished by different background colors (1 → 3 yellow; 1 → 6′ light blue; and 1 → 9 light
red).
Schematic Representation of the Halogen-Bond
Donor and Halogen-Bond
Acceptors in This Study
Either methyl and amino (−CH3 and −NH2, highlighted in red) or formyl
(−CHO, highlighted in blue) groups were added stepwise to formaldehyde.
Each set is distinguished by different background colors (1 → 3 yellow; 1 → 6′ light blue; and 1 → 9 light
red).In Table , the
bond energy and different geometrical parameters are reported (see
also Supporting Information (SI 1–2)
for cartesian coordinates). The results clearly indicate that the
stepwise functionalization of the carbonyl acceptor leads to an observable
variation of energies and geometries. ΔEBond becomes more stabilizing almost linearly with the insertion
of −CH3 and −NH2 groups for each
complex set (1 → 3, 1 → 9, and 1 → 6′), reaching the largest values for complexes 3 (−2.48 kcal mol–1), 6 (−2.79
kcal mol–1), and 6′ (−3.19
kcal mol–1), respectively, while it becomes weaker
when a formyl moiety is added to form complex 7 (−2.65
kcal mol–1). Data reveal, at the first instance,
that the presence of the second peptide bond, close to the XB pair,
is involved in complex stability (Table , complexes from 7 to 9). The Br–O distance follows the same trend of ΔEBond only for set 1 → 3, that is, it becomes shorter with a more stable ΔEBond. In set 1 → 9, it shortens proportionally from complex 1 (3.164 Å)
to complex 6 (3.034 Å), but after the insertion
of the formyl group it slightly elongates, reaching, finally, a value
of 3.118 Å in complex 9. In complex 6′, yielding the strongest ΔEBond value among the overall set, the bond length shows some increase
as well (3.063 Å). These values are consistent with previous
benchmarks on available crystal structures.[28]
Table 1
Geometrical Features and Bonding Energies
of Bromobenzene in Complex with XB Acceptors Used in our Studya
set
complex
Br···O (Å)
ωBrOC (deg)
θCArBrO (deg)
φBrOCN (deg)b
ΔEBond (kcal mol–1)c
1–3
1
3.164
99.1
165.0
180.0
–2.10 (−1.85)
2
3.113
101.1
168.6
180.0
–2.29
(−2.02)
3
3.088
121.3
176.9
175.0
–2.48 (−2.18)
1–9
1
3.164
99.1
165.0
180.0
–2.10 (−1.85)
4
3.080
99.8
169.4
180.0
–2.47
(−2.16)
5
3.059
100.2
169.9
181.1
–2.60 (−2.30)
6
3.030
120.7
176.9
168.7
–2.79 (−2.47)
7
3.090
110.9
174.9
136.1
–2.65 (−2.35)
8
3.111
105.2
174.5
127.8
–2.68
(−2.37)
9
3.118
103.5
174.1
125.2
–2.71 (−2.39)
1–6′
1
3.164
99.1
165.0
180.0
–2.10 (−1.85)
4
3.080
99.8
169.4
180.0
–2.47
(−2.16)
5′
3.037
111.7
177.6
179.6
–2.79 (−2.46)
6′
3.063
112.6
175.2
217.1
–3.19 (−2.83)
Computed at BLYP-D3(BJ)/TZ2P.
For the complex set 1 → 3, values refer to dihedral angles represented
by BrOCH (1) and BrOCCH3 (2, 3).
In parentheses,
the counterpoise
corrected energy. The basis superposition error of monomers is reported
in SI 3.
Computed at BLYP-D3(BJ)/TZ2P.For the complex set 1 → 3, values refer to dihedral angles represented
by BrOCH (1) and BrOCCH3 (2, 3).In parentheses,
the counterpoise
corrected energy. The basis superposition error of monomers is reported
in SI 3.The ideal CArBrO angle θ (Figure ) has been reported
in the literature to
be 175–180°.[23] Comparison of
the most stable complexes (3, 6, and 6′) highlights that, although they retain almost the
same linear angle (176.9 and 175.2°), their respective energies
are different. For 6 and 6′ this
is due to the difference in the dispersion energy term, while complex 3 shows a lower stability because of any contribution (Figure ). Therefore, a more
linear XB does not necessarily implicate a stronger XB. The θ
angle, indeed, neglects the effect of substituents on stability. The
BrOC angle, ω, ranges on average between 99 and 121°. The
dihedral angle between bromine, carbonyl oxygen, carbonyl carbon,
and its main geminal N atom (−H for formaldehyde and −CH3 for acetaldehyde or acetone), φ, can change significantly
as new moieties are added to the acceptor structure. Interestingly,
complexes 7, 8, 9, and 6′ feature the highest variability of φ compared
to the other systems, by negative and positive deviations from planarity
(180°), respectively (136.1, 127.8, 125.2, and 217.1°).
This geometrical feature indicates how the carbonyl bond plane is
oriented toward the halogen atom: when a formyl group is added to
complex 6, the main axis of the carbonyl bond is rotated
drastically clockwise (φ ≪ 180°), while in the −CH3-functionalized complex 6′ it is rotated
anticlockwise (φ ≫ 180°) (vide infra). For both,
the oxygen lone pair (LP) orientation with respect to the halogen
atom changes significantly, and even the resulting energy variation
is different. The ΔEBond reaches
the strongest energy for the 6′ complex (−3.19
kcal mol–1), giving preliminary suggestions about
the higher stability of the Gln sidechain-mediated XB. The inclusion
of the formyl moiety (complex 7), on the other hand,
leads to destabilization. These findings imply the existence of different
forces determining the interaction mechanism.
Figure 3
Representation of the
halogen-bonding angles.
Figure 4
EDA for XB complex sets 1 → 3 (A), 1 → 9 (B), and 1 → 6′
(C).
Representation of the
halogen-bonding angles.EDA for XBcomplex sets 1 → 3 (A), 1 → 9 (B), and 1 → 6′
(C).
Nature
of the Halogen Bond
Energy
decomposition analysis in combination with the Kohn–Sham molecular
orbital theory offers a thorough understanding of the electronic mechanism
involved in the stability of each XBcomplex set (SI 4).For set 1 → 3, the stepwise addition of methyl groups leads to an increase of
all contributions to ΔEInt (Figure A). In magnitude,
electrostatics is the most stabilizing component, whereas Pauli repulsion
is highly destabilizing. However, ΔVElstat cannot provide the observed negative ΔEInt alone, because, if other favorable components were excluded,
it would be largely canceled out by ΔEPauli. Both ΔEOi and ΔEDisp contribute significantly to the interaction
energy. The electrostatic interaction energy shows a strong correlation
with the orbital interaction energy. It can be seen that their gradient
is almost equal for each pair of points shown in Figure (ΔΔVElstat ≈ ΔΔEOi). The change in orbital interaction depends on the energies of the
interacting orbitals. In general, the smaller the highest occupied
molecular orbital (HOMO)–lowest unoccupied molecular orbital
(LUMO) gap, the stronger the orbital interactions. The larger charge
on the acceptor when going from 1 to 3 results
in the destabilization of the oxygen LP orbital (see also Figures and 6), thereby decreasing the HOMO–LUMO gap and thus yielding
a stronger ΔEOi.
Figure 5
Optimized complexes,
MOs and related energies (in eV). Each set
is distinguished by different colors (1 → 3 yellow; 1 → 6′ blue;
and 1 → 9 red).
Figure 6
Energy
(in eV) of the interacting HOMO and LUMO, for sets 1 → 3 (A), 1 → 9 (B), and 1 → 6′
(C); for complexes 8–9, values refer
to HOMO – 1.
Optimized complexes,
MOs and related energies (in eV). Each set
is distinguished by different colors (1 → 3 yellow; 1 → 6′ blue;
and 1 → 9 red).Energy
(in eV) of the interacting HOMO and LUMO, for sets 1 → 3 (A), 1 → 9 (B), and 1 → 6′
(C); for complexes 8–9, values refer
to HOMO – 1.Analysis of set 1 → 9 is consistent
with previous results (Figure B). All of the components increase their contribution up to
the largest value (6), where ΔEOi equals even ΔEInt. After the inclusion of the formyl moiety, all of the contributions
decrease, with the only exception of ΔEDisp. When the new peptide bond is formed, the other components
reach a plateau. ΔEInt becomes more
stabilizing due to dispersion effects, and also because of the considerable
decrease in Pauli repulsion destabilization observed after the insertion
of the formyl group. Contributions from the orbital and electrostatic
interactions are still correlated. They become less stabilizing concerted
with the clockwise reorientation of the LP located on the peptide
carbonyl (Table ,
φ).Acetamide and propanamide (5′, 6′, Scheme ) represent
very simple models of sidechain acceptors: Asn and Gln, respectively.
ΔEInt is more stabilizing for the
Gln. ΔEPauli is increasingly destabilizing
stepwise along the entire set, while ΔEDisp is more stabilizing. ΔEOi and ΔVElstat are approximately
constant between 5′ and 6′ (Figure C). The
−CH3 and −NH2 stepwise functionalization
is determinant in improving the overall stability, as already observed
for the series formaldehyde–acetaldehyde–acetone (set 1 → 3), but the higher stabilization observed
for the Gln sidechain is due to dispersive effects only because the
β methyl group improves neither the electrostatics nor the orbital
interaction, i.e., when considering the Gln sidechain as a potential
acceptor, the stabilization observed is only due to dispersion effects,
while in the case of the Asn sidechain all of the components are affected.
The Gln is more favored than the Asn sidechain in forming XBs, following
the better dispersion given by the β carbon. It is reasonable
to assume that a linear alkyl elongation of acetamide would not affect
the XB stability in terms of ΔEOi and ΔVElstat. There is no indication
in these systems for any substantial C–H···Br
hydrogen bonding, which would show up as a slight elongation of the
C–H bond due to the donor–acceptor interaction of the
Br lone-pair orbital with the σ*CH acceptor orbital.
Such a C–H elongation does not occur (see SI 5). On the contrary, there is a (very minor) contraction
of the C–H bond upon complexation.Our calculations give
concrete evidence of how the nearby local
chemical environment of any potential acceptor can influence the ligand–protein
XBs, acting on each energy component. To further elucidate the role
of MO interactions in halogen bonding, we performed an extensive KS
MO analysis.
Kohn–Sham Molecular
Orbitals and Charge
Transfer
In Figure , it is possible to see the overlap between the main interacting
LUMO of bromobenzene (XBdonor) and the HOMO of the XB acceptors.
The LUMO energy of bromobenzene is constant, and, on the other moiety,
the HOMO, which mainly consists of an oxygen LP, follows a certain
trend, yielding different ΔεHOMO–LUMO values (Figure ).
εHOMO increases when going from acceptor 1 to acceptor 3, from 1 to 6 and from 1 to 6′, reflecting the
observed ΔEBond trends and energy
minima. As can be seen in Figure , the oxygen LP orbital on the acceptors overlaps significantly
with the virtual orbital on Br. The introduction of another peptide
bond into complex 6 (complexes 7–9) stabilizes the εHOMO by 0.49 eV. The carbonyl
bond axis rotates clockwise, and a weaker ΔEOi contribution is observed for complexes 7, 8, and 9. The oxygen’s LP orbital
of complexes 8 and 9, in fact, occupies
a lower (more stabilized) energy level (HOMO – 1), and the
HOMO is located on the other oxygen atom. Based on the significant
contribution of ΔEOi to the total
XB energy, and the good correlation between ΔEOi and the LP energy level (HOMO), we can conclude that
MO interactions play an important role in halogen bonding. To further
validate this observation, charge transfer mechanisms were explored
by gross population analysis and VDD charges (Table and Figure ).
Table 2
Gross Populations
(in Electrons) of
Main Interacting MOs
complex
LUMO
HOMO
1
0.013
1.989
2
0.017
1.987
3
0.021
1.985
4
0.019
1.984
5
0.021
1.983
5′
0.023
1.985
6
0.024
1.984
6′
0.021
1.990
7
0.018
1.992
8
0.016
1.993a
9
0.016
1.994a
Values refer to
HOMO – 1.
Figure 7
VDD charges (in au) of the halogen-bond acceptor and donor
for
sets 1 → 3 (A), 1 → 9 (B), and 1 → 6′ (C)
due to the halogen-bond formation (eq ).
VDD charges (in au) of the halogen-bond acceptor and donor
for
sets 1 → 3 (A), 1 → 9 (B), and 1 → 6′ (C)
due to the halogen-bond formation (eq ).Values refer to
HOMO – 1.Gross population
values give a measure of how many electrons migrate
from the LP orbital of the XB acceptor toward the lowest unoccupied
MOs of the XBdonor (charge transfer). Values are consistent with
the existence of a CT process for any XBcomplex. The gross populations
increase for the LUMO and decrease for the HOMO when −CH3 and −NH2 groups are added to the XB acceptor.
The opposite behavior is observed in the presence of the second peptide
bond. Indeed, the LUMO population decreases for complex 7 and is kept constant for complexes 8 and 9, where only the HOMO population changes slightly. The VDD charge
analysis reported in Figure gives further insight into the electron density flow from
the XB acceptor to the donor. In all of the complexes, the carbonyl
compound VDD charge ΔQ is positive (it donates
electrons), while the bromobenzene is always negative (it accepts
electrons). As the methyl and amino groups are added to the system,
acceptor and donorcharges become respectively more positive and more
negative, conversely when introducing another peptide bond.In set 1 → 6′, ΔεHOMO–LUMO becomes smaller with the methyl group insertion,
but ΔQ of the Asn sidechain acceptor (5′) is more negative than Gln (6′), indicating a less efficient CT in the latter case. Consistently,
the greater XB length observed in 6′ (3.063 vs
3.032 Å, Table ) leads to a smaller HOMO–LUMO overlap, compared to complex 5′ (S2 = 0.008 in 5′, S2 = 0.005 in 6′). The CT is strongly evident when considering the
series formaldehyde–acetaldehyde–acetone (1–3), in which −CH3 groups are
added stepwise at both sides of the carbonyl moiety and the LUMO population
increases. In accordance, ΔεHOMO–LUMO (Figure ) becomes
smaller when going from 1 to 3. ΔεHOMO–LUMO, gross population analysis, and VDD charges
resemble the same general trend, confirming the involvement of CT
in XB stability and its dependence on the local chemical environment
of the Lewis pair. Noteworthily, structural isomer pairs (5–5′, 6–6′) show that substituents’ position affects the electronic
distribution significantly since their ΔεHOMO–LUMO, gross populations, and VDD charges are different for each complex,
despite each member sharing the same atoms with its analogue. In general,
we found that protein methyl and amino building blocks improve the
charge donation and the stability of the complex, differently from
the proximal peptide bond carbonyl, which tends to lower it.
Halogen Bonds vs Hydrogen Bonds
XBs
and HBs share two features: (1) a common bond acceptor, i.e., an electronegative
atom with a partial negative charge acting as the XB or HB acceptor,
and (2) directionality. In the previous sections, we have defined
the presence of CT mechanisms mediated by MO interactions. Here we
address the importance of XB directionality and the main differences
compared to HB. In Figure , the most relevant HOMOs of formaldehyde are reported. Any
of these orbitals could overlap in space with the main LUMO of the
donor, yielding some interaction. As can be seen in Figure , all three orbitals can have
a good overlap with the LUMO of the XBdonor. However, the energy
difference between the HOMO and lower-lying orbitals is very large.
For example, the orbital energy goes down by 3.67 eV when moving from
the HOMO to HOMO – 1, which amounts to an increase in the gap
between the occupied MO and the LUMO of more than 72%. As a result,
the HOMO–LUMO interaction is stronger than the [HOMO –
1]–LUMO interaction.
Figure 8
Directionality and energy (in eV) of the most
relevant HOMOs in
the formaldehyde XB complex.
Directionality and energy (in eV) of the most
relevant HOMOs in
the formaldehydeXBcomplex.The major overlap involves an LP of the oxygen oriented toward
the halogen atom following the BrOC angle, ω, close to 120°
(Figure ). A similar
depiction was already provided in the literature for HBs and can be
reliably related to the so-called “orthogonality” between
HBs and XBs in ligand–protein systems,[45] i.e., the peptide carbonyl can engage both at one time, following
the directionality of its LPs.With a view to validate the common
nature of HBs and XBs, we have
calculated the geometry and energy of the complexes obtained using
pyridine and formaldehyde as bond acceptors (having different LP directionality)
and water and bromobenzene as bond donors. The calculated geometries
and MOs reported in Figure confirm that XBs and HBs can have a similar bonding mechanism.
Figure 9
XB/HB
pair comparison. HOMO and LUMO energies (in eV) along with
their gross population (in electrons) and the bond lengths between
O/N and H/Br (in Å).
XB/HB
pair comparison. HOMO and LUMO energies (in eV) along with
their gross population (in electrons) and the bond lengths between
O/N and H/Br (in Å).For each pair, donor–acceptor orbital overlap occurs exactly
in the same direction of the LP HOMO. The bond distances are considerably
smaller for the HB complexes. The gross populations reveal a similar
charge transfer picture: the LP orbitals lose electron density, which
is being transferred to the opposing virtual orbital on hydrogen (HB)
or the halogen (XB). The gross populations for HBs and XBs are of
the same order of magnitude.EDA discloses similarities between
HBs and XBs in a more quantitative
manner (Table ). ΔEBond and ΔEInt attribute more stability to the HBs than XBs. Energy components
are more stabilizing for the pyridine than the formaldehyde acceptor
in any complex pair, because of the higher LP orbital. Their relative
contribution to the overall energy is approximately equal, independently
of the complex considered. ΔEPauli and ΔVElstat give the highest
contribution, followed by ΔEOi and
ΔEDisp. Even in these cases, the
electrostatic interaction and Pauli repulsion are not the only determining
factors for the total interaction energy. Interestingly, ΔEOi shares the same order of magnitude with ΔVElstat, being generally more than one-half of
the latter. The dispersion interaction is relatively more important
for the XBs than for the HBs.
Table 3
EDA (in kcal mol–1) for HB and XB Complexes, Computed at the BLYP-D3(BJ)/TZ2P
Level
of Theory
complex
ΔVElstat
ΔEPauli
ΔEOi
ΔEDisp
ΔEint
ΔEBonda
HOH···O=CH2
–7.56
7.43
–4.02
–1.21
–5.36
–5.27
(−4.94)
HOH···NC5H5
–13.01
13.73
–7.15
–1.70
–8.13
–7.90 (−7.50)
PhBr···O=CH2
–2.54
3.70
–1.41
–1.86
–2.11
–2.10
(−1.85)
PhBr···NC5H5
–6.44
9.36
–3.60
–2.70
–3.38
–3.33 (−2.99)
In parentheses, the counterpoise
corrected energy.
In parentheses, the counterpoise
corrected energy.The effect
of the bond donors on any energeticcomponent is greater
than the effect of the bond acceptors, especially if comparing bromobenzene
and water as bound to the pyridine acceptor. The bond distance in
a HB complex is ∼1.5 times shorter than in the analogous XB.
However, the |ΔεHOMO–LUMO| is smaller
for the XB than the HB because the LUMO is more stabilized in bromobenzene
than in water. Also, the MO interaction is more favorable for HB than
XB, and the bond length is shorter. To analyze these aspects, we calculated
the interaction energy profile of the HB and XBcomplexes by varying
the distance between N and Br/H from 3.0 to 1.8 Å in 20 geometry
optimization steps (0.06 Å per step). The angles ∠CArBrN and ∠NHO were kept constant. The results are reported
in Figure (see SI 6 for coordinates). In both HB and XB, electrostatics
and orbital interactions are the most important stabilizing components.
Note that all individual contributions, as functions of the atom pair
distance, are more favorable in halogen bonding, except for ΔEPauli and ΔEStrain, which are less destabilizing in hydrogen bonding. The interaction
energy gets stronger with shorter distances in HB, while in XB it
quickly becomes destabilizing at ∼2.5 Å, indicating that
shorter bond lengths are not allowed. Indeed, both Pauli repulsion
and strain energy are 20 times more destabilizing in XB than in HB.[11] XB is clearly more favored than the latter one
in terms of electrostatics, orbital interactions, and dispersion at
any distance. However, the strong Pauli repulsion, due to the overlap
between the monomers’ filled orbitals, prevents the monomers
from getting closer to each other.
Figure 10
Energy terms and the largest overlap
are represented as functions
of the distance between the acceptor N and donors Br (XB complex in
blue) or H (HB complex in red), computed at the BLYP-D3(BJ)/TZ2P level
of theory.
Energy terms and the largest overlap
are represented as functions
of the distance between the acceptor N and donors Br (XBcomplex in
blue) or H (HB complex in red), computed at the BLYP-D3(BJ)/TZ2P level
of theory.
Directionality
of Halogen Bonds
Bonding
directionality is crucial for understanding the basis of XB stability,
as the orbital overlap and, therefore, the orbital interaction are
strongly affected by the relative orientation of the monomers. The
σ-hole theory models directionality by computing the electrostatic
potential surface of the halogen atom in the isolated monomer. Based
on this, the perpendicular orientation of the XB atom pair (θ
= 90°, Figure ) should be highly disfavored because of the electrostatic repulsion
occurring between the negative charge density of the acceptor and
the negative belt on the halogen. This model follows the classical
chemical interpretation of repulsion occurring when strongly electronegative
atoms approach each other. However, DFT calculations on perpendicular
geometries, performed by Huber et al. in 2013,[16] provided results that are highly inconsistent with this
conclusion.To understand the directionality of XBs for medicinal
chemistry, the pyridine–bromobenzenecomplex model was used.
PyridineLewis base is not a natural protein component, but its electron
LP is highly directional and lies on the same plane of the bromine
atom, making pyridine suitable for the specificcorrelation between
stability and directionality. The geometry of the complex was reoptimized
by starting from two possible orientations of the pyridine plane with
respect to the phenyl ring, namely, transverse and coplanar (Figure , panels A and
B). The θ angles, corresponding to the minimum energy structures
of the two constrained optimizations, were almost linear (178.2 and
179.3° respectively), and the bond lengths were 2.986 and 2.983
Å. The transverse and coplanar optimized structures differed
in energy only by 0.05 kcal mol–1, validating the
usage of both in the subsequent step. For each structure, we performed
single-point energy calculations and energy decomposition analysis,
as a function of the zenith and azimuthal angle θ, ranging from
180 to 90° in 10 steps (coordinates in SI 7). As expected, ΔEInt is
unfavorable for θ ∼ 90–140°, independently
of the case considered. The azimuth angle variation leads to more
destabilization than the zenith angle. ΔEDisp is linearly more favorable in any condition. ΔVElstat and ΔEOi are almost constant for the zenith angle, while they even become
more stabilizing for the azimuth angle variation. In any case, the
complex is highly destabilized in the perpendicular orientations (Figure ) because ΔEPauli increases, reaching the highest contribution
for the coplanar/azimuth θ angle complex combination. Why does
Pauli repulsion increase? As shown in Figure , depending on the angle considered, a different
HOMO of the bromobenzene overlaps with the HOMO of pyridine. Such
orbitals are the HOMO and HOMO – 2, for the zenith and azimuthal
angle, respectively. In general, for the most stable geometries, the
HOMOs of the donor and acceptor do not overlap significantly and ΔEInt is favorable. Independently of the case
considered, in fact, for θ = 180°, S2 is always less than 10–5 (SI 7, pages 54-63-72-82). However, when θ decreases, the overlap becomes greater by several
orders of magnitude compared to the initial state. Specifically, for
θ = 90°, S2 is always larger
than 10–3. The big HOMO–HOMO overlap causes
strong Pauli repulsion and, finally, an unfavorable interaction energy
is observed.
Figure 11
Energy terms and MOs represented as functions of the zenith/azimuth
θ angle between N, Br, and aromatic C, computed at the BLYP-D3(BJ)/TZ2P
level of theory (A, transverse orientation; B, coplanar orientation).
Energy terms and MOs represented as functions of the zenith/azimuth
θ angle between N, Br, and aromaticC, computed at the BLYP-D3(BJ)/TZ2P
level of theory (A, transverse orientation; B, coplanar orientation).As mentioned above, regarding the azimuth angle
in Figure , the
electrostatic interactions
and orbital interactions are more stabilizing at perpendicular geometries
than at the linear ideal ones. Indeed, this result is in total contrast
with the σ-hole model—which, conversely, predicts destabilizing
electrostatics for perpendicular XBs—and extremely pronounced
for the coplanar complex (Figure B), where the orbital interactions are even stronger
than electrostatics.
Conclusions
In the
present study, we have investigated the effect of substituents
on peptide halogen-bond (XB) acceptors, by means of the Kohn–Sham
molecular orbital (MO) theory and energy decomposition analysis (EDA),
giving the basis for more accurate ligand–protein interaction
models. We find that peptide methyl and amino building blocks improve
the stability of XBcomplexes by electrostatics, dispersion, and charge
transfer from the Lewis base to the halogenated Lewis acid. Conversely,
the inclusion of a peptide carbonyl, adjacent to the XB pair, decreases
the stability of the XBs. Our results point out the great influence
of the protein backbone environment in both the complex geometries
and energies. The most used N-methyl-acetamide acceptor
model (complex 6), indeed, is not appropriate when describing
ligand–peptide XBs. The inclusion of the dihedral angle φ
dependence into our analysis provides a deeper understanding of the
XBdonor–acceptor orientation, by accurately describing the
approach of the halogen atom toward the peptide bond plane. Moreover,
we have found φ to be highly dependent on the chemical environment,
whereas the widely used θ angle shows only little dependence.We have also compared the stability and geometry of XBs to HBs,
as a function of the atom pair distance. Our EDA on donor–acceptor
model systems of XBs and HBs reveals that XBs and HBs share the same
interaction mechanism, based on the subtle interplay of electrostatics,
donor–acceptor orbital interactions, and dispersion, consistent
with previous comparative studies. However, it was found that XBs
are less stable than HBs, with bond lengths longer than HBs, because
of a stronger Pauli repulsion. Our findings demonstrate the need to
incorporate quantum effects in molecular modeling approaches for drug
design. Finally, the directionality of XBs was thoroughly investigated
using a pyridine–bromobenzene model. The zenith and azimuth
θ angles were explored in a range between 180 and 90°,
starting from either a transverse or a coplanar orientation of the
pyridine with respect to the bromobenzene ring. The electrostatic
interactions appear to be always more favorable for the perpendicular
than for the linear states, in total disagreement with the σ-hole
model. Indeed, the only term responsible for the destabilization of
the interaction energy is the Pauli repulsion arising from the HOMO–HOMO
overlap between the lone pair of the XB acceptor and the π lone
pairs of the XBdonor. Thus, the directionality of XBs is ascribed
to the Pauli repulsion and not to any electrostatic repulsion.This work has provided an insightful understanding of the halogen
bonding mechanism in ligand–peptide systems, by means of an
accurate quantum-chemical modeling methodology, comprising all underlying
physicochemical factors required within a typical drug design process.
Our findings will support the implementation of DFT-based forcefields,
aimed at modeling even large ligand–protein systems more accurately.
Indeed, the proposed strategy is highly suitable to the context of
molecular docking, molecular dynamics, and all of those computational
methods by which the correct prediction or rationalization of ligand
binding states can make the difference to the identification of new
powerful therapeuticcandidates.
Authors: H M Berman; J Westbrook; Z Feng; G Gilliland; T N Bhat; H Weissig; I N Shindyalov; P E Bourne Journal: Nucleic Acids Res Date: 2000-01-01 Impact factor: 16.971
Authors: Rainer Wilcken; Markus O Zimmermann; Andreas Lange; Andreas C Joerger; Frank M Boeckler Journal: J Med Chem Date: 2013-01-03 Impact factor: 7.446