The concurrence of enzymatic reaction and ligand-receptor interactions is common for proteins, but rare for small molecules and has yet to be explored. Here we show that ligand-receptor interaction modulates the morphology of molecular assemblies formed by enzyme-instructed assembly of small molecules. While the absence of ligand-receptor interaction allows enzymatic dephosphorylation of a precursor to generate the hydrogelator that self-assembles to form long nanofibers, the presence of the ligand-receptor interaction biases the pathway to form precipitous aggregates containing short nanofibers. While the hydrogelators self-assemble to form nanofibers or nanoribbons that are unable to bind with the ligand (i.e., vancomycin), the addition of surfactant breaks up the assemblies to restore the ligand-receptor interaction. In addition, an excess amount of the ligands can disrupt the nanofibers and result in the precipitates. As the first example of the use of ligand-receptor interaction to modulate the kinetics of enzymatic self-assembly, this work not only provides a solution to evaluate the interaction between aggregates and target molecules but also offers new insight for understanding the emergent behavior of sophisticated molecular systems having multiple and parallel processes.
The concurrence of enzymatic reaction and ligand-receptor interactions is common for proteins, but rare for small molecules and has yet to be explored. Here we show that ligand-receptor interaction modulates the morphology of molecular assemblies formed by enzyme-instructed assembly of small molecules. While the absence of ligand-receptor interaction allows enzymatic dephosphorylation of a precursor to generate the hydrogelator that self-assembles to form long nanofibers, the presence of the ligand-receptor interaction biases the pathway to form precipitous aggregates containing short nanofibers. While the hydrogelators self-assemble to form nanofibers or nanoribbons that are unable to bind with the ligand (i.e., vancomycin), the addition of surfactant breaks up the assemblies to restore the ligand-receptor interaction. In addition, an excess amount of the ligands can disrupt the nanofibers and result in the precipitates. As the first example of the use of ligand-receptor interaction to modulate the kinetics of enzymatic self-assembly, this work not only provides a solution to evaluate the interaction between aggregates and target molecules but also offers new insight for understanding the emergent behavior of sophisticated molecular systems having multiple and parallel processes.
This article reports
the first use of the ligand–receptor
interaction to regulate enzymatic self-assembly and emergent properties
of the assemblies of small molecules. Self-assembly of small molecules
is a thermodynamically favorable process during which small molecule
monomers assemble to form large supramolecular structures.[1−9] Typically these supramolecular structures are static with properties
dictated by their constituents.[4] In nature,
however, it is dynamic supramolecular structures and emergent properties
of the assemblies which are the most prevalent.[10,11] A prominent process is reversible protein phosphorylation and dephosphorylation
that regulates many essential cellular functions.[12] For example, tyrosine phosphorylation in VAV protein is
a key mechanism in regulating the ligand–receptor interaction,
thus further activating enzymes for immune responses.[13] Additionally, the complex protein folding process has a
well-established reliance on dephosphorylation of ATP by chaperone
proteins.[14,15] Meanwhile, immunological studies show that
enzymatic transformation generates death ligands (e.g., TNF, TRAIL),
which bind to cell death receptors to initiate oligomerization processes
that control cell fates. A fundamental feature of these processes
in living systems is the concurrence of enzymatic reaction and ligand–receptor
interactions (e.g., enzymes or pseudo enzymes as molecular scaffolds
for self-assembly),[16] which results in
sophisticated control of protein–protein interactions. This
fact raises the possibility of employing small molecules to mimic
this essential process for modulating protein–protein interactions,
which would be a novel strategy for developing new therapeutics. Despite
their significance, such an approach has received limited exploration
because of the limited number of well-defined ligand–receptor
systems of small molecules. Recently, we reported that enzymatic reaction
is able to dimerize the ligand to mimic the activation of signal transduction.[17] It would be highly desirable to use ligand–receptor
interactions to modulate the outcome of enzyme-instructed self-assembly
(EISA)[18−23] of small molecules because morphological differences of the nanoscale
assemblies may elicit different cellular responses.[24−28] However, the use of ligand–receptor interactions
for precisely controlling the kinetic behavior of small molecules
remains challenging.To understand the complex behavior of sophisticated
molecular systems
undergoing multiple and/or parallel processes, we choose to explore
small molecules that are substrates of enzymes and are participants
of ligand–receptor interactions. Specifically, we synthesized
a small heptapeptide, Nap-FFYGGaa (1), which self-assembles
to form nanofibers or nanosheets in aqueous solution. Phosphorylated 1 (i.e., 1P, phosphorylated at tyrosine residue)
is a substrate of alkaline phosphatase (ALP) and a receptor of vancomycin
(2). Our study reveals that the assemblies of 1 exhibit emergent properties of assembled molecules,[29,30] which drastically affect the ligand–receptor interaction
between the assemblies and the ligand, in effect “switching
off” the ligand–receptor interaction between 2 and 1. On the other hand, the ligand–receptor
interaction between 2 and 1P is able to
bias EISA of 1 to generate aggregates containing short
nanofibers, an observation that differs from EISA of 1 in the absence of 2. Additionally, during EISA of 1 in the presence of 2, short fibers emerge first,
followed by aggregation and disruption of fibers, leading to formation
of a precipitate. This transient fiber formation is coupled with a
time-dependent change in the viscoelastic properties of the solution
of 1, 2, and ALP, which is not observed
when one of the components is missing, the hallmark of emergent behavior.
As shown in Scheme , immediately after enzymatic dephosphorylation, 1 is
“monomeric” and is able to bind the ligand (2), or the enzyme can dephosphorylate the complex of 1P and 2. Thus, the binding between 1 and 2 favors an alternative pathway of assembly (i.e., different
from the supramolecular polymerization of 1 observed
without 2), leading to precipitation. While 2 shows no measurable binding to assemblies of 1, the
addition of a surfactant Tween-80 (Tw-80) breaks up the assemblies
of 1 and restores binding between 1 and 2. Isothermal titration calorimetry (ITC) measurement in the
presence of surfactant, in fact, serves as a facile method to study
interactions between ligands and receptors when either are prone to
aggregate.
Scheme 1
Illustration of Ligand–Receptor Interaction
of Small Molecules
Dictating the Pathways of EISA
While proteins usually change their conformation or shape
upon
enzymatic reaction to regulate ligand–receptor interaction
for specific functions, as shown in the case of inherently disordered
proteins,[31,32] small molecules, in general, barely exhibit
large conformational differences upon enzymatic reaction. As the first
example illustrating reciprocal modulation between ligand–receptor
interaction and enzymatic self-assembly, this work provides useful
insights for developing nanoscale assemblies of small molecules for
controlling biological and cellular processes, understanding the emergent
behavior of sophisticated molecular systems undergoing multiple and
parallel processes, and further offers a general approach to control
the transformation of small molecules in the context of ligand–receptor
interactions.
Results and Discussion
Molecular Design and Synthesis
We chose vancomycin
(2) and a d-Ala-d-Ala derivative (1) as the ligand–receptor pair because of their well-established
and specific interactions, as demonstrated by Walsh,[33,34] Williams,[35] and Whitesides[36,37] as well as other groups.[38,39] Recently, we have shown
that ligand–receptor interaction modulates the cytotoxicity
of molecular aggregates.[40,41] Encouraged by these
results, we designed a small molecule (Nap-FFpYGGaa (1P)) and the hydrogelator 1. The heptapeptide
and various derivatives (Scheme ) were synthesized by standard solid-phase peptide
synthesis (SPPS) procedures (see Supporting Information (SI)) on a 2-chlorotrityl chloride resin,[42] further purified by HPLC on a reverse phase C18 column, and lyophilized
to give the peptides as fine white powders in approximately 80% yield.
Phosphorylated tyrosine was synthesized following previously reported
methods[43] and the free amine further protected
by an Fmoc group for SPPS. The overall yield of 1P is
about 80%, based on resin loading.
Scheme 2
Molecular Structures of the Heptapeptidic
Precursor 1P and Its Corresponding Hydrogelator 1
Ligand Modulates Enzymatic
Self-Assembly
To understand
how self-assembly affects the ligand–receptor interaction and
how the ligand–receptor interaction modulates the process or
behavior of enzymatic self-assembly, we used ALP to catalyze dephosphorylation
of 1P without and with the presence of 2. As shown in Figure A, without ALP, the addition of 1 equiv of 2 into the
solution of 1P (500 μM) results in a colloidal
suspension, which forms precipitates depending on pH and concentration,
indicating strong intermolecular interaction between 1P and 2. Transmission electron microscopy (TEM) shows
that the morphology of the aggregates is largely unstructured (Figure A). In the absence
of 2, ALP (1.25 U/mL) converts 1P to 1, which, as expected, self-assembles to form long nanofibers
(Figure B). When the
concentration of 1P is 500 μM, the enzyme-induced
formation of the nanofibers results in a viscous mixture. The simultaneous
addition of 2 (1 equiv) and ALP (1.25 U/mL) into a solution
of 1P (500 μM) induces formation of large aggregates,
which cluster together and form precipitates (Figure C) over time. Although a self-supporting
gel was only made upon changing the pH of a 4 mM solution of 1 to pH 6.4 (Figure S2), the addition
of ALP into the solution of 1P (500 μM) and 2 (500 μM) also yields gel pieces that are sufficiently
stable for rheology measurement (Figures S3 and S4). These results confirm that 1 is a hydrogelator.
The formation of precipitates over time agrees with an observed decrease
in the storage modulus or critical strain of the mixture over 24 h
(Figure S3). Furthermore, the time dependence
of the changes in storage and loss moduli are an emergent property
of the combination of all three components. However, 2 days after
using ALP to generate 1 from 1P, the addition
of 1 equiv of 2 to the solution of 1 hardly
yields any precipitates after 24 h. TEM reveals that the nanofibers
(Figure D) are similar
to those formed by mixing 1P and ALP without the post-self-assembly
addition of 2. This result indicates that, being a kinetically
trapped state following EISA of 1, the assemblies of 1 hardly favor binding with 2. Interestingly,
while the direct addition of 1 in water results in a
suspension consisting of nanoribbons (Figure E), TEM reveals small unstructured aggregates
on the edge of the nanoribbon of 1 after the addition
of 2 (Figure F). On the other hand, the addition of 5 equiv of 2 into a 500 μM suspension of 1 almost completely
destroys the nanoribbons formed by 1 and affords an opaque
colloidal precipitate (Figure S5) 24–48
h after the addition, indicating that high concentrations of 2 shift the equilibrium toward binding between 1 and 2.
Figure 1
TEM images of (A) suspension of 1P and 2; (B) 1P and ALP; (C) 1P, 2, and ALP; (D) 1P treated with ALP for 2 days
and then 2 was added; and (E) 1 and (F) 1 and 2 in water. [1P]0 = [1]0 = [2]0 =
500 μM,
ALP = 1.25 U/mL, pH = 7.4.
TEM images of (A) suspension of 1P and 2; (B) 1P and ALP; (C) 1P, 2, and ALP; (D) 1P treated with ALP for 2 days
and then 2 was added; and (E) 1 and (F) 1 and 2 in water. [1P]0 = [1]0 = [2]0 =
500 μM,
ALP = 1.25 U/mL, pH = 7.4.
ITC of Binding and Stability of the Assembly
To investigate
the interaction between 2 and the d-Ala-d-Ala derivatives (i.e., 1P and 1),
we used ITC to estimate the dissociation constant (Kd) of the binding between 1P and 2. As shown in Figure A, 1P binds with 2 in a 1:1 ratio, with
a Kd of 108 μM. This result agrees
well with relatively tight binding between 2 and d-Ala-d-Ala. Titration in the presence of ALP appears
to give a dissociation constant of 10 μM (Figure S6). This result suggests that the dephosphorylation
process and subsequent self-assembly still permit the binding of 2 with 1P or 1. In contrast, assemblies
of 1 hardly bind with 2. The heating profile
(Figure B) of titration
of 2 into a suspension of 1 is similar to
that of the dissociation of the dimers of 2 (Figure S7), suggesting that the interaction between
assembled 1 and 2 is too weak to be measured
by ITC. In fact, this is the first case where 2 shows
negligible binding with a d-Ala-d-Ala derivative.
Figure 2
ITC of
(A) 1P and (B–D) 1 with 2 at different concentrations of Tw-80 for the determination
of dissociation constant (Kd) and stoichiometry
(n). Negative peaks indicate an exothermic release
of heat.
ITC of
(A) 1P and (B–D) 1 with 2 at different concentrations of Tw-80 for the determination
of dissociation constant (Kd) and stoichiometry
(n). Negative peaks indicate an exothermic release
of heat.Considering that the assemblies
of a hydrogelator containing d-Ala-d-Ala,[17,44] in a previous report,
are able to bind with 2, the lack of binding between 2 and the assemblies of 1 is surprising. To understand
this result, we synthesize control molecules Nap-ffpyGGaa
(3P) and the corresponding self-assembling molecule, 3, by replacing the l-amino acid residues, FFY, in 1P or 1, with their d-amino acid enantiomers,
ffy. Like 1P, 3P binds with 2 with a Kd of 82 μM. Similarly
to the assemblies of 1, the assemblies of 3 barely bind with 2 (Figure S8). This control experiment excludes the possibility that the conformation
of the receptor (i.e., 1 or 3) weakens the
binding between 1 (or 3) and 2. Moreover, this result confirms that the assemblies of small molecules,
indeed, differ considerably from their monomeric building blocks.
As expected, upon the mutation of d-Ala-d-Ala to l-Ala-l-Ala, the resulting molecule, 4P (or 4), is unable to bind with 2 (Figure S8), which further confirms that the ligand–receptor
interaction between 2 and 1P, 1, 3P, or 3 still relies on the binding
between vancomycin and d-Ala-d-AlaTo compare
the complex parallel processes occurring during the
ITC experiments and to gain insights into the supramolecular behavior
observed in the TEM in Figure , we examined the total heat released over the entire ITC
experiment. We carried out three sets of titrations (in PBS buffer
and at pH 7.4): 1P to (i) 2 alone, (ii)
to ALP alone, and (iii) to a solution of 2 and ALP ([ALP]0 = 1.67 U/mL). Integrating the heat release profiles for each
titration yields the total heat released for each titration, from
which the total heat released by dilution of 1P is subtracted.
The total heat release is −4261 μJ for titration of 1P to 2, −4653 μJ for titration
of 1P to ALP, and −7186 μJ for titration
of 1P to 2 and ALP (Figure S9), indicating that formation of nanofibers by dephosphorylation
of 1P is more enthalpically favorable than binding of 1P and 2 alone. Importantly, the heat released
from binding of 1P and 2 is comparable to
heat released from dephosphorylation of 1P. This result
agrees with hardly any disruption of fibers of 1 formed
by dephosphorylation of 1P following the addition of 2 (Figure D). However, the fibers of nanosheets of 1, being kinetically
trapped, can slowly transform over several weeks to months to a precipitate
after the addition of 5 equiv of 2. Furthermore, as the
total heat released by titration of 1P to a solution
of 2 and ALP is significantly larger than the heat released
by simple dephosphorylation of 1P, 2 likely
provides a low-energy intermediate along the fibrilization pathway
of 1, which drives the hydrogelator to form the unstructured
aggregates that contain 1 and 2 (Figure C).
Addition of
Surfactant Restores the Ligand–Receptor Interaction
A series of studies by Shoichet et al. have revealed that the aggregation
of small molecules in water usually leads to false positives (up to
95%) in drug screening,[45,46] which certainly is
a form of abnormal binding. In addition to indicating the aggregates
of small molecules are a rather general phenomenon, those results
also imply that the assemblies can cause false negatives (i.e., the
lack of ligand–receptor binding between 2 and 1). To verify that “monomeric” 1 still is able to bind to 2, we employed a nonionic
surfactant, Tw-80, to disrupt assemblies of 1. In the
presence of 1.0 wt % of Tw-80, the appearance of negative peaks in
the ITC heating profile indicates a release of heat (Figure C), likely due to molecular
binding between 1 and 2. Upon increasing
the Tw-80 concentration to 4.0 wt %, heating release dominates the
whole titration process (Figure D), and fitting by an independent binding model gives
a dissociation constant of 366 μM. This result confirms that
surfactant restores the ligand–receptor interaction between 2 and 1. Moreover, this result suggests that
using surfactant during ITC offers a facile method to study binding
between ligands and aggregate-prone receptors. We further used ITC
in the presence of Tw-80 to measure the binding of 2 and 3. Similar to the case of 1, the addition of
4.0 wt % Tw-80 recovers the ligand–receptor binding between 2 and 3 (Figure S10). In addition, the heating profile of the titration of 2 into a solution of 4 shows negligible change over various
concentrations of Tw-80 (Figure S11). These
results indicate that the surfactant itself has little contribution
to heat released during the titrations shown in Figure C,D. The observed heat release likely originates
from the interaction of 2 and the monomeric 1 after the surfactant disrupts the assemblies of 1.
Surfactant Breaks the Assemblies and Restores Binding
To
verify the effect of Tw-80 on assemblies of 1, we
used dynamic light scattering (DLS) to monitor the light scattering
signal and hydrodynamic radius (Rh) of
suspensions of 1 with different amounts of Tw-80 (Figure ). As seen in Figure A, as the Tw-80 concentration
increases from 1.0 wt % to 2.0 wt %, a peak representing species with
an Rh ranging from 3 to 10 nm starts to
grow. When the concentration of Tw-80 is increased to 4.0 wt %, this
peak exhibits significant growth, accompanied by the disappearance
of the peaks corresponding to the assemblies (larger than 100 nm),
indicating that the addition of Tw-80, indeed, disrupts the assemblies
of 1. Meanwhile, the light scattering signal of 1 decreases gradually with increasing Tw-80 concentration
(Figure B). After
the addition of 4.0 wt % Tw-80 into a suspension of 1, the light scattering signal decreases significantly and is almost
identical to a solution of 4.0 wt % Tw-80 alone (Figure S13). This result not only confirms that assemblies
of 1 dissociate upon the addition of Tw-80 but also suggests
that the dissociated species are too small to scatter light. TEM images
(Figure ) show that,
at a higher Tw-80 concentrations, the long dense nanosheets of 1 become low density short nanosheets, with only a few small
fibrils remaining. Finally, at 4.0 wt % Tw-80, nanoparticles dominate
(Figure S15). These results confirm that
Tw-80 disrupts the assemblies of 1 into oligomers.
Figure 3
DLS measurements
showing (A) hydrodynamic radii and (B) light scattering
signals (I/I0) for the
solution of 1 (800 μM) with various concentrations
of Tw-80 (wt %).
Figure 4
TEM images of suspensions
of 1 and 2 with
(A) 0 wt %, (B) 1.0 wt %, and (C) 4.0 wt % of Tw-80 or TEM of (D)
only 4.0 wt % of Tw-80. Inset are their optical images. [1]0 = [2]0 = 800 μM.
DLS measurements
showing (A) hydrodynamic radii and (B) light scattering
signals (I/I0) for the
solution of 1 (800 μM) with various concentrations
of Tw-80 (wt %).TEM images of suspensions
of 1 and 2 with
(A) 0 wt %, (B) 1.0 wt %, and (C) 4.0 wt % of Tw-80 or TEM of (D)
only 4.0 wt % of Tw-80. Inset are their optical images. [1]0 = [2]0 = 800 μM.After the DLS study of the effect
of Tw-80 on assemblies, we used
TEM to examine the morphological properties of 1 and 2 under various amounts of Tw-80. TEM micrographs of the colloidal
solution of 1 and 2 show large amounts of
nanosheets with dots along the edges, likely unstructured aggregates
of 1 and 2. The presence of nanosheets and
relatively few aggregates agrees well with no measurable ligand–receptor
interaction between 2 and assembled 1. After
adding 1.0 wt % Tw-80 into a suspension of 1 and 2, more unstructured aggregates form, and nanosheets still
remain (Figure B).
Meanwhile, optical images clearly show the formation of precipitates.
This result indicates that as 1.0 wt % Tw-80 breaks up assemblies
of 1, the oligomers released are able to bind with 2 to form aggregates, which bind together to form precipitates.
Such an observation is consistent with our previous results that as 1P is converted to 1, the forming hydrogelator
binds with 2 to induce aggregation. At 4.0 wt % Tw-80,
the aggregates disappear to give a clear solution, consisting of nanoparticles
with a diameter of 12 ± 2 nm (Figure C), which is almost identical to a solution
only containing 4.0 wt % Tw-80. This result indicates that, due to
the strong dissolution of Tw-80, the complex of 1 and 2 is unable to form large aggregates. Together with DLS data,
this result also confirms that 4.0 wt % Tw-80 completely breaks up
assemblies of 1 to monomeric or oligomeric 1, which binds with 2 (i.e., restores the ligand–receptor
interaction).
Morphological Evolution
As demonstrated
for both small
molecule supramolecular polymerization[41,47−49] and for assembly of amyloid proteins,[50−52] aggregate morphology,
and even toxicity, has a strong dependence on initial conditions and
the aggregation pathway. A time-dependent study of the gelation and
precipitation behavior of 1P in the presence of 2 and ALP reveals that the morphology and self-assembling
behavior of 1 correlate with the concentration of 2. As shown in Figure , the morphologies of the fibers or amorphous precipitates
formed after the addition of 2 to a solution of 1P and ALP exhibit a strong dependence on the concentration
of 2. The addition of 1 equiv of 2 is unable
to prevent the formation of long nanofibers, but can turn the nanofibers
into short fibers within 48 h, accompanied by forming a precipitate
identical to that in Figure C. While the addition of 1.5 equiv of 2 decreases
the nanofiber density, the addition of 2 or 3 equiv of 2 results in precipitation within 24 h. The addition of 5 equiv of 2 completely prevents the formation of long nanofibers. These
results indicate that, at pH 7.6, nanofibers are a metastable state
along the precipitation pathway, suggesting that the interaction between 1 and 2 leading to precipitation is indeed energetically
more favorable than self-assembly of 1 alone.
Figure 5
TEM micrographs
taken on three consecutive days of suspensions
of 1P, 2, and ALP, with varying concentrations
of 2. [1P]o = 500 μM, ALP
= 1.25 U/mL, pH = 7.6, each scale bar is 100 nm.
TEM micrographs
taken on three consecutive days of suspensions
of 1P, 2, and ALP, with varying concentrations
of 2. [1P]o = 500 μM, ALP
= 1.25 U/mL, pH = 7.6, each scale bar is 100 nm.Variation of ALP concentration gives similar results, with
higher
ALP concentrations giving rise to more dense nanofibers prior to precipitate
formation (Figures and S19). Surprisingly, at an ALP concentration
of 6.25 U/mL, nanofibers remained on the third day, indicating increased
order of the nanofibers of 1 formed at higher enzyme
concentration, similar to enzyme-induced order of supramolecular polymerization
reported by Ulijn et al.[18,53] There also is an alternative
explanation to the stability of the fibers formed at 6.25 U/mL ALP.
Higher enzyme concentration likely gives higher concentrations of 1. Fibers may form with a combination of 1 and 1P. Hence higher relative concentrations of 1 would likely give fibers with a higher composition of 1 relative to 1P, leading to more stable structures.
Figure 6
TEM micrographs
taken on three consecutive days of suspensions
of 1P, 2, and ALP with varying concentrations
of ALP. [1P]0 = [2] = 500 μM,
pH = 7.6, each scale bar is 100 nm.
TEM micrographs
taken on three consecutive days of suspensions
of 1P, 2, and ALP with varying concentrations
of ALP. [1P]0 = [2] = 500 μM,
pH = 7.6, each scale bar is 100 nm.In addition, dynamic oscillatory rheology confirms the disintegration
of the gels formed by dephosphorylation of 1P in the
presence of 2 and ALP. While both the storage and loss
moduli are frequency independent, the storage and loss moduli of the
gels formed by EISA of a solution of 500 μM 1P with
1.25 U/mL ALP in the presence of 1 equiv of 2 decrease
about an order of magnitude from 24 to 48 h (Figures S3 and S4), indicating that 2 promotes the dissociation
of the gel matrix. Hence both rheology and TEM confirm that the self-assembled
fibers are a transient structure, indicative of a local energy minimum,
with binding and subsequent precipitation of 1 and 2 being the global energy minimum.
Modulation of the Free
Energy Landscape
The transient
formation of the nanofibers during EISA and the relative stability
of assemblies of 1 against further precipitation after
the addition of 2 indicate the presence of multiple structurally
diverse intermediates along the fibril formation pathway. These intermediates
likely interact with 2 to divert self-assembly away from
fibril formation. Specifically, transient formation of nanofibers
upon EISA of 1P and further deterioration of assembled 1 into a precipitate of 1 and 2,
together with the observation that the addition of Tw-80 disrupts
assemblies of 1 and restores binding between 1 and 2, indicate that either (i) common di-, tri-, or
oligomeric intermediates of 1 exist for both nanofiber
assembly and precipitation or (ii) these pathways share only monomeric 1. Figure illustrates the plausible energy landscape for EISA of 1P both in the presence and absence of 2. Containing an
enzyme-catalyzed step, EISA is inherently under kinetic control, and
hence observations at thermodynamic equilibrium offer little information
on perturbation of EISA by 2. However, analysis of time-dependent
TEM, ITC, and the responses of the system to different concentrations
of ligand provide insights into these kinetic pathways. Without 2, EISA of 1P follows a simple pathway illustrated
on the left of Figure , whereby 1P (or oligomeric 1P) first undergoes
dephosphorylation to provide 1, which further assembles
to form nanofibrils. Although it is possible that 1P may
form micelles before dephosphorylation,[54] such a scenario is less likely in the presence of 2 because 2 binds to 1P and disfavors the
formation of micelle (as shown in Figure A). However, in the presence of 2, the entire energy landscape appears to be available, yielding a
complex mixture of species. 1P may bind with 2 in solution creating a lower energy species (1P·2) than simply “monomeric” 1P,
which can be further dephosphorylated to form 1·2, and may further assemble to yield precipitates. Additionally,
as dimerization of 2 is well-known,[35] a dimeric complex (1P·2)2 of 2 and 1P and/or 1 is likely to form instead of the complex (1P·2), which further aggregates following dephosphorylation to
form a precipitate. Aggregation is likely driven by the high local
concentration of 2 caused by dimerization and perhaps
also by the ability for 2 to promote dimerization of
a peptide hydrogelator, as we have previously shown.[44] The results in Figure indicate that more than 1 equiv of 2 is
needed for the formation of the precipitate and 2 is
part of the precipitate, thus 2 unlikely catalyzes the
fiber to precipitate conversion. Importantly, when vancomycin aglycon[55,56] replaces 2, no aggregates were observed (Figure S20); however, short fibers similar to
those in Figure were
observed, indicating that vancomycin aglycon destabilizes assemblies
of 1 in a similar fashion to 2. Because
the glycogen of 2 is essential for dimerization in water,
this result indicates that dimerization of 2 allows the
formation of large structures, thereby promoting further aggregation.
In addition, this observation supports formation of the dimeric complex
(1P·2)2 as a key intermediate
in the precipitation pathway. Therefore, during EISA of 1P, the presence of 2 allows for formation of lower energy
complexes with 1P or 1, diverting the supramolecular
aggregation by creating a lower energy pathway, similar to molecular
catalysts or molecular chaperones.[57]
Figure 7
Qualitative
energy landscape for the multiple paths of the assembly
or precipitation of 1 and 2 based on thermodynamic
data from ITC and relative stabilities of assemblies from TEM studies
showing the role of 2 in stabilizing precipitation pathways.
Oligomers of 1P and 1 which likely exist
are left out for clarity.
Qualitative
energy landscape for the multiple paths of the assembly
or precipitation of 1 and 2 based on thermodynamic
data from ITC and relative stabilities of assemblies from TEM studies
showing the role of 2 in stabilizing precipitation pathways.
Oligomers of 1P and 1 which likely exist
are left out for clarity.In addition to 2 diverting assembly of 1 during EISA, TEM reveals that 2 destabilizes
the assemblies
of 1. The addition of 1 equiv of 2 to the
nanofibers of 1 is unable to lead to precipitation (Figure D), while the addition
of 5 equiv of 2 to nanosheets of 1 gives
an opaque colloidal suspension paired with disruption of the nanosheets
of 1 (Figure S4). Additionally,
binding between 1 and 2 is restored upon
the addition of Tw-80 that breaks up assemblies of 1,
as evidenced by ITC (Figure d) and TEM (Figure ), indicating that 1 and 2 can interact.
Hence although assemblies of 1 barely revert to oligomers
or monomers that can bind with 2, sufficiently high concentrations
of 2 can perturb the energy landscape and pull the equilibrium
toward binding of 1 and 2. Based on this,
there are two plausible “mechanisms” for 2 breaking the assemblies of 1: (i) Free 2 in solution can bind with monomeric or oligomeric 1 and initiate precipitation, thereby lowering the concentration of 1 in solution, leading to deterioration of large assemblies
of 1; and (ii) 2 may bind directly to assemblies
of 1 leading to destruction of the assemblies and formation
of an intermediate species of 1 and 2, followed
by precipitate formation. Direct binding of 2 to the
assemblies of 1, however, is unlikely as ITC showed little
release of heat upon titration of 2 to assembled 1 (Figure b). Hence precipitation caused by 2 relies either on
reversible supramolecular polymerization of 1 or on the
presence of intermediate species of 1 in solution. Therefore,
transient formation of fibers of 1 is indicative of the
dynamic nature of EISA, a process that dynamically evolves based on
atomistic interactions between precursors (1P) of the
self-assembling molecules (1) as well as ligands (2), eventually bringing the system to kinetic or thermal equilibrium
dependence on both the initial and boundary conditions of the system.
Conclusion
The assembly or aggregation of proteins or peptides
remains one
of the most significant problems in biology and medicine, especially
associated with diseases like Alzheimer’s disease.[58−63] The path taken, however, depends strongly on the initial conditions
of the system as well as intrinsic kinetic factors such as enzyme
activation or critical nucleus formation. Recently, ionic strength
was found to modulate the energy landscape of Aβ40.[51] However, control over peptide concentration
and initial state remains difficult.[51] While
it remains to prove that ligand–receptor interactions may modulate
the aggregation of Aβ,[50] this study
on how interaction with a ligand significantly alters supramolecular
assembly of small molecules should provide useful insights. Because
the formation of Aβ results from enzymatic reactions,[64,65] the study of ligand–receptor interactions to modulate EISA
of small molecules is more relevant to the disease condition than
using hexafluoroisopropanol (HFIP) or dimethyl sulfoxide to generate
Aβ amyloids.[66] In fact, we used HFIP
to form the nanofibers of 1 and found that using HFIP
leads to various different morphologies (Figure S21).Moreover, it is well-known that in drug screening,
small molecules
hit with high aggregation potentials are poor candidates due to unpredictable
efficacy of ligand–receptor interactions.[45,46] This fact not only implies that self-assembly of small molecules
should modulate specific ligand–receptor interactions but also
suggests a limited knowledge about the molecular interactions between
aggregates and their target molecules. EISA creates multiple processes
which run in parallel, while also providing control over aggregating
peptide concentration. Additionally, this experimental system should
be useful for the study of the kinetics of the interconversion of
the molecular species, though one has to obtain accurate rate information
on the reactions.Although being extensively used by nature
for controlling important
cellular functions such as apoptosis[67] and
immune responses,[68] exploration of EISA
in the context of small molecules is at its infancy.[26,69−77] Recently, EISA has found applications in selective inhibition of
cancer cells[22,78−82] or targeting tumors in an animal model,[83] but enzymatic control over ligand–receptor
interactions of small molecules has yet to be investigated. This work,
thus, provides necessary understanding to develop EISA in sophisticated
environments with prevailing ligand–receptor interactions.
Hence, this study demonstrates that perturbation of assembly can be
accomplished through modulation of the relative energies of intermediate
species. In a more general sense, the insights obtained in this work
would contribute to the exploration of supramolecular chemistry in
cellular milieu.
Authors: Yi Kuang; Junfeng Shi; Jie Li; Dan Yuan; Kyle A Alberti; Qiaobing Xu; Bing Xu Journal: Angew Chem Int Ed Engl Date: 2014-05-12 Impact factor: 15.336
Authors: Lu Zhang; Di Jing; Nian Jiang; Tatu Rojalin; Christopher M Baehr; Dalin Zhang; Wenwu Xiao; Yi Wu; Zhaoqing Cong; Jian Jian Li; Yuanpei Li; Lei Wang; Kit S Lam Journal: Nat Nanotechnol Date: 2020-01-27 Impact factor: 40.523