Supramolecular Self-Sorting Networks using Hydrogen-Bonding Motifs

Article abstract of DOI:10.1002/chem.201804791

A current objective in supramolecular chemistry is to mimic the transitions between complex self-sorted systems that represent a hallmark of regulatory function in nature. In this work, a self-sorting network, comprising linear hydrogen motifs, was created. Selecting six hydrogen-bonding motifs capable of both high-fidelity and promiscuous molecular recognition gave rise to a complex self-sorting system, which included motifs capable of both narcissistic and social self-sorting. Examination of the interactions between individual components, experimentally and computationally, provided a rationale for the product distribution during each phase of a cascade. This reasoning holds through up to five sequential additions of six building blocks, resulting in the construction of a biomimetic network in which the presence or absence of different components provides multiple unique pathways to distinct self-sorted configurations.

Full text of DOI:10.1002/chem.201804791

A Journal of
Accepted Article
Title: Supramolecular Self-Sorting Networks Using Hydrogen-Bonded
Motifs
Authors: Heather Coubrough, Stephanie van der Lubbe, Kristina
Hetherington, Aisling Minard, Christopher Pask, Mark
Howard, Celia Fonseca Guerra, and Andrew John Wilson
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To be cited as: Chem. Eur. J. 10.1002/chem.201804791
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Supramolecular Self-Sorting Networks Using Hydrogen-Bonded
Motifs
Heather M. Coubrough,[a,b] Stephanie C. C. van der Lubbe,[c] Kristina Hetherington,[a,b] Aisling Minard,[a,b]
Dr. Christopher Pask,[a] Dr Mark J. Howard,[a] Prof. Dr. Célia Fonseca Guerra*[c,d] and Prof. Dr. Andrew
J. Wilson*[a,b]
Abstract: A current objective in supramolecular chemistry is to mimic
the transitions between complex self-sorted systems that represent a
hallmark of regulatory function in nature. In this work, a self-sorting
network, comprising linear hydrogen motifs, has been created.
Selecting six hydrogen bonding motifs capable of both high-fidelity
and promiscuous molecular recognition gives rise to a complex self-
sorting system that includes motifs capable of both narcissistic and
social self-sorting. Examination of the interactions between individual
components, experimentally and computationally provides a rationale
for the product distribution during each phase of a cascade. This
reasoning holds through up to five sequential additions of six building
blocks, resulting in the construction of a biomimetic network in which
the presence or absence of different components provides multiple
unique pathways to distinct self-sorted configurations.
behaviour.[1, 3] In terms of biomimetic systems that recapitulate
these features, defined supramolecular assemblies employing
multiple consecutive narcissistic (self-loving) and/or social (self-
loathing) integrative self-sorting[4] events have been used to
transition between well-defined
– and in some instances
functional[5] – complexes.[6] The parallel assembly of different
complexes and transition to express different architectural
complexity has also been demonstrated.[5b] However, these
multicomponent systems have typically relied on shape and
geometrical complementarity together with dative coordination
bonds. In contrast, non-integrative systems capable of transition
between different self-sorted configurations are less established
as is the exploitation of weaker interactions e.g. hydrogen-
bonding set within the context of a recognition pattern of donors
(D) and acceptors (A).[7] Achieving this objective is a fundamental
challenge and more accurately mimics many of the bimolecular
associations that control cellular processes including those that
occur within the context of multicomponent protein assemblies
(e.g. the binding of co-activators to transcription factor
complexes).[8]
Introduction
Nature has the ability to assemble multiple functional assemblies
simultaneously in defined locations, and, with temporal
Previously, we described a supramolecular system which
we termed a self-sorting cascade;[9] it exploited both orthogonal
and promiscuous recognition behavior of linear arrays of
hydrogen bonds[10] to achieve sequential self-sorting depending
on which components were present. Comprising four different
hydrogen bonding motifs, four rounds of self-sorting could be
achieved with different complexes formed depending on the
sequence in which the components were added. Furthermore, the
transitions could be triggered (albeit irreversibly) using a light
mediated reaction to unmask one of the H-bonding motifs, thus
mimicking the process of post-translational regulation. In this work,
we studied in greater detail the ability of linear arrays of hydrogen-
bonds to self-sort using a combination of experimental (x-ray
precision.[1] For example, in
a cellular signaling cascade,
individual proteins interact selectively with certain proteins during
one stage of a cascade and then with different proteins at another
stage, driven by protein expression levels and enzymatically
manipulated
post-translational
modifications
(PTMs).[1-2]
Regulatory control in a cellular context thus requires molecular
recognition motifs capable of selective but adaptive recognition
[a]
H. M. Coubrough, K. Paraschiv, A. Minard, Dr. C. Pask, Dr M. J.
Howard, and Prof. Dr. A. J. Wilson
School of Chemistry, University of Leeds, Woodhouse Lane, Leeds
LS2 9JT, United Kingdom
E-mail: a.j.wilson@leeds.ac.uk
1
single crystal and H NMR) and computational (DFT) methods.
[b]
[c]
H. M. Coubrough, K. Paraschiv, A. Minard and Prof. Dr. A. J. Wilson
Astbury Centre for Structural Molecular Biology, University of Leeds,
Woodhouse Lane, Leeds LS2 9JT, United Kingdom
S. C. C. van der Lubbe, Prof. Dr. C. Fonseca Guerra
Department of Theoretical Chemistry and Amsterdam Centre for
Multiscale Modelling, Vrije Universiteit Amsterdam, The Netherlands
E-mail: c.fonsecaguerra@vu.nl
We illustrate that thermodynamically less preferential complexes
can be formed during self-sorting driven by the stability of the
whole system, and that this can be influenced by the configuration
and conformation of the hydrogen-bonding motif. This allowed us
to extend the scope of the self-sorting cascade to six components
and construct cascades that operate in the presence of each other
but with cross-talk, recapitulating a novel aspect of biological
signaling and resulting in a self-sorting network.
[d]
Prof. Dr. C. Fonseca Guerra
Leiden Institute of Chemistry, Gorlaeus Laboratories, Leiden
University, The Netherlands
Supporting information for this article is given via a link at the end of
the document.((Please delete this text if not appropriate))
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Figure 1. The lowest energy dimerisation interactions between the six linear hydrogen bonding motifs 1-6 with dashed lines showing intermolecular hydrogen bonds.
(supporting information Fig. S1a), three of which present a
quadruple hydrogen-bond array.
A single crystal analysis
Results and Discussion
confirmed that AUPy 1 forms a quadruple hydrogen-bonded
homodimer 1·1 in the solid state; in this case with the monomer
adopting the ADAD presenting tautomeric conformer (Fig. 2a).
This is entirely consistent with results observed previously.[11b]
In this work we examined the literature to identify additional H-
bonding motifs 1-2 to add to those employed 3-6 in our previous
study (Fig. 1).[9] Prior work by Sijbesma and co-workers
Similarly, NAPyO
2 may feasibly access two tautomeric
established
that
self-complementary
and
configurations (see supporting information Fig. S1b). Single x-ray
crystal analysis on an isopropyl analogue of NAPyO 7 revealed a
quadruple hydrogen-bonded homodimer 7·7 in which the
monomer was present as the pyrimindinone tautomer resulting in
a DADA array (Fig. 2b).
dialkylaminoureidopyrimidinone (AUPy) motifs e.g.
1
amidonapthyridone (NAPyO) motifs e.g. 2 could be used to form
alternating supramolecular copolymers through-preferential
heterocomplexation, with tunable polymer composition.[11] These
building blocks were thus known to elicit low fidelity recognition
behavior in the same way as ureidopyrimidinone (UPy) 4, an
essential requirement for the assembly of a cascade.[12] Such
variable recognition behavior arises through the different arrays
of donors and acceptors (e.g. DADA, DDAA) presented by
different accessible tautomers/ conformers of each motif. The use
of diamidonaphthyridine (DAN) 3, ureidoimidazole (UIM) 5 and
Pairwise Interactions
The interactions of these two additional components (AUPy
1 and NAPyO 2) with partners were then further investigated
using 1H NMR in CDCl3. The 1H NMR resonances from separate
samples of AUPy 1·1 and NAPyO 2·2 homodimers were
compared to a 1:1 mixture of AUPy 1 and NAPyO 2 (supporting
information Fig. S2). The small yet notable changes in the
chemical shift of the NH signals relative to the homodimers were
indicative of complex formation and consistent with reported
interactions.[11c] Attempted 2D 1H-1H NOESY analyses were
confounded by the presence of exchange peaks for NH/OH
resonances, preventing a more in depth structural interpretation,
although such exchange peaks are entirely consistent with an
interaction between AUPy 1 and NAPyO 2.
amidoisocytosine (AIC)
6 with more restricted molecular
recognition properties enforced by a solitary arrangement of
donors and acceptors in each case was also considered
necessary for effective assembly of a cascade. In the prior study
motifs 3-6 were shown to form a pair of tightly bound heterodimers
3·4 and 5·6 in chloroform resulting in effective self-sorting.
Therefore, our study commenced with a deeper analysis of the
recognition properties of these compounds with an emphasis on
1 and 2.
To further confirm the presence of a heterodimer variable
temperature (VT) NMR analyses were performed (supporting
information Fig. S3). As the temperature was reduced from 277K
to 244K the broad NH/OH signals in the region 9-15 ppm
sharpened and split to reveal additional resonances consistent
Synthesis of Hydrogen Bonding Motifs
The synthesis of AUPy 1 and NAPyO 2 was achieved by
adaptation of previously described methods (see experimental
[11b, 11c]
section and supporting information).
Like UPy 4, AUPy 1
has the potential to adopt four different tautomers/conformers
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Table 1. The Gibbs free energies computed for all dimerization interactions with
respect to the most stable tautomer ADDA in implicit chloroform solvation at the
BLYP-D3(BJ)/TZ2P level of theory (without alkyl chains).
interacting array of dimers seen experimentally.
* denotes the
Hydrogen Bonding Motif
Homodimers
AUPy
Interacting Array
ΔG (kcal mol-1)
ADAD*
AADD
ADAD
AADD*
ADAD*
AADD
-2.2
0.6
AUPy
UPy
-2.6
-6.9
-3.5
7.4
UPy
NAPyO
NAPyO
Heterodimers
AUPy·DAN
UPy·DAN
ADDA·DAAD*
ADDA·DAAD*
ADAD·DADA*
AADD·DDAA
ADDA·DAAD
ADAD·DADA
AADD·DDAA
ADDA·DAAD
ADAD·DADA
AADD·DDAA
-5.0
-4.8
-2.3
4.1
AUPy·NAPyO
AUPy·NAPyO
AUPy·NAPyO
UPy·NAPyO
UPy·NAPyO
UPy·NAPyO
AUPy·UPy
AUPy·UPy
0.0
-2.6
0.8
0.5
-2.4
-3.1
Figure 2. X-ray crystal structures of (a) AUPy 1 and (b) NAPyO 7 homodimers
(carbon is shown in grey, nitrogen in blue, oxygen in red, hydrogens in white
and hydrogen bonds as dashed lines, with distances shown in Å).
Figure 3. Optimized dimer interactions and their Gibbs free energies ΔG between brackets [in kcal mol-1] with respect to their most stable tautomer ADDA. Computed
at the BLYP-D3(BJ)/TZ2P level of theory (without alkyl chains).
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with the presence of homodimers of AUPy 1·1 and NAPyO 2·2 as
well as AUPy·NAPyO 1·2 heterodimer as the dominant species;
at 253 K the ratio of homodimer:heterodimer was observed to be
1:2. This indicates fast exchange between homodimers 1·1/2·2
and heterodimer 1·2 at room temperature. This is a property that
is useful in the context of the cascades/network discussed later,
in that recognition simply needs to translate into a response e.g.
a signal change/distinct spectrum and not necessarily diagnostic
resonances associated with particular complexes. To further
understand the observations gleaned from 1H NMR analyses, we
computed the Gibbs free energies of dimerization (G) at the
BLYP-D3(BJ)/TZ2P level of theory with implicit chloroform
solvation at 298K. The Gibbs free energies for the AUPy 1·1 and
NAPyO 2·2 homodimers were -2.2 and -3.5 kcal mol-1
respectively (Fig. 3, Table 1 and supporting information for
Cartesian coordinates). The lowest energy AUPy·NAPyO 1·2
heterodimer was seen for the ADAD·DADA interacting array with
a Gibbs free energy of -2.3 kcal mol-1. Hence the dimerization
energy of the AUPy 1·1 homodimer is close to that of the
AUPy·NAPyO 1·2 heterodimer, which is consistent with
experimental observations of a mixture of homodimers and
heterodimer at room temperature.
tautomer in the dimer (i.e. excluding Gtaut) the AUPy 1·1 is more
stable as DDAA than as DADA tautomer, and of similar energy to
the calculated UPy 4·4 dimer. It is thus the higher energetic
penalty of switching from the pyrimidinol to the pyrimidinone
tautomer for AUPy that is responsible for its preference to be in
DADA tautomeric form. This may be attributed to the
intramolecular hydrogen bond between the [6]N and ureido NH
(supporting information Fig. S8).
Next the interactions of AUPy 1 and NAPyO 2 with UPy 4
were examined. Previous studies have highlighted the
promiscuous nature of UPy 4 to interact through several hydrogen
bonding arrays.[9, 12] Surprisingly 1H NMR suggested there was no
significant interaction of UPy 4 with AUPy 1 or NAPyO 2 in 1:1
mixtures (supporting information Fig. S4 & S5). A variable
1
temperature H NMR analysis of a 1:1 mixture of NAPyO 2 and
UPy 4 further confirmed narcissistic self-sorting (supporting
information Fig. S6). In such mixtures UPy 4 remained as
homodimer 4·4 and did not show heterodimer interactions with
AUPy (1·4) or NAPyO (2·4).
Taken together these observations raised the following
interesting points: (i) AUPy 1 has a preference to adopt a DADA
pyrimidinol tautomer in the homodimer in contrast to the
extensively observed DDAA pyrimidinone tautomer in UPy 4 and
(ii) AUPy 1 has the ability to form a heterodimer with NAPyO 2
where UPy 4 does not. To resolve these queries we turned to DFT
calculations. These showed the most stable UPy 4·4 and AUPy
1·1 homodimers to have a G of -6.9 and -2.2 kcal mol-1, while
the most stable UPy·AUPy 1·4, UPy·NAPyO 2·4 and
AUPy·NAPyO 1·2 heterodimers have G values of -3.1, -2.6
and -2.3 kcal mol-1, respectively (Fig. 3). Hence the dimerization
energy of UPy (i.e. to form 4·4) contrasts with that of AUPy 1·1 in
being considerably stronger than the potential heterodimers (1·4
and 2·4), which explained why AUPy forms heterodimers while
UPy does not.
Next, the molecular basis for the tautomeric difference
between AUPy and UPy was reconciled. Naturally, the secondary
electrostatic model proposed by Jorgensen[13] and verified by
Zimmerman[14] dictates that the DDAA array should be a higher
affinity interaction than the DADA array, but nevertheless the
DADA tautomer is preferred by AUPy 1·1. Our DFT calculations
revealed that this is caused by the differences in tautomerization
energy Gtaut (supporting information Fig. S7). When considering
the Gibbs free energies of dimerization with respect to the actual
Figure 4. Structural and thermodynamic characterisation of AUPy·DAN 1·8
heterodimer (a) single crystal structure of AUPy·DAN 1·8 heterodimer (carbon
is shown in grey, nitrogen in blue, oxygen in red, hydrogens in white and
hydrogen bonds as dashed lines, with distances shown in Å), (b) ITC
thermograms (top) and binding isotherm for the addition of a solution of AUPy
1 (1 mM) into DAN 3 (0.1 mM) in CHCl3 (bottom).
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We then characterized interaction of the additional
components AUPy 1 and NAPyO 2 with DAN 3 presenting only a
DAAD arrangement of hydrogen bonding functionalities. 1H NMR
analyses on 1:1 mixtures of NAPyO 2 and DAN 3 demonstrated
no interaction as expected given the incompatible linear arrays. In
contrast, 1H NMR analyses on a 1:1 mixture of AUPy 1 and DAN
3 indicated heterodimer 1·3 formation (supporting information Fig.
S9), in a similar manner to the observation of heterodimer 3·4
formation for DAN 3 and UPy 4 (supporting information Fig. S10).
2D 1H-1H NOESY analyses also supported the formation of a
heterodimer with NOE cross peaks between NH signals of both
system; because the ΔG for the UPy 4·4 homodimer is lower (i.e.
more negative) than both heterodimers by 1.9 (AUPy·DAN 1·3)
and 2·1 (UPy·DAN 3·4) kcal mol-1, UPy dimerizes with itself
instead of with DAN, and the AUPy 1·1 homodimer consumes two
equivalents on DAN to form the AUPy·DAN 1·3 heterodimer.
Even though calculations reveal AUPy·DAN 1·3 is 2.8 kcal mol-1
more stable than the AUPy 1·1 homodimer, the requirement to
maximise hydrogen-bonding interactions dictates this behaviour.
To provide further evidence that the overall number of hydrogen
bonds in the system must first be maximised before considering
the strength of the dimerization interaction and lowest energy
AUPy 1 and DAN 3 (supporting information Fig. S11). Additionally, conformers, a further 1H NMR experiment was performed with
single crystal diffraction studies on a co-crystal of AUPy 1 and
DAN (isopropyl analogue) revealed the anticipated
DAN 3, AUPy 1 and UPy 4 in 2:1:1 ratio (supporting information
Fig. S12). This predictably resulted in an equal amount of AUPy-
DAN 1·3 and UPy·DAN 4·3 heterodimers with no homodimers
present. Here the excess of DAN 3 drives the formation of UPy-
DAN 4·3 heterodimer over the UPy 4·4 homodimer, despite an
energetic bias towards the latter.
Finally, the AUPy-DAN 1.3 heterodimer was also shown to
‘win-out’ in the presence of NAPyO 2. On the addition of DAN 3
to the weak AUPy·NAPyO 1·2 heterodimer, NAPyO 2 is displaced
resulting in formation of AUPy·DAN 1·3 heterodimer and NAPyO
2·2 homodimer (supporting information Fig. S13). This can be
readily explained in terms of both maximising the number of
8
ADDA·DAAD 1·8 heterodimer interaction as expected (Fig. 4a).
Isothermal titration calorimetry confirmed a strong interaction with
an association constant of Ka=106 in chloroform (Fig. 4b). We next
tested which dimers would “win-out” when AUPy 1, DAN 3 and
1
UPy 4 were combined in a 1:1:1 ratio. The H NMR data were
indicative of a mixture of UPy 4·4 homodimer and AUPy·DAN 1·3
heterodimer (Fig. 5), consistent with prior observations.[11c] Our
DFT analyses indicated no significant Gibbs free energy
difference ΔG between UPy·DAN 3·4 (-4.8 kcal mol-1) and
AUPy·DAN 1·3 (-5.0 kcal mol-1). Thus, the energetic difference
between the two heterodimers fails to explain preferential
AUPy·DAN (1·3) heterodimer formation. Instead, the behaviour is
explained by considering the free energy change in this system
and the additive effects of each dimer formed. Again, the high
stability of the UPy 4·4 homodimer drives the behaviour of the
hydrogen bonds in
a system and association strength.
Unsurprisingly DFT computations mirror these experimental
observations; AUPy·NAPyO 1·2 and AUPy·DAN 1·3
heterodimers have a ΔG of -2.3 and -5.0 kcal mol-1.
Figure 5. Analysis of pairwise interactions and preferences for AUPy 1, DAN 3 and UPy 4 by 1H NMR (10 mM, CDCl3) (a) AUPy 1, (b) 1:1 AUPy 1: DAN 3, (c) 1:1:1
AUPy 1: DAN 3: UPy 4, (d) 1:1 DAN 3: UPy 4 (e) UPy 4.
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Figure 6. Five component signalling cascade studied by 1H NMR (10 mM, CDCl3) (a) AUPy 1, NAPyO 2, DAN 3, UIM 5 and AIC 6, (b) AUPy 1, NAPyO 2, UIM 5
and AIC 6, (c) AUPy 1, UIM 5 and AIC 6, (d) AUPy 1, UIM 5 (e) AUPy 1.
interaction between AIC.UIM 6.5 was unchanged, but small
changes in chemical shifts of the NH resonances of AUPy 1 were
observed, consistent with formation of AUPy·NAPyO 1·2 as the
dominant species comprising either component (as previously
discussed). The cascade was completed by the addition of DAN
3 (Fig. 6a). The AIC.UIM 6·5 heterodimer remained with no
resonances in the 1H NMR affected. However a significant upfield
shift for proton H4 and sharpening of NH resonances for AUPy 1
indicated formation of AUPy·DAN 1·3 and the displacement of
NAPyO 2 from complexation with AUPy 1 (Supporting information
Fig. S12). Based on this reasoning the final mixture was
comprised of AUPy·DAN 1·3 and AIC.UIM 6·5 heterodimers as
well as NAPyO.NAPyO 2·2 homodimer (as predicted) and a clear
pathway of sequential self-sorting established for five
components.
Self-sorting cascades
Having characterized the pairwise dimerization behaviour of
the individual components, this allowed the construction of a
number of self-sorting cascades. The simplest of which was
conceived though the addition of NAPyO 2 to AUPy 1 followed by
the addition of DAN 3 as described above (supporting information
Fig. S13). More complex self-sorting cascades exploiting five
hydrogen bonding motifs were also investigated (Fig. 6a).
Beginning with AUPy·AUPy 1·1 homodimer (Fig. 6e) the addition
of UIM 5 (Fig. 6d) resulted in a small shift in the H4 resonance of
AUPy 1 and broadening of the NH signals, consistent with weak
interaction AUPy·UIM 1·5 heterodimer formation (supporting
information Fig. S14). The AIC 6 motif was then added to the
mixture (Fig. 6c) resulting in formation of UIM·AIC.5·6 indicated
by the downfield shift in the H24 resonance and broadening of the
H20 resonance of UIM 5 (supporting information Fig. S15).
Concomitant recovery of the AUPy homodimer 1·1 was observed
on the basis of the restoration of its NH resonances towards the
expected frequency. Upon the addition of NAPyO 2 (Fig. 6b) the
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1
A series of H NMR experiments were then performed to
demonstrating the absence of clear speciation may be tolerated
in cascades (see earlier discussion on AUPy·NAPyO 1·2). AIC 6
was then added (Fig. 7c) resulting in strong heterodimer formation
with UIM 5 (illustrated by the downfield shift of H2, supporting
information Fig. S14), and simultaneous reformation of the UPy
4·4 and AUPy 1·1 homodimers. Formation of the AUPy·NAPyO
1·2 heterodimer occurred on addition of NAPyO 2 to the cascade
in the presence of UPy 4·4 homodimer and UIM·AIC 5·6
heterodimers (Fig. 7b). Addition of DAN 3, as expected, disrupted
1·2 complexation resulting in AUPy·DAN 1·3 heterodimer and
exemplify a six-component cascade (Fig. 7). The first six
component cascade (pathway E, see Fig. 9) initiated with UPy 4·4
homodimer; addition of AUPy 1 lead to no change in chemical
shifts consistent with narcissistic self-sorting of UPy 4·4 and AUPy
1·1 homodimers (Fig. 7e). Upon the addition of UIM 5; UPy.UIM
4·5 and AUPy.UIM 1·5 heterodimers were formed as major
products (Fig. 7d). This was indicated by the upfield shift and
broadening of H18 of UPy 4 as well as the upfield shift of H4 and
broadening of NH signals of AUPy 1, in line with
heterodimerization observed in the two-component mixture
(supporting information Fig. S14&16). Noteworthy here, is the fact
that distinct spectral changes are sufficient to distinguish this
phase of the cascade from the preceding and subsequent phases,
NAPyO 2·2 homodimers (Fig. 7a). Thus,
a final product
distribution with four major components AUPy·DAN 1.3, UIM·AIC
5·6 heterodimers and NAPyO 2·2, UPy 4·4 homodimers was
observed.
Figure 7. Pathway E 1H NMR (500 MHz, 10 mM, CDCl3) six component signalling cascade (a) AUPy 1, NAPyO 2, DAN 3, UPy 4, UIM 5, and AIC 6, (b) AUPy 1,
NAPyO 2, UPy 4, UIM 5, and AIC 6, (c) AUPy 1, UPY 4, UIM 5, and AIC 6, (d) AUPy 1, UPy 4, and UIM 5, (e) AUPy 1 and UPy 4 (f) UPy 4.
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Figure 8. Pathway G 1H NMR (500 MHz, 10 mM, CDCl3) orthogonal signalling cascade (a) AUPy 1, NAPyO 2, DAN 3, UPy 4, UIM 5, and AIC 6, (b) AUPy 1, NAPyO
2, UPy 4, UIM 5, and AIC 6, (c) AUPy 1, NAPyO 2, UPY 4 and UIM 5 (d) AUPy 1, NAPyO 2 and UPy 4, (e) AUPy 1 and UPy
self-sorting transitions occur, two in one channel and two in the
other, however the transitions do not cross over resulting in
orthogonal cascades.
Orthogonal self-sorting cascade
To develop cascades occurring in parallel (but comprising
components capable of cross-talk) an approach to perform two
orthogonal self-sorting cascades (Pathway G, Fig. 8) was
developed. The aim was to create two parallel cascades which
can operate in sequence in spite of the ability of complexes from
both cascades to interact with one another in different scenarios.
Starting with a mixture of UPy 4·4 and AUPy 1·1 homodimers (Fig.
8e) the cascade could be split in two with UPy 4·4 at the head of
one channel and AUPy 1·1 at the head of the other. On the
addition of NAPyO 2 (Fig. 8d); the “UPy channel” is unchanged
whereas AUPy 1 interacts with NAPyO 2 to form AUPy·NAPyO
1·2 heterodimer. Upon addition of UIM 5 to this three-component
mixture (Fig. 8c); the “AUPy channel” is unchanged and UPy·UIM
4·5 heterodimer formed in the UPy channel. With the addition of
AIC 6 (Fig. 8b); the “AUPy channel” is unchanged through a
further stage but in the “UPy channel” UPy·UIM 4·5 heterodimer
is disrupted to form UPy 4·4 homodimer and UIM·AIC 5·6
heterodimer. The cascade is completed with the addition of DAN
3; here the “UPy channel” is unchanged but DAN 3 interacts with
AUPy 1 in the “AUPy channel” to form AUPy·DAN 1·3
heterodimer liberating NAPyO 2·2 homodimer. Overall four social
Self-sorting network
To elaborate a self-sorting network, several different additional
cascades were exemplified; understanding potential hydrogen
bonding interactions between motifs 1-6 was key in creating a
self-sorting network with intersecting pathways (Fig. 9). By
1
comparing the H NMR spectra of each mixture with the distinct
chemical shifts of heterodimers and homodimers the major
components in each pathway were identified. Hence several
different self-sorting pathways could be plotted together based on
their product distribution, resulting in a network of diverging and
converging paths with the same end point. For example, pathway
B (red Fig. 9) initiates with UPy 4·4 homodimer and on addition of
DAN 3 led to production of DAN·UPy 3·4 heterodimer (supporting
information Fig. S18e). Pathway B continues with the addition of
AUPy 1 resulting in disassembly of DAN·UPy 3·4 heterodimer at
the expense of DAN·AUPy 3·1, together with regeneration of UPy
4·4 homodimer (supporting information Fig. S18d). The hydrogen
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bonding interactions are unchanged on the addition of NAPyO 2
which is present as 2·2 homodimer (supporting information Fig.
S18c). UIM 5 is able to interfere with the UPy 4·4 homodimer
interactions to form UPy.UIM 4.5 heterodimer (supporting
information Fig. S18b) which is in turn disassembled to form
UIM.AIC 5.6 heterodimer with concomitant UPy 4·4 homodimer
formation on addition of AIC 6 (SI Figure16a). Pathway C (yellow
Fig. 9) takes a different route from pathway B in that UIM 5 and
AIC 6 are successively added to the DAN·UPy 3·4 heterodimer
(considered here as an interchange) to create UPy·UIM 4·5 and
UIM·AIC 5·6 heterodimers successively (supporting information
Fig. S19c-d). The ability of UIM 5 to disrupt the DAN·UPy 3·4
heterodimer is moderate, and a series of low-fidelity complexes
are formed –nonetheless, the resultant 1H NMR spectrum is
diagnostic of a distinct state within the network, and, the addition
of AIC 6 restores a well-resolved spectrum indicative of a well-
defined self-sorted configuration. Finally, in pathway C addition of
AUPy 1 switches the configuration from DAN·UPy 3·4 and
UIM·AIC 5·6 to AUPy·DAN 1·3, UPy 4·4 and UIM·AIC 5·6 with
subsequent addition of NAPyO 2·2 promoting no change in the
distribution of the other components (supporting information Fig.
S19a-b). Pathways A, D, E and F further exemplify the different
network configurations that can be obtained depending on which
components are present and therefore expressed in the system
(see supporting information Fig. S19, 20-21 for experimental
data).
Figure 9. Schematic showing the self-sorting behaviour of pathways A to G in forming hydrogen bonding dimers
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1868220 contains the supplementary crystallographic data for this paper.
These data can be obtained free of charge from the Cambridge
Crystallographic Data Centre via www.ccdc.cam.ac.uk/data_request/cif.
Conclusions
Detailed analyses of molecular recognition behavior of hydrogen
bonding motifs by experiment and computation has allowed a
complex self-sorting network made up of several signaling
cascades to be created. The sequential addition of six linear
hydrogen motifs has led to cascades capable of both narcissistic
and social self-sorting phases as well as a mixture of both.
Through the examination of interactions between individual
components of each cascade, the product distribution of the
overall system can be understood in terms of orthogonal
recognition. The varying degrees of fidelity and promiscuity of the
hydrogen bonding interactions of these motifs and critically an
understanding of their behavior was essential in developing the
cascades comprising the network. These cascades include for the
first-time parallel cascades that operate in the presence of each
other, but which are capable of cross-talk. Future studies will
center on exploiting these motifs as components of self-sorting
and reconfigurable materials, on developing reversible transitions
between the different phases of the cascade. Beyond this,
developing approaches to temporarily perturb the system may
provide access to out-of-equilibrium networks with emergent
behavior.
Crystal structure determination for 7: Single crystals were grown by the
slow evaporation of 7 in acetonitrile. X-Ray diffraction data were collected
at the University of Leeds. Crystal data. C12H13N3O2, M = 231.25, crystal
size 0.15 × 0.06 × 0.03 mm3, monoclinic, a = 4.8837(11), b = 22.962(4), c
= 9.9321(18) Å , α = 90, β = 101.26(2), γ = 90 °, U = 1092.4(4) Å3, T =
120.00(10) K, P21/n, Z = 4, l = 0.811 mm−1, λ = 1.54184 [Cu–Kα], 4018
reflections measured, 2121 unique (Rint = 0.0500), observed (I > 2r(I)).
The final R1 was 0.0832 (observed reflections 0.1048) and wR(F2) was
0.2057 (all data 0.2223) for 164 parameters. CCDC 1868221 contains the
supplementary crystallographic data for this paper. These data can be
obtained free of charge from the Cambridge Crystallographic Data Centre
via www.ccdc.cam.ac.uk/data_request/cif.
Crystal structure determination for 1.8: Single crystals were grown by
the slow evaporation of a 1:1 mixture of 1 and 8 in acetonitrile. X-Ray
diffraction data were collected at the University of Leeds. Crystal data.
C33H51N9O4, M = 637.82, crystal size 0.29 × 0.11 × 0.08 mm3, monoclinic,
a = 9.52157(15), b = 15.8558(3), c = 22.3751(3) Å , α = 90, β = 92.0659(13),
γ = 90 °, U = 3375.81(9) Å3, T = 119.99(13) K, P21/n, Z = 4, l = 0.684 mm−1
λ = 1.54184 [Cu–Kα], 13422 reflections measured, 6628 unique (Rint
,
=
0.0348), observed (I > 2r(I)). The final R1 was 0.0412 (observed reflections
0.0541) and wR(F2) was 0.0996 (all data 0.1084) for 442 parameters.
CCDC 1868219 contains the supplementary crystallographic data for this
paper. These data can be obtained free of charge from the Cambridge
Crystallographic Data Centre via www.ccdc.cam.ac.uk/data_request/cif.
Experimental Section
General considerations: Solvents and reagents were purchased from
Sigma Aldrich or Fisher Scientific and used without further purification
unless otherwise stated. Where anhydrous solvents were required,
dichloromethane, chloroform, tetrahydrofuran and acetonitrile were
obtained from the in-house solvent purification system Innovative Inc.
PureSolv®. Anhydrous pyridine was placed over KOH for 24 hours before
being refluxed for 2 hours and distilled over Linde 5Å molecular sieves and
solid KOH before use. All non-aqueous reactions were carried out under a
nitrogen atmosphere. Chloroform-d was placed on CaCl2 before being
distilled over Linde 5A molecular sieves before use in 1H NMR cascade
experiments. Analytical thin layer chromatography was performed on
Merck Kieselgel 60 F254 0.25 mm pre-coated aluminium plates. Product
NOESY data acquisition and processing: Phase sensitive 1H-1H
NOESY experiments were performed on a 1:1 mixture of components at
50 mM concentration with respect to each component in CDCl3 solvent.
Spectra were recorded using a 750 ms mixing time with 256 increments,
2048 data points on a JEOL ECA600ii spectrometer at 298 K operating at
14.1 T (600 MHz for 1H).
ITC experiments: ITC experiments were carried out using Microcal
ITC200i instrument (Malvern) at 25°C in chloroform. 100 μM DAN 3 was
present in the cell and titrated with 1 mM AUPy 1 loaded into the syringe
using 26, 1.4 μL injections with 120 s spacing between the injections for
26 injection. Heats of chloroform dilution was subtracted from each
measurement raw data. Data was analysed using Microcal Origin 8 and
fitted to a one-binding site model.
spots were visualised under UV light ((λmax
= 254 nm). Flash
chromatography was carried out using Merck Kieselgel 60 silica gel.
Nuclear magnetic resonance spectra were obtained at 298 K (unless
stated) using a Bruker AV500 spectrometer operating at 11.4 T (500 MHz
for 1H) and JEOL ECA600ii operating at 14.1 T (150 MHz for 13C) and
NOESY spectra as stated. Infra-red spectra were obtained using a Perkin-
Elmer FTIR spectrometer where absorption maxima (ῡmax) are quoted in
wavenumbers (cm-1) and only structurally relevant absorptions have been
included. High Resolution Mass Spectra (HRMS) were recorded on a
BrukerDaltonicsmicroTOF using electrospray ionisation (ESI). Detailed
synthetic procedures and characterization are given in the Supporting
information.
Molecular structure calculations: The computations were carried out by
using the density functional theory-based program Amsterdam Density
Functional (ADF) 2017.108[15] at the BLYP-D3(BJ)/TZ2P[16] level of theory,
which is known to accurately reproduce hydrogen bond strengths and
lengths.[17] Solvent effects were accounted for by using the implicit
conductor-like screening model (COSMO), in which the solute molecule is
surrounded by a dielectric medium.[18] All optimized structures have been
verified to be true minima (zero imaginary frequencies). The molecular
figures were illustrated using CYLview.[19] Full computational details are
given in the Supporting Information.
Crystal structure determination for 1: Single crystals were grown by the
slow evaporation of 1 in acetonitrile. X-Ray diffraction data were collected
at the University of Leeds. Crystal data. C17H31N5O2, M = 337.47, crystal
size 0.21 × 0.07 × 0.04 mm3, triclinic, a = 5.1924(6), b = 11.8545(15), c =
15.3976(10) Å , α = 97.911(8), β = 93.859(7), γ = 102.021(10) °, U =
913.65(17) Å3, T = 120.3(7) K, P-1, Z = 2, l = 0.661 mm−1, λ = 1.54184
[Cu–Kα], 6466 reflections measured, 3410 unique (Rint = 0.0462),
observed (I > 2r(I)). The final R1 was 0.0532 (observed reflections 0.0774)
and wR(F2) was 0.1306 (all data 0.1468) for 232 parameters. CCDC
Acknowledgements
This work was supported by the EPSRC (EP/KO39292/1). HC
thanks the the University of Leeds for a Leeds Anniversray
Research Scholarship. CFG and SL thank the Netherlands
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Organization for Scientific Research (NWO/CW) for financial
support.
Keywords: hydrogen-bonding • biomimetic chemistry • self-
sorting • supramolecular chemistry • molecular recognition.
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Entry for the Table of Contents
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Heather M. Coubrough, Stephanie C. C.
van der Lubbe, Kristina Paraschiv,
Aisling Minard, Dr. Christopher Pask, Dr
Mark J. Howard, Prof. Dr. Célia Fonseca
Guerra* and Prof. Dr. Andrew J. Wilson*
Page No. – Page No.
A self-sorting network, comprising linear hydrogen motifs, has been created
whereby six hydrogen bonding motifs capable of both high-fidelity and promiscuous
molecular recognition give rise to a complex self-sorting system.
Supramolecular Self-Sorting
Networks Using Hydrogen-Bonded
Motifs
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