Quantifying Non-Covalent
Attractive Interactions in
Asymmetric Catalysis
Kaid C. Harper
Department of Chemistry, University of Utah, 315 So. 1400 E., Salt Lake City, Utah
kharper@chem.utah.edu
Received Date (will be automatically inserted after manuscript is accepted)
ABSTRACT
R2 R H X
1
N
N
N
R3
O
Stabilized
H-Bonds
H
H
N
R2 R H X
1
N
N
N
R
3
O
H
H
H
H
N
C
H
R-enantiomer
N
H
N
C
H
S-enantiomer
Asymmetric oganocatalysis relies on non-covalent attractive interactions for reactivity as well as enantioselectivity.
Through computational techniques combined with physical organic principles, non-covalent attractive interactions
can be quantified and their role in asymmetric induction delineated. Models which describe asymmetric induction
based on non-covalent interactions are derived and experimentally validated suggesting their key role in several
asymmetric organocatalytic reactions.
Enzymatic systems have long been a source of
inspiration for the development of asymmetric catalysts.
Organocatalysis (which employs small chiral catalysts to
create enantioenriched products) holds considerable
advantages over transition metal-based asymmetric
catalysis:
including the elimination of metallic
byproducts and stoichiometric oxidants/reductants,
generally simpler catalytic systems, and of reactivity
manifolds that are not compatible with transition metals.1
With the notable exception of nucleophilic catalysis,
organocatalytic systems rely primarily on non-covalent
interactions for reactivity and asymmetric induction.2
Non-covalent attractive forces include hydrogen bonding,
- interactions, cation- interactions and other
electrostatic interactions. Jacobsen and coworkers have
recently developed organocatalysts which employ noncovalent attractive interactions’ to catalyze new
asymmetric reactions.3 Moreover, they have explored the
1
Berkessel, A.; Groeger, H. Asymmetric Organocatalysis; WileyVCH: Weinheim, Germany, 2005.
2
Taylor, M.S.; Jacobsen, E.N. Angew. Chem. Int. Ed. 2006, 45, 1520.
3
Knowles, R.R.; Jacobsen, E.N. Proc. Natl. Acad. Sci. U.S.A. 2010,
107, 20678.
mechanism by which asymmetric induction occurs within
these systems. Using computational chemistry in tandem
with traditional physical organic techniques, they
discovered correlations between enantioselectivity and
non-covalent attractive interactions. Specifically, they
were able to develop correlations between cation-
interactions and enantioselectivity and also hydrogen
bond length and enantioselectivity. Although often
implicated, only recently have non-covalent attractive
interactions been addressed quantitatively in asymmetric
catalysis, which has led to increased understanding of
these important interactions.
Jacobsen and coworkers faced a formidable challenge
in seeking to apply computational techniques to
asymmetric catalysis. The small energy differences that
give rise to high enantioselectivities (2-3 kcal/mol) are
difficult to estimate computationally in complex
asymmetric catalytic systems.4
This challenge is
generally overcome by simplifying model systems to
include only key interactions. Simplification of these
4
Pfaltz, A.; Drury, W. J. Proc. Natl. Acad. Sci. U.S.A. 2004, 101,
5723.
systems in computational modeling often restricts their
application to rational design. However, computational
techniques are an attractive resource for modeling noncovalent attractive interactions, as such interactions are
often difficult to elucidate by other techniques. Jacobsen
and coworkers studies are particularly useful because they
incorporate the entire catalytic system into their
computations creating a clear picture of how
enantioselectivity is achieved.
Jacobsen and Uyeda have recently reported an
asymmetric Claisen rearrangement (Figure 1A).5 Their
inspiration in developing an asymmetric organocatalytic
variant of this rearrangement was based on reports that
chorismate mutase enzymes catalyze [3,3]-sigmatropic
rearrangements through the stabilization of key
intermediates via H-bonding.6
Figure 1. A) The asymmetric Claisen rearrangement. B)
Compuationally determined catalyst structure.
C)
Computationally determined substrate geometry. D) Proposed
transition state with the cation-π interaction shown in red.
The optimized asymmetric variant proved to be general
and gave high enantioselectivity for a number of different
α-oxy methyl esters.
Given the general catalyst
selectivity and the novelty of the reaction, Jacobsen and
Uyeda directed their efforts towards the challenge of
understanding the mechanism of asymmetric induction.7
Modeling asymmetric induction (computationally)
requires several key pieces of information including: the
enantiodetermining step of the reaction, the catalyst
conformation in the transition state and the substrate
conformation in the transition state. They hypothesized
that the rearrangement step was the most probable
enantiodetermining step through detailed kintetic
analysis. Calculations determined the lowest energy
catalyst conformer (Figure 1B), which is dominated by a
stabilizing cation- interaction between the pyrrole rings
and guanidinium ion. These computational results were
verified by an X-ray crystal structure as well as NMR
spectroscopic studies. This was the first example of how
5
Uyeda, C.; Jacobsen, E.N. J. Am. Chem. Soc. 2008, 130, 9228.
Chook, Y.-M.; Ke, H.; Lipscomb, W.H. Proc. Natl. Acad. Sci.
U.S.A. 1993, 90, 8600.
7
Uyeda, C.; Jacobsen, E. N. J. Am. Chem. Soc. 2011, 133, 5062.
6
non-covalent
attractive
forces
influence
the
enantioselectivity of this reaction. Knowing the preferred
geometry of the catalyst, the possible transition state
conformations of model substrate 1 were examined.
Using a simplified catalyst, N,N-dimethyl guanidinium,
the overall activation energy of the catalyst system was
demonstrated to be 4.4 kcal/mol lower than the
uncatalyzed pathway through stabilization of the cabonylbound s-cis substrate conformation (Figure 1C).
Knowing the ground state geometries and binding
preferences, the overall energy of the catalyzed system
was calculated at the B3LYP/6-31G(d) level of DFT. The
difference in transition state energies was calculated to be
2.99 kcal/mol greater for the minor (R,R) product,
compared to the 1.36 kcal/mol difference experimentally
observed.
Although the computational model
overestimates the observed difference in energy, it does
correctly predict facial selectivity, and therefore was used
as a first approximation of the transition state.
A key difference in the computed transition states is the
projection of the allyl portion of the substrate (Figure
1D). In the transition state leading to the major
enantiomer, the allyl fragment is projected toward a
phenyl substituent, while in the minor transition state, the
allyl fragment is projected under the cyclohexyldiamine
portion of the catalyst.
In the enantiodetermining
transition state, a buildup of positive charge occurs on the
allyl fragment. This buildup of positive charge is
stabilized by the π-system of the phenyl ring in the major
transition state (indicated in red).
Jacobsen and Uyeda synthesized and computationally
predicted the enantioselectivity of electronically-varied
catalysts 3a-3f (Figure 2). These electronic perturbations
would variably stabilize the cation-π. Using the M05-2X
functional,8 which is designed to model the type of charge
separation evidenced in Figure 1D, they qualitatively
modeled the trend in increasing enantioselectivity with
increasing electron density of the phenyl substituent
(Figure 2). Comparison with the experimentally observed
enantioselectivity revealed the computational predictions
generally overestimated the enantioselectivity by ~ 2.1
kcal/mol. This relatively large error is systematic,
implying that the source of the error is entropic or
reaction medium related, because the calculations are
performed in the gas phase. The trend also quantitatively
describes the optimal catalyst for this reaction, that being
the dimethyl-amino substituted 3b. General evaluation of
3b in the substrate scope led to generally greater
enantioselectivities.
This example demonstrates how two different noncovalent attractive forces working in concert can deliver
high degrees of enantioselectivity. It also demonstrates
the power of computational techniques in modeling these
non-covalent attractive forces.
In the organocatalytic Claisen rearrangement, the key
enantiodetermining interaction was stabilization of charge
buildup through a cation-interaction, despite the
8
Zhao, Y.; Truhlar, D. G. Acc. Chem. Res. 2008, 41, 157.
absence of a formal cationic intermediate.
With
knowledge that such interactions can improve
enantioselectivity, it seems natural to invoke them in
reactions where cationic intermediates are proposed.
Again inspired by the advances in the understanding of
cation- interactions in enzyme active sites, Jacobsen and
Knowles rationalized that incorporating cation-stabilizing
arene moieties into their anion-binding thiourea
frameworks could promote reactions in which charge
separation is required.9 To examine this hypothesis, they
undertook the development of an asymmetric variant of
the polycyclization of hydroxylactams (Figure 3).
F
A)
Me
N
Me
N
N
F
BAr F-
3a
NH2+
R
N
H
N
H
F
F
3c
F
F
R
3d
F
3b
N
F
N
F
N
N
Me
3e
CF3
3f
B)
interaction; however, the dependence on arene size could
also be due to steric repulsion. To delineate the role of
the arene as either sterically repulsive or cation-
stabilizing, an Eyring analysis was performed using
several arene substituents on the catalyst (Figure 3). The
results of the analysis over a 70° range revealed that the
arene contribution was primarily enthalpic in nature. This
analysis suggests that the arene provides structural order
via a cation- interaction rather than entropic steric
destabilization. Further support for this argument was
sought by construction of two linear free energy
relationships, which relate enantioselectivity to both the
polarizability (black) and the quadrapole moment (blue)
of the arene ring (Figure 3).11,12 The quadrapole moment
and polarizability are physical properties that denote
electron delocalization. The strong linear correlation
shows that this key enantiodetermining interaction is
dependent on the amount of electron delocalization and,
by extension, cation- stabilization.13 These linear free
energy relationships were among the first of their kind to
be applied to asymmetric catalysis and they highlight how
traditional physical organic principles can be used to
quantify non-covalent attractive interactions.
A)
B)
OMe
Me
O
N
OH
4
C)
CF3
t-Bu
OMe
N
Me
15 mol% 6
25 mol% HCl
4Å MS, TBME
-30 °C, 48 h
O
N
Ar
O
S
N
H
N
H
CF3
6
H
H
5
6a
6b
6c
6d
Aryl =
Phenyl
2-Napthyl
9-Phenanthryl
4-Pyrenyl
% ee
25
61
87
95
Figure 2. A) Catalysts synthesized for the asymmetric Claisen
rearrangemeng B)
Plot of calculated vs. experimental
enantioselectivity for the catalysts in A.
They examined known substrate 4, which upon treatment
with
hydrochloric
acid,
undergoes
dehydration/chlorination to form a chlorolactam. They
hypothesized that using a chiral thiourea catalyst would
ionize the chlorolactam and stabilize the charge separated
intermediates through H-bonding. The bound iminium
substrate would then undergo sequential nucleophilic
cyclizations in association with the chiral catalyst. Initial
catalyst screening revealed that the enantioselectivity of
the cyclization was highly dependent on arene size. It
had been shown that arenes are known to bind cations
with increasing strength with increasing arene size and
overall electron density.10
The dependence of
enantioselectivity on arene size implies a cation-
9
Knowles, R. R.; Lin, S.; Jacobsen, E. N. J. Am. Chem. Soc. 2010,
132, 5030.
10
As demonstrated in the asymmetric variant of the Claisen
rearrangement.
Figure 3. A) The asymmetric polycyclization of
hydroxylactams. B) Dependence of enantioselectivity on arene
size.
C) Linear-free energy relationship between
enantioselectivity and polarizability (black) and quadrapole
moment (blue).
11
Mecozzi, S.; West, A. P.; Dougherty, D.A. J. Am. Chem. Soc.
1996, 118, 2307.
12
Ngola, S. M.; Dougherty, D. A. J. Org. Chem. 1996, 61, 4355.
13
Vijay, D.; Sastry, G.N. Phys. Chem. Chem. Phys. 2008, 10, 582.
D)
CF3
A)
2 mol% 8
2 equiv TMSCN
2 equiv MeOH
Ph
N
Ph
Ph
HN
toluene, -30 C
20 h
7
Ph
Ph
R2
R1
R3
X
H
N
O
d1
d4
d3
R1
N
R3
d2
N
H
H
R2
N
O
O
d1
H
d3
O
H
CF3
Ph
N
C
Me tBu
N
Ph
H
O
O
Me
N
O
N
H
N
H
8d
Me
N
H
N
H
Me
Ph
8b
Me
N
Me Me
N
Ph
O
Ph
S
N
H
N
H
8c
Me
Me
N
Me
N
8g
8e
Me
H
S-enantiomer
S
tBu
N
H
Ph
Ph
R-enanti omer
N
H
8a
d2
N
N
N
H
S
N
H
H
H
d4
C
Me tBu
N
Ph
N
H
H
H
N
Ph
S
8
C)
N
Ph
CN
B)
X
Me tBu
N
8f
Me
N
8h
Ph
Me
Figure 4. A) The asymmetric Strecker reaction. B) Computationally proposed transition states with calculated H-bonds shown in color. C)
Catalyst library. D) Linear free energry relationships between the compuationally determined cumulative bond legnths and
experimentally determined transition-state free energy.
The cation- interactions described above demonstrate
that non-covalent attractive interactions can be used in
tandem
to
enhance
reactivity
and
amplify
enantioselectivity. H-bonding donating structures were
employed in each study to generate catalytic reactivity.
While H-bonding was crucial for catalysis, it was not
implicated as a key element for asymmetric induction.
Jacobsen and Zeund have recently reported studies on the
thiourea-catalyzed asymmetric Strecker reaction, which
provide strong evidence for direct H-bonding effects on
enantioselectivity.14 After careful and detailed kinetic
analyses, determination of catalyst structure, and
determination of substrate binding, they were able to
make the assumption that the enantiodetermining step
was the transition from the protonated iminium-cyanide
pair to the bound charge-separated species (Figure 4B).
Based on this assumption, they designed a computational
study to determine the key factors contributing to
enantioselectivity. Experimental results from a range of
synthesized ligands (Figure 4C) showed that small
pertubations in catalyst structure were accompanied by
large changes in enantioselectivity. Computationally
evaluating the influence on enantioselectivity of these
catalysts, they discovered that they could both predict the
trend and quantify enantioselectivity for these catalysts
using the B3LYP/6-31G (d) level of theory. This is one
of the first examples whereby computational analysis
accurately predicted the observed difference in transition
state energies. Evaluating the catalysts employed in this
study, they found no obvious source of steric
interaction/repulsion, which might explain the observed
enantioselectivities. Lack of direct steric repulsion led
them to examine other factors which might be affected by
the perturbations. The strength of H-bonding between
catalyst and substrate would be highly dependent on the
overall catalyst geometry. Because the strength of H14
Zuend, S. J.; Jacobsen, E. N. J. Am. Chem. Soc. 2009, 131, 15358.
bonding
is
highly
distance-dependent,
they
computationally examined the length of all of the Hbonds in the transition state (Figure 4D). Evaluation of
the two H-bonds between the thiourea and cyano group
(d1 + d2) revealed a static bond length regardless of the
catalyst structure for both the R product pathway as well
as the (S) product pathway. Next, they examined the Hbond network between the iminium hydrogen, the cyano
nitrogen, and the amide carbonyl (d3 + d4). Again they
found that the pathway leading to (R) product was not
affected by the length of the H-bonds. However, they
found strong correlation between the total H-bond length
and the experimentally observed enantioselectivity in the
(S) pathway. The H-bonds become destabilized in the S
pathway, leading to higher observed enantioselectivity.
These
results
strongly
implicate
the
carbonyl/cyanide/iminium ion interaction is responsible
for the differences in energy in the diastereomeric
transitions states and is the key factor in determining
facial selectivity.
In each of the above examples, Jacobsen and
coworkers discovered and quantified non-covalent
attractive interactions. These examples demonstrate the
importance of these forces in enantioselective outcomes
and these examples demonstrate the considerable utility
of computational techniques in tandem with physical
organic principles for quantifying these interactions.
Similarly, the studies outlined above rely on non-covalent
stabilization of reaction intermediates to promote
reactivity as well as enantioselectivity, which stands in
contrast to more commonly invoked steric destabilization.
Overall, the application and quantification of these noncovalent attractive interactions could change the entire
design paradigm within asymmetric organocatalysis.