概要信息：

An Array-Based Method To Identify Multivalent Inhibitors
Yalong Zhang,† Qian Li,† Luis G. Rodriguez,‡ and Jeffrey C. Gildersleeve†,*
Chemical Biology Laboratory, National Cancer Institute, 376 Boyles Street, Building 376,
Frederick, Maryland 21702, and Optical Microscopy and Analysis Laboratory, SAIC-Frederick,
Inc., AdVanced Technology Program, NCI-Frederick, Frederick, Maryland 21702
Received January 28, 2010; E-mail: gildersj@mail.nih.gov
Abstract: Carbohydrate-protein interactions play a critical role in a variety of biological processes, and
agonists/antagonists of these interactions are useful as biological probes and therapeutic agents. Most
carbohydrate-binding proteins achieve tight binding through formation of a multivalent complex. Therefore,
both ligand structure and presentation contribute to recognition. Since there are many potential combinations
of structure, spacing, and orientation to consider and the optimal one cannot be predicted, high-throughput
approaches for analyzing carbohydrate-protein interactions and designing inhibitors are appealing. In this
report, we develop a strategy to vary neoglycoprotein density on a surface of a glycan array. This feature
of presentation was combined with variations in glycan structure and glycan density to produce an array
with approximately 600 combinations of glycan structure and presentation. The unique array platform allows
one to distinguish between different types of multivalent complexes on the array surface. To illustrate the
advantages of this format, it was used to rapidly identify multivalent probes for various lectins. The new
array was first tested with several plant lectins, including concanavalin A (conA), Vicia villosa isolectin B4
(VVL-B4), and Ricinus communis agglutinin (RCA120). Next, it was used to rapidly identify potent multivalent
inhibitors of Pseudomonas aeruginosa lectin I (PA-IL), a key protein involved in opportunistic infections of
P. aeruginosa, and mouse macrophage galactose-type lectin (mMGL-2), a protein expressed on antigen
presenting cells that may be useful as a vaccine targeting receptor. An advantage of the approach is that
structural information about the lectin/receptor is not required to obtain a multivalent inhibitor/probe.
Introduction
Carbohydrate-protein interactions play a critical role in many
biological processes, such as cell-cell recognition, inflamma-
tion, and metastasis.1-3 Due to their importance, there have been
significant efforts to identify carbohydrate-binding proteins,
determine their natural ligands, and characterize their biological
functions. In addition, the development of agonists/antagonists
of these interactions has received considerable attention. For
example, many bacteria and viruses bind to carbohydrates on
the surface of host cells as a key step of infection, and inhibitors
of these interactions have been sought after as antibacterial or
antiviral agents.4-6 As a second example, migration of leuko-
cytes to sites of infection is mediated by a carbohydrate-binding
protein, L-selectin, and inhibitors of this protein have been
investigated extensively as anti-inflammatory agents.7-9
Analysis of carbohydrate-protein interactions and develop-
ment of inhibitors/probes of these interactions is challenging
for several reasons. First, there are thousands of glycans found
in nature, and it is difficult to predict which ones will bind to
a protein. Consequently, one would like to evaluate binding to
many glycans to determine if a protein binds carbohydrates and
to identify its ligands. Unfortunately, only a small number of
structurally defined glycans are available in homogeneous form,
and these are typically only available in small quantities.
Therefore, it is difficult to test large numbers of potential ligands
for binding. Second, carbohydrate-binding proteins, such as
lectins and antibodies, typically bind monovalent carbohydrate
ligands with low affinity and poor selectivity.6,10-12 To com-
pensate for the low intrinsic affinity, carbohydrate-binding
proteins normally possess multiple binding sites, which enables
them to simultaneously bind two or more carbohydrate ligands
on a cell surface or glycoprotein. The resulting multivalent
complexes can have much higher overall affinity (referred to
as avidity) and selectivity. To produce a multivalent interaction,
however, the spacing and orientation of the carbohydrate ligands
must be appropriately matched to the binding sites of the
receptor. Therefore, proper presentation of the ligands is critical
for recognition.
† Chemical Biology Laboratory, National Cancer Institute.
‡ Advanced Technology Program, NCI-Frederick.
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Published on Web 06/28/2010
10.1021/ja100608w  2010 American Chemical Society J. AM. CHEM. SOC. 2010, 132, 9653–9662 9 9653
Agonists/antagonists of carbohydrate-binding proteins are
very useful for a variety of basic research and clinical applica-
tions. While there have been many attempts to design monova-
lent inhibitors of lectins, high affinity monovalent inhibitors are
extremely rare and most have affinities in the micromolar to
millimolar range. Therefore, multivalency has been a key design
feature for the majority of current inhibitors and probes for
lectins. A variety of multivalent scaffolds have been developed,
such as dendrimers, proteins, polymers, beads, and lipo-
somes.6,10-12 Different multivalent platforms can display glycans
with varying spacing, orientation, density, flexibility, and overall
architecture, but it is difficult to predict the optimal scaffold for a
particular glycan-lectin interaction. Optimization of multivalent
presentation is especially tough when the spacing and geometries
of the binding sites on the target lectin are not known.
Glycan arrays contain many different carbohydrates im-
mobilized on a solid support in a spatially separated arrange-
ment.13-19 They provide a high-throughput tool to evaluate
many potential carbohydrate-protein interactions in parallel
while using only tiny amounts of scarce materials. Glycan arrays
have great potential for aiding the design and development of
lectins inhibitors, but certain challenges exist. For most array
platforms, a multivalent display is achieved by presenting
multiple copies of a monovalent ligand on the surface. With
this approach, the surface acts as the multivalent scaffold and,
therefore, the spacing and orientation of ligands are defined by
the surface. While this approach is useful for identifying ligands
that are recognized by carbohydrate-binding proteins, it is not
ideal for the development of multivalent probes since it can be
difficult to identify a soluble multivalent scaffold that mimics
the presentation of the carbohydrates on the array surface.
We have focused on an alternative approach for the construc-
tion of glycan arrays wherein multivalent glycoconjugates are
immobilized on the surface.20-29 To produce our arrays, glycans
are first covalently attached to a carrier protein, such as albumin,
to generate multivalent neoglycoproteins. These conjugates are
then immobilized on the surface to produce a neoglycoprotein
array. Neoglycoproteins have been used for many years as
reagents to study carbohydrate recognition, as multivalent
inhibitors of carbohydrate-protein interactions, and as immu-
nogens.4,30 Since the same multivalent scaffold is used on the
array surface and for solution applications, this strategy is well-
suited for the identification of multivalent neoglycoprotein
probes for lectins. In addition, the approach offers unique
opportunities to modulate presentation, including varying the
carrier protein, the glycan density, and the neoglycoprotein
density.
In this study, we describe the development and evaluation
of a strategy to modulate neoglycoprotein density on the array
surface. The approach is simple and economical and can readily
be combined with other elements of glycan array diversity. To
illustrate this, we constructed arrays with variations in neogly-
coprotein density, glycan structure, and glycan density. Col-
lectively, the new arrays contained approximately 600 combi-
nations of glycan structure and presentation. One advantage of
this unique array format is that it allows one to distinguish
between different multivalent binding modes. To illustrate the
utility of this new multidimensional array format, we demon-
strate that it provides rapid access to high-affinity multivalent
probes for various plant, bacterial, and animal lectins.
Materials and Methods
General Methods. Unless otherwise stated, reagents were pur-
chased from commercial suppliers and used without purification. All
aqueous solutions were prepared from Milli-Q water with a 0.2 µm
filter. Bovine serum albumin (BSA) was purchased from Sigma (St.
Louis, MO). Alexa Fluor488 (AF488) BSA conjugates, Alexa Fluor594
(AF594) BSA conjugates, AF555 succinimidyl ester, and QSY-7
succinimidyl ester were purchased from Invitrogen Corporation
(Carlsbad, CA). Biotinylated BSA, ConA, VVL-B4, and RCA120 were
purchased from Vector Laboratories (Burlingame, CA). Cy3-strepta-
vidin and alkaline phosphatase (AP)-streptavidin were purchased from
Zymed Laboratories of Invitrogen Corporation (Carlsbad, CA). His-
tagged PA-IL was a gift from Professor Lara Mahal (New York
University). Antipenta-His mouse IgG1 was purchased from Qiagen
(Valencia, CA), Cy3-labeled goat anti-mouse IgG+IgM(H+L) and
AP-goat anti-mouse IgG+IgM(H+L) were purchased from Jackson
ImmunoResearch (West Grove, PA). RGal-BSA and Pk-HSA were
purchased from V-Laboratories (Covington, LA). Recombinant mMGL-2
and biotinylated goat anti-mouse IgG were purchased from R&D
Systems (Minneapolis, MN).
Analysis of Lectin Binding on the Full Array. Microarray
slides (for array fabrication, see Supporting Information) were
assembled with an 8 well slide holder (Grace Bio-Laboratories,
Inc., Bend, OR). All slides were blocked with 3% BSA/PBS at r.t.
for 2.0 h before experiments. Dilution series of biotinylated lectins
[Concanavalin A (ConA), Vicia Villosa lectin (VVL-B4), and
Ricinus communis agglutinin (RCA120)] were prepared in 1% BSA/
PBST0.05. ConA was prepared in a range from 0.18 nM to 460
nM. VVL-B4 was in a range from 1.2 nM to 620 nM. RCA120
was in a range from 0.41 nM to 105 nM. Two hundred microliters
of the lectin solutions was added to each well. Each well was then
covered tightly with seal strips and incubated at r.t for 2.0 h. After
washing unbound lectin with 4 × 400 µL of PBST0.05, streptavidin-
Cy3 in 1% BSA/PBS (1:500, 1 µg/mL, 200 µL/well) was added
and incubated at r.t. for 2.0 h.
Pseudomonas aeruginosa lectin I (PA-IL) and mouse macroph-
age galactose-type lectin-2 (mMGL-2) were prepared in 1% BSA/
TSMT0.05 (20 mM Tris, 150 mM NaCl, 0.05% tween 20, 2 mM
CaCl2, 2 mM MgCl2). PA-IL was diluted in a range from 37 nM
to 4700 nM. mMGL-2 was diluted in a range from 0.38 nM to 24
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9654 J. AM. CHEM. SOC. 9 VOL. 132, NO. 28, 2010
A R T I C L E S Zhang et al.
nM. Unbound lectin was washed off by 4 × 400 µL of TSMT0.05
and tapped dry. Mouse anti-His IgG1 in 1% BSA/TMS (1:200, 1
µg/mL, 200 µL/well) for PA-IL, and biotinylated goat anti-mouse
IgG in 1% BSA/TMS (1:200, 2 µg/mL, 200 µL/well) were added
and incubated at r.t. for 2.0 h. Slides were washed by 4 × 400 µL
of TSMT0.05 and tapped dry. Then goat anti-mouse Cy3-
IgG+IgM(H+L) 1% BSA/TMS (1:500, 1 µg/mL, 200 µL/well)
for PA-IL and Cy3-streptavidin in 1% BSA/PBS (1:500, 1 µg/mL,
200 µL/well) for mMGL-2 were added and incubated at r.t. for
2.0 h. All slides were washed 4 × 400 µL of PBST0.05 and tapped
dry, removed from the holder, and immersed into PBST0.05 buffer
for 10 min. Slides were dried by centrifuging at 1000 rpm for 5
min.
Slides were scanned using a Genepix 4000A microarray scanner
at 10 µm resolution (Molecular Devices Corporation, Union City,
CA) at a PMT voltage setting of 440 (or 460) at 532 and 632 nm.
Images were analyzed with Genepix Pro 6.0 analysis software
(Molecular Devices Corporation). Spots were defined as circular
features of 100 µm. The features were resized manually as needed.
The background-corrected mean (F532mean-B532) was used for
data analysis. Fluorescence data for each spot for a given neogly-
coprotein or glycoprotein were averaged. The apparent Kd values
were determined following the method of MacBeath.31 The mean
was plotted with the concentration of lectins on a logarithmic scale
and a nonlinear curve was fitted using Origin 8.0 (OriginLab,
Northampton, MA) according to the equation below:
where Fc is the fluorescent intensity for the lectin binding at any
specific concentration, Fmax is the maximum intensity, Kd is the
apparent dissociation constant for the lectin and neoglycoprotein
on the array, and [L] is the concentration of lectins.
Analysis of Solution Inhibition and IC50 Determination by
ELISA-like Assays. Wells of a 96-well plate (nontreated Maxisorb
NUNC 96-well plate) were incubated with 500 ng/well of neogly-
coprotein in 1× PBS buffer, pH 7.4, at 4 °C overnight. The
following neoglycoproteins were used for the respective lectins:
Man-R-BSA (ConA), Ac-S-Tn(Ser)-S-G-33-BSA (VVL-B4), Ac-
S-TF(Thr)-S-G-28-BSA (RCA120), Lac-BSA (PA-IL) and Ac-
TF(Thr)-G-24-BSA (mMGL-2). After adsorbing the appropriate
neoglycoprotein to the well surfaces, the solutions were removed
and the wells were blocked with 3% BSA in PBS buffer at r.t. for
2.0 h. Biotinylated plant lectins (ConA ) 1:5000; VVL-B4 )
1:2000; and RCA120 ) 1:2500; each in 1% BSA in PBS) were
incubated with a series of concentrations of various neoglycopro-
teins for 30 min. Then 60 µL of the mixture was added to each
well and incubated at r.t. for 2.0 h. The neoglycoprotein-lectin
mixture solutions were removed, and the plate was washed four
times with PBST0.05 (200 µL/well). AP-streptavidin was diluted
1:500 in 1% BSA in PBS, and 65 µL of the solution was added to
each well and incubated for 2.0 h. The streptavidin solution was
removed, and the plate was washed four times with PBST0.05.
Next, 75 µL of 4-methylumbellyferyl phosphate solution (MUP;
100 µM in Tris, pH 9.0) was added to each well and the plate was
scanned immediately using a FLX 800 microplate fluorescence
reader (BioTek, Winooski, VT; excitation ) 360, emission ) 440).
Inhibition assays for PA-IL and mMGL-2 were carried out in
an analogous manner except that samples were diluted in TSM
buffer (20 mM Tris, 150 mM NaCl, 2 mM CaCl2, 2 mM MgCl2).
In addition, binding was detected by mouse anti-His IgG1 (1:200
in 1% BSA/TMS; 65 µL/well) followed by AP-goat anti mouse
IgG+IgM (H+L) (1:500 in 1% BSA/TSM; 70 µL/well) for PA-
IL, and biotinylated goat anti-mouse IgG (1:200 in 1% BSA/TMS;
65 µL/well) followed by AP-streptavidin (1:500 in 1% BSA/TSM;
70 µL/well) for mMGL-2.
The assays were conducted in triplicate, and the data was
normalized by subtracting the negative control (samples without
lectin) and then dividing by the maximum [maximum ) positive
control (lectin without mixing with neoglycoprotein) - negative
control]. The mean was plotted and fit using Origin 8.0 software.
IC50 values for the neoglycoproteins were obtained from the
concentration of neoglycoprotein at 50% of relative intensity.
Results and Discussion
Array Design and Rationale. Our objective was to develop
an array-based strategy to identify multivalent probes for glycan-
binding proteins and to better profile their binding properties.
Carbohydrate-binding proteins can adhere to a surface coated
with neoglycoproteins in a variety of ways. For example, a
carbohydrate-binding protein can form a multivalent complex
with a single neoglycoprotein (1-to-1 complex, see Figure 1a)
or can recognize carbohydrates on adjacent neoglycoproteins
to form a bridging complex (i.e., one lectin binding two or more
neoglycoproteins, see Figure 1b). These different types of
multivalent complexes are not equivalent, and the ability to
distinguish between them could be useful for a number of(31) Gordus, A.; MacBeath, G. J. Am. Chem. Soc. 2006, 128, 13668–9.
Figure 1. Different multivalent binding modes and the array strategy.
Fc )
Fmax
Kd
[L]
+ 1
J. AM. CHEM. SOC. 9 VOL. 132, NO. 28, 2010 9655
Array-Based Method To Identify Multivalent Inhibitors A R T I C L E S
applications. First, it would be useful for identifying multivalent
probes for lectins. Although both types of multivalent complexes
produce high avidity interactions on a surface, a bridging
complex is difficult to achieve in solution and generally produces
aggregates. Therefore, a neoglycoprotein with the ability to form
a 1-to-1 complex on a surface is more likely to retain activity
as a high affinity, solution-phase probe. Second, methods to
distinguish between different types of multivalent complexes
could be useful for detecting carbohydrate-binding proteins
within complex mixtures. Many carbohydrate-binding proteins
have similar specificities but distinct architectures (e.g., different
numbers of binding sites, different distances between binding
sites). Because the spacing and orientations of the binding sites
are different, these proteins could form different types of
multivalent complexes on the surface, and methods to discrimi-
nate between those complexes could enable one to differentially
detect those proteins.
One strategy to distinguish 1-to-1 complexes and bridging
complexes is to vary the neoglycoprotein density on the array
surface. Formation of a bridging complex requires neoglyco-
proteins to be positioned in close proximity to each other. If
individual neoglycoprotein molecules are spaced farther apart
on the surface, bridging complexes should be disfavored (see
Figure 1c). One method to achieve the desired spacing involves
adding unmodified BSA into the print solutions and then printing
these mixtures on the array surface.32 With this strategy,
unmodified BSA occupies surface area between neoglycoprotein
molecules (see Figure 1c). As the proportion of BSA increases,
individual neoglycoproteins will be spaced farther apart, and
the neoglycoprotein density decreases. While the relative
proportions of neoglycoprotein and BSA would be modulated,
the total protein concentration would be maintained at a constant
value (125 µg/mL, a concentration that saturates the surface).
By comparing binding at high and low neoglycoprotein density,
one could distinguish between 1-to-1 complexes and bridging
complexes.
We,22 and others,33-39 have previously described methods
to vary the glycan density on the surface of an array. In our
previous work, glycan density was modulated by varying the
average number of glycans per molecule of albumin. The
method described above for spacing apart neoglycoproteins
involves varying the neoglycoprotein density (the average
number of neoglycoprotein molecules per unit surface area).
While similar in certain respects, modulation of neoglycoprotein
density is functionally distinct and complementary with varying
glycan density (for a detailed example illustrating the functional
differences between variations in glycan density versus varia-
tions in neoglycoprotein density, see Figure S4, Supporting
Information). It was our intention to construct arrays with
variations in both glycan density and neoglycoprotein density.
Although the design concept was simple, a number of factors
could cause problems. First, the neoglycoproteins must have
limited movement on the surface. Some degree of flexibility
was expected due to the linkers and conformational motion of
the carrier protein, but individual molecules of neoglycoprotein
should not be able to move or “slide around” on the surface. If
this were the case, then neoglycoproteins and molecules of
unmodified BSA could rearrange during an assay to form both
1-to-1 and bridging complexes. Second, the immobilization
process should result in an even distribution of neoglycoproteins
and unmodified BSA on the surface. If the neoglycoproteins
cluster together, for example, then the addition of BSA would
not generate the expected spacing. Ideally, the spacing on the
surface would be predictable, controllable, and consistent for
all neoglycoproteins. For example, variations in glycan length,
branching, and the number of glycans per molecule of albumin
should not significantly affect this relationship. For these
reasons, our initial studies were aimed at characterizing the
surface and validating the design concept.
Surface Characterization and Model Studies. To better
characterize the surface, we carried out a set of experiments
with model arrays. First, arrays were printed with AF488-BSA,
a fluorophore-labeled protein, with or without varying amounts
of unmodified BSA and the resulting spots were scanned using
a confocal microscope. For each of the neoglycoprotein densi-
ties, the fluorescence was found to be consistent over the area
of the spot (see Figure S1, Supporting Information). Although
the resolution is not sufficient to define positions at a single-
molecule level, the result supports an even distribution of
conjugates. Next, we carried out a photobleaching experiment
to determine if the conjugates can move around on the spot. A
pattern was photobleached within a section of the spot, and the
fluorescence was monitored over the next 4 h (see Figure S2,
Supporting Information). If the AF488-BSA conjugates were
capable of moving around on the spot, one would expect
redistribution of the AF488-BSA molecules and disappearance
of the photobleached pattern. In contrast, we found that the
photobleached section did not regain fluorescence, at least over
the time frame of the experiment, indicating that the conjugates
do not move around on the surface.
Next, we estimated the effects of BSA addition on the spacing
of neoglycoproteins on the surface. BSA has dimensions of
approximately 35 Å × 35 Å × 70 Å. For simplicity, we treated
BSA molecules as rectangular boxes with the above dimensions
and assumed that the surface contained a monolayer of closely
packed BSA molecules. In addition, we assumed that the BSA
molecules formed a regular arrangement with the 70 Å side
laying parallel to the surface. Based on this model, we would
expect each neoglycoprotein to be, on average, surrounded by
a shell of unmodified BSA molecules at a ratio of 1:7
(neoglycoprotein:BSA). This would correspond to an average
spacing from the center of one neoglycoprotein to the center of
the next neoglycoprotein of about 140 Å (see Figure S3,
Supporting Information).
To evaluate this model, we carried out a set of resonance
energy transfer experiments. AF555-BSA (donor) and QSY7-
BSA (quencher) were mixed in equal amounts, and then the
mixture was combined with varying amounts of unmodified
BSA. The mixtures were then printed on the array surface, and
the fluorescence was imaged and quantified. In this experiment,
QSY7-BSA quenches the fluorescence of AF555-BSA in a
(32) An alternative method to space neoglycoproteins apart on the array
surface is to print subsaturating amounts of neoglycoprotein; however,
we have found previously that when the array surface is not saturated,
uneven distributions of neoglycoproteins can be produced.
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A R T I C L E S Zhang et al.
distance-dependent manner. Quenching was clearly evident in
the absence of added BSA, and the relative amount of quenching
decreased as the proportion of BSA increased (see Table S1,
Supporting Information), showing that addition of BSA spaced
the donors and acceptors farther apart. At a ratio of 1:7, no
quenching was observed, indicating that the average distance
between acceptor and donor was greater than ∼90 Å (based on
a Förster critical distance of 45 Å for AF555-QSY7). These
results are consistent with our model. As with previous
experiments, the fluorescence was uniform over the area of the
spot, which is consistent with an even distribution of acceptor
and donor conjugates.
Finally, we were concerned that longer glycans, branched
structures, and/or high densities of glycans on BSA might
impede or slow immobilization of these neoglycoproteins
relative to unmodified BSA. If so, the compositions and spacings
of neoglycoproteins on the surface would vary, depending on
the particular neoglycoprotein, which could complicate analyses
and comparisons. For example, long and/or branched glycans
on certain neoglycoprotein might slow the rate of immobilization
to the surface. If so, unmodified BSA might out-compete those
neoglycoproteins, resulting in much lower neoglycoprotein
densities than expected on the surface. To test this, we evaluated
three glycans at both high and low density on BSA for a total
of six neoglycoproteins. We included two monosaccharide-BSA
conjugates (Man-R-4-BSA and Man-R-20-BSA), two linear
trisaccharides (LNT-4-BSA and LNT-20-BSA; LNT ) Gal
1-
3GlcNAc
1-3Gal
), and two branched glycopeptides [S-TnThr-
S-4-BSA and S-TnThr-S-20-BSA] (see Figure 2). Each was
labeled with a fluorophore, AF555, and printed on the microar-
ray slide with varying proportions of BSA (see Figure S6 and
Table S2, Supporting Information). The slides were washed and
scanned to determine the amount of fluorescence at each spot.
The fluorescence intensities of samples were normalized relative
to the corresponding spots with 100% neoglycoprotein to get a
relative percentage of fluorescence. As shown in Table S3 in
the Supporting Information, each of the samples at a given BSA
ratio gave about the same fluorescence relative to the 100%
sample, indicating that size, branching, and the density do not
significantly affect the immobilization efficiency for these six
neoglycoproteins. Although evaluation of all the other array
components was not feasible, the results from this subset suggest
that the addition of unmodified BSA should have similar effects
on the surface composition for most neoglycoproteins in our
collection. As with previous experiments, the fluorescence was
uniform over the area of the spots, which is consistent with an
even distribution of conjugates.
Construction of the Full Array and Validation with Plant
Lectins. The next step was to incorporate variations in neogly-
coprotein density with our existing glycan array. Arrays were
fabricated using our previously published protocols (see also
Supporting Information).22,23 On the basis of preliminary studies,
we chose to construct our first-generation array with four ratios
of added BSA per array component: 1:0 (100%; no BSA), 1:1
(50%), 1:3 (25%), and 1:7 (12.5%). We included 147 different
neoglycoproteins and glycoproteins, along with several controls
including BSA alone (for a full list of array components, see
Table S4 in the Supporting Information), giving a total of 591
combinations of structure and neoglycoprotein/glycoprotein
density. Each combination was printed in duplicate within a
subarray, and eight subarrays were printed on each slide,
allowing us to carry out eight independent array experiments
in parallel on a slide.
Our next objective was to evaluate binding of several plant
lectins to validate the array design strategy. As a first test case,
we examined binding of concanavalin A (ConA). ConA is a
mannose/glucose binding plant lectin that has been studied
extensively using many methods and techniques. ConA was
evaluated on the array to determine the effects of neoglyco-
protein density on binding. It is important to note that the
measured signal intensity for each array component at a given
lectin concentration can vary as a function of the amount of
ligand and that changes in neoglycoprotein density produce
differences in the total amount of ligand on each spot. Therefore,
we evaluated binding at a range of concentrations and deter-
mined the apparent Kd values for various glycans at each of the
four BSA ratios (see Table 1 and Table S5 for a full listing of
apparent Kd values for ConA), since affinity constants are not
dependent on the amount of ligand. Due to the high-throughput
design of the array, a full dilution series for a lectin can easily
be completed in a single day.
ConA binding was highly dependent on neoglycoprotein
density. For the spots with 100% neoglycoprotein, ConA showed
similar avidity for a number of mannose-containing neoglyco-
proteins and for Glc-R-BSA. For example, Man6-BSA and Man-
R-BSA had similar apparent Kd values of 49 and 69 nM,
respectively (see Figure 3a; see Figure 4a for structures). The
apparent Kd for Glc-R-BSA was 113 nM. These values are quite
comparable to the apparent Kd values measured on another
glycan array37 and affinity constants measured by SPR.33 In
contrast, binding to these neoglycoproteins was significantly
different at low neoglycoprotein density (ratio of 1:7). In
particular, Man6-BSA was bound tightly by ConA even at a
ratio of 1:7 (app Kd ) 108 nM), whereas Man-R-BSA and Glc-
R-BSA were not bound at all by ConA at a ratio of 1:7 (see
Figure 3b).
On the basis of these results and the design concept, we
inferred that Man6-BSA was forming a 1-to-1 complex with
ConA, while Man-R-BSA and Glc-R-BSA were forming bridg-
ing complexes (see Figure 3c). Therefore, we anticipated that
Man6-BSA would be capable of inhibiting ConA in solution,
while Man-R-BSA and Glc-R-BSA would not. To test this, an
ELISA-like assay was used. Neoglycoproteins were incubated
with biotinylated ConA at varying concentrations, and the
Figure 2. Neoglycoproteins used in the model studies.
J. AM. CHEM. SOC. 9 VOL. 132, NO. 28, 2010 9657
Array-Based Method To Identify Multivalent Inhibitors A R T I C L E S
mixtures were then added to 96-well plates precoated with Man-
R-BSA. Binding of ConA was detected by incubating the wells
with streptavidin-alkaline phosphatase (SA-AP) followed by a
fluorogenic AP substrate (see Figure 3d). The IC50 values, the
concentrations of neoglycoprotein required to produce 50%
inhibition, were then determined. Man6-BSA was found to have
an IC50 of 38 ( 14 nM, while Man-R-BSA and Glc-R-BSA
failed to show any significant inhibition at a concentration as
high as 758 nM. Therefore, only Man6-BSA acted as a solution-
phase inhibitor. The results highlight one of the key advantages
Table 1. Selected Binding Data for the Plant Lectins
without BSA (1:0) with BSA (1:7) inhibition data
lectin liganda App Kd(nM) p valueb App Kd(nM) p valueb IC50(nM) p valueb
ConA Man6 49 ( 29 108 ( 10 38 ( 14
Man-R 69 ( 7 0.23 NB <0.0005 >758 <0.0005
Glc-R 113 ( 15 0.04 NB <0.0005 >758 <0.0005
VVL-B4 Ac-A-TnThr-S-G-23 66 ( 9 317 ( 115 16 ( 4
Ac-S-TnSer-S-G-22 132 ( 44 0.17 ND <0.0005 650 ( 39 0.002
Ac-V-Tn(Thr)-S-G-19 125 ( 58 0.29 ND <0.0005 368 ( 35 0.03
GA2di-37 164 ( 27 0.04 ND <0.0005 172 ( 2 0.001
RCA120 LacNAc (trimeric) 8.0 ( 0.3 83 ( 18 11.5 ( 0.8
Lac 8.1 ( 0.5 0.83 307 ( 42 0.02 114 ( 3 0.0005
a For complete array data and apparent Kd values, see the Supporting Information. b Paired t-test. NB denotes no binding. ND (not determined)
denotes some binding but apparent Kd too large to measure. Values have not been adjusted for valency. Complete binding data can be found in the
Supporting Information.
Figure 3. Comparison of ConA binding to Man6 and Man-R. (a) ConA binding at high neoglycoprotein density (1:0); shown are pairs of spots for Man-R
and Man6 at a single ConA concentration (189 nM) and binding curves over a range of ConA concentrations. (b) ConA binding at low neoglycoprotein
density (1:7); shown are pairs of spots for Man-R and Man6 at a single ConA concentration (189 nM) and binding curves over a range of ConA concentrations.
(c) Proposed binding modes at high and low neoglycoprotein density. At high density, ConA binds Man-R via a bridging complex and Man6 via a 1:1
complex. At low neoglycoprotein density, a bridging complex with Man-R cannot be formed. (d) Inhibition of ConA binding was evaluated by an ELISA-
like assay at a range of neoglycoprotein concentrations and inhibition curves are shown for Man6 and Man-R. Man6 shows good inhibition, while Man-R
shows no inhibition.
9658 J. AM. CHEM. SOC. 9 VOL. 132, NO. 28, 2010
A R T I C L E S Zhang et al.
of this method. Using the conventional immobilization format
(i.e., 100% neoglycoprotein; no added BSA), Man6-BSA, Man-
R-BSA, and Glc-R-BSA appeared to have roughly equivalent
binding to ConA, both in terms of their apparent Kd values and
in terms of the raw fluorescence signals at each lectin concen-
tration (see Figure 3a). By varying neoglycoprotein density,
however, major differences could be detected, and these
differences enabled us to predict which neoglycoprotein would
have activity as a solution-phase inhibitor and which ones would
be poor inhibitors.
Next, we evaluated binding to the plant lectin, Vicia Villosa
lectin B4 (VVL-B4). This lectin is a GalNAc binding protein
that has been used for many years to detect expression of the
Tn antigen in tumors samples.40-46 Analogous to our studies
on ConA, binding was evaluated at a range of concentrations
using the array and apparent Kd values were determined. A
number of glycans/glycopeptides were bound by VVL-B4, and
full binding profiles are provided in the Supporting Information.
Like ConA, neoglycoprotein density had a major impact on
binding for VVL-B4. Using the conventional format (i.e., no
added BSA), a number of glycopeptides had similar binding
signals and apparent Kd values. For example, the apparent Kd
values for Ac-A-TnThr-S-G-23-BSA, Ac-S-TnSer-S-G-22-BSA,
Ac-V-TnThr-S-G-19-BSA, and GA2di-37-BSA ranged from
66-164 nM (see Table 1). At a ratio of 1:7, however, Ac-A-
TnThr-S-G-23-BSA was clearly the best binder (apparent Kd of
317 nM). Ac-S-TnSer-S-G-22-BSA, Ac-V-TnThr-S-G-19-BSA,
and GA2di-37-BSA retained some binding at 1:7, but the
apparent Kd values were too high to measure on the array (>3
µM). These results suggested that Ac-S-TnSer-S-G-22-BSA, Ac-
V-TnThr-S-G-19-BSA, and GA2di-37-BSA may have some
activity as solution inhibitors, but they would be much worse
than Ac-A-TnThr-S-G-23-BSA. To test this, an ELISA-like
solution inhibition assay was used as before. As expected, Ac-
A-TnThr-S-G-23-BSA was a good inhibitor (IC50 value of 16 (
4 nM; see Table 1), while the other three were found to be
11-40 fold worse. Again, variations in neoglycoprotein density
on the array surface revealed differences in binding that enabled
us to predict which of these neoglycoproteins would be the best
inhibitor in solution.
As a third test case, we evaluated binding of Ricinus
communis agglutinin (RCA120), a galactose-binding plant
(40) Tollefsen, S.; Kornfeld, R. J. Biol. Chem. 1983, 258, 5172–5176.
(41) Puri, K. D.; Gopalakrishnan, B.; Surolia, A. FEBS Lett. 1992, 312,
208–212.
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A.; Cantacuzene, D.; Nimtz, M.; Alzari, P. M.; Osinaga, E. Eur.
J. Biochem. 2000, 267, 1434–1440.
(43) Osinaga, E.; Bay, S.; Tello, D.; Babino, A.; Pritsch, O.; Assemat, K.;
Cantacuzene, D.; Nakada, H.; Alzari, P. FEBS Lett. 2000, 469, 24–
28.
(44) Babino, A.; Tello, D.; Rojas, A.; Bay, S.; Osinaga, E.; Alzari, P. M.
FEBS Lett. 2003, 536, 106–110.
(45) Wu, A. M. FEBS Lett. 2004, 562, 51–58.
(46) Kato, K.; Takeuchi, H.; Ohki, T.; Waki, M.; Usami, K.; Hassan, H.;
Clausen, H.; Irimura, T. Biochem. Biophys. Res. Commun. 2008, 371,
698–701.
Figure 4. Chemical structures of selected glycans.
J. AM. CHEM. SOC. 9 VOL. 132, NO. 28, 2010 9659
Array-Based Method To Identify Multivalent Inhibitors A R T I C L E S
lectin.47,48 RCA120 is one of two toxic lectins isolated from
the seeds of the castor bean. The more potent of the two is
ricin, a potential biological warfare agent. RCA120 is about 20
times less toxic and is often used as a model of ricin, since the
carbohydrate-binding properties are similar. RCA120 was
evaluated at a range of concentrations, and apparent Kd values
were determined. Only a few neoglycoproteins were bound by
the lectin, and two clearly stood out as the best binders: Lac-
BSA and LacNAc (trimeric)-BSA (see Figure 4c for structures).
In the absence of added BSA, these two neoglycoproteins both
had apparent Kd values of 8 nM (see Table 1). At a ratio of 1:7,
binding was weaker for both conjugates, and modest differences
in avidities could be detected. In particular, LacNAc(trimeric)-
BSA had about a 4 fold better apparent Kd (83 vs 307 nM).
One explanation for the observed binding is that RCA120
can form high avidity, bridging complexes with both neogly-
coconjugates at high neoglycoprotein density. At low neogly-
coprotein density, RCA120 can still form multivalent complexes
with both ligands, but the resulting 1:1 complexes are 10-40
fold weaker than the corresponding bridging complexes formed
at high neoglycoprotein density. In addition, RCA120 displays
a difference in selectivity when binding in a 1:1 complex, with
LacNAc(trimeric)-BSA being bound more tightly. Based on this
hypothesis, both neoglycoproteins should function as solution
inhibitors, but LacNAc(trimeric)-BSA should be better. To test
this, an ELISA-like inhibition assay was used. Both neoglyco-
proteins were found to inhibit binding; however, LacNAc
(trimeric)-BSA was about 10-fold better [IC50 for LacNAc
(trimeric)-BSA ) 11.5 ( 0.8 nM; IC50 for Lac-BSA ) 114 (
3 nM]. The inhibition constants were consistent with our array
results, although the absolute difference between the neogly-
coproteins at 1:7 was not as large as the difference measured
in solution (4-fold vs 10-fold, respectively). By evaluating
binding at multiple neoglycoprotein densities, we were able to
detect differences in binding that could not have been predicted
on the basis of binding at high neoglycoprotein density alone.
Rapid Identification of Multivalent Inhibitors of PA-IL. On
the basis of the success with the plant lectins, we next applied
the new array to the identification of inhibitors of a lectin
involved in bacterial infections. P. aeruginosa is an opportunistic
bacteria causing numerous nosocomial diseases, such as septi-
cemia, urinary tract infections, pancreatitis, and dermatitis. P.
aeruginosa lectin I (PA-IL) is a soluble carbohydrate-binding
protein from the bacteria P. aeruginosa.49-51 It is a galactose-
binding, C-type lectin consisting of 121 amino acids (12.75
kDa), and the crystal structure reveals that it is a tetramer with
a rectangular shape.52 PA-IL is a virulence determinant, and P.
aeruginosa lethality is dependent on its expression.51,53 PA-IL
also contributes to biofilm formation, as demonstrated by studies
of P. aeruginosa variants lacking or overexpressing the lectin.54
Therefore, PA-IL has become an important molecular target for
P. aeruginosa, infections and several inhibitors have been
reported in the literature.50,52,55 PA-IL is known to bind glycans
terminating in a Gal-R residue, such as GalR1-4Gal
1-4Glc
(Pk) and GalR1-3Gal
1-4GlcNAc (alphaGal).49,50,52,54 Previ-
ous studies have also shown that multivalent conjugates with
GalNAc
1-4Gal
 (the terminal disaccharide of GA2; GA2di)
can inhibit P. aeruginosa binding.56 The specificity of PA-IL
has also been evaluated previously on several glycan arrays.25,57,58
Our objective was to use the array to rapidly identify high
avidity, solution-phase inhibitors of PA-IL. His-tagged PA-IL25
was evaluated at a range of concentrations on the array, and
the apparent Kd values at various neoglycoprotein densities were
determined. This lectin bound a number of glycans with terminal
alpha-linked Gal or GalNAc residue, and the best ligands at
low neoglycoprotein density are listed in Table 2 (complete data
can be found in the Supporting Information). On the basis the
array binding at low neoglycoprotein density, several neogly-
coproteins were predicted to be good solution-phase inhibitors,
including RGal, P1, Pk, BG-B, and Bdi. Two of these, RGal and
Pk, were selected for additional studies to confirm inhibitory
activity. Solution inhibition was measured using an ELISA-
like assay as before. Both conjugates were excellent inhibitors:
RGal-BSA had an IC50 of 30 ( 3 nM, and Pk-HSA had an IC50
of 64 ( 12 nM. For comparison, galactose showed 32%
inhibition at a concentration of 400 mM under the same
conditions.
PA-IL had poor binding to GalNAc
1-4Gal
-containing
neoglycoproteins on our array, indicating that they should not
be good inhibitors of PA-IL. Nevertheless, previous published
studies had shown that other multivalent GalNAc
1-4Gal

conjugates do bind PA-IL. Therefore, we also tested the
(47) Itakura, Y.; Nakamura-Tsuruta, S.; Kominami, J.; Sharon, N.; Kasai,
K. I.; Hirabayashi, J. J. Biochem. (Tokyo) 2007, 142, 459–469.
(48) Podder, S. K.; Surolia, A.; Bachhawat, B. K. Eur. J. Biochem. 1974,
44, 151–160.
(49) Imberty, A.; Wimmerova, M.; Mitchell, E. P.; Gilboa-Garber, N.
Microbes Infect. 2004, 6, 221–228.
(50) Kirkeby, S.; Hansen, A. K.; d’Apice, A.; Moe, D. Microb. Pathog.
2006, 40, 191–197.
(51) Chemani, C.; Imberty, A.; De Bentzmann, S.; Pierre, M.; Wimmerova,
M.; Guery, B. P.; Faure, K. Infect. Immun. 2009, 77, 2065–2075.
(52) Cioci, G.; Mitchell, E. P.; Gautier, C.; Wimmerova, M.; Sudakevitz,
D.; Perez, S.; Gilboa-Garber, N.; Imberty, A. FEBS Lett. 2003, 555,
297–301.
(53) Laughlin, R. S.; Musch, M. W.; Hollbrook, C. J.; Rocha, F. M.; Chang,
E. B.; Alverdy, J. C. Ann. Surg. 2000, 232, 133–142.
(54) Diggle, S. P.; Stacey, R. E.; Dodd, C.; Camara, M.; Williams, P.;
Winzer, K. EnViron. Microbiol. 2006, 8, 1095–1104.
(55) Hauber, H. P.; Schulz, M.; Pforte, A.; Mack, D.; Zabel, P.; Schuma-
cher, U. Int. J. Med. Sci. 2008, 5, 371–376.
(56) Autar, R.; Khan, A. S.; Schad, M.; Hacker, J.; Liskamp, R. M. J.;
Pieters, R. J. ChemBioChem 2003, 4, 1317–1325.
(57) Moni, L.; Pourceau, G.; Zhang, J.; Meyer, A.; Vidal, S.; Souteyrand,
E.; Dondoni, A.; Morvan, F.; Chevolot, Y.; Vasseur, J. J.; Marra, A.
ChemBioChem 2009, 10, 1369–1378.
(58) ConA, VVL-B4, RCA120, PA-IL, and mMGL-2 have been screened
by the Consortium for Functional Glycomics, and binding data can
be found at http://www.functionalglycomics.org/glycomics/publicdata/
primaryscreen.jsp.
Table 2. Binding Dataa for Pseudomonas aeruginosa Lectin I
(PA-IL)
apparent Kd (nM) solution inhibition
ligand at 1:7 p valueb IC50 (nM) p valueb
Pk 200 ( 51 - 64 ( 12 -
Adi-17 336 ( 99 0.23
RGal 292 ( 87 0.33 30 ( 3 0.06
Bdi 282 ( 56 0.27
BG-B (EMD) 291 ( 91 0.34
GA2di-37 ND <0.0005 >758 <0.0005
GalR1-4Gal
 319 ( 64 0.18
G2M4 138 ( 35 0.29
LacNAc 253 ( 24 0.32
P1 128 ( 30 0.23
a Values have not been adjusted for valency. ND (not determined)
denotes some binding but apparent Kd too large to measure. Complete
binding data can be found in the Supporting Information. b p values
refer to a comparison between the Kd and the IC50 value for Pk and each
of the other neoglycoproteins (paired t-test).
9660 J. AM. CHEM. SOC. 9 VOL. 132, NO. 28, 2010
A R T I C L E S Zhang et al.
corresponding neoglycoprotein, GA2di-37-BSA, in the solution
inhibition assay. As expected from the array data, it did not
show any significant inhibition in solution at a concentration
of 758 nM. This result highlights one of the major difficulties
in designing multivalent probes. Although a specific carbohy-
drate may be an excellent ligand when presented on a particular
scaffold, it may be a poor ligand when presented on a different
multivalent scaffold. Therefore, the ligand and scaffold must
be optimized simultaneously. Our array format provides a high-
throughput means to identify appropriately matched ligands and
scaffolds.
Rapid Identification of Multivalent Inhibitors of mMGL-2.
Macrophage galactose-type lectins are C-type lectins expressed
as homo-oligomers on myeloid antigen presenting cells (APC),
such as macrophages and dendritic cells (DCs).59-61 Mice
express two related lectins, mMGL-1 and mMGL-2, whereas
humans express a single MGL. mMGL-1 and mMGL-2 have
distinct carbohydrate-binding specificities, and mMGL-2 has
been found to be more similar to human MGL.59,60,62 The
biological roles of mMGL-2 are still being elucidated, but it is
thought to be involved in immune recognition of pathogens,
internalization of antigens, and regulation of effector T cells.61
Human MGL has also been implicated in viral infection and
immune evasion by tumor cells.61 For these reasons, inhibitors
with high affinity and selectivity would be useful tools for
studying the biological roles of this protein and evaluating its
potential as a receptor for antigen targeting for vaccines.
mMGL-2 has been shown previously to bind several tumor-
associated carbohydrate antigens, including the Tn antigen
(GalNAc-R-Ser/Thr) and the Thomsen-Friedenreich disaccharide
(TF, Gal
1-3-GalNAc-R-Ser/Thr).59,60,62 In the studies by
Irimura and colleagues, mMGL-2 was found to preferentially
bind GalNAc-terminal oligosaccharides. The best solution-phase
inhibitor for mMGL-2 was found to be Gb4, with a Kd value of
19.2 µM.62 No solution-phase multivalent inhibitors were
reported, but binding to a multivalent surface containing a
terminal GalNAc-
 provided a Kd value of 2.1 µM. In a separate
report, Irimura found that multivalent polyacrylamide polymers
containing GalNAc-
 provided the best binding to surface-
immobilized mMGL-2, but solution-phase inhibition was not
tested.59 In a study by van Kooyk and colleagues, mMGL-2
was found to have broader specificity, with binding to both
GalNAc- and Gal-terminal structures. Multivalent polyacryla-
mide polymers displaying GalNAc-R, GalNAc-
, or core 1 were
found to bind to cells expressing mMGL-2, but affinities were
not reported.60 As a qualitative measure of binding, about 35%
of mMGL-2 positive cells were bound by the multivalent
polymers in a flow cytometry assay when using a concentration
of about 0.5 µM polymer. While these results are promising, it
is unlikely that a monosaccharide-based ligand would display
sufficient selectivity for most biological applications. Therefore,
more potent and selective multivalent inhibitors for mMGL-2
would be useful.
Our objective was to use the array to identify high avidity,
solution-phase inhibitors of mMGL-2. As with our previous
experiments, mMGL-2 was assessed at a range of concentrations
and the apparent Kd values were determined at various neogly-
coprotein densities. The earlier reports by van Kooyk and
Irimura showed some discrepancies in the binding specificity
of mMGL-2. Similar to the van Kooyk study, we observed
binding to glycans with both terminal GalNAc and Gal. In
general, however, the GalNAc terminal glycans bound better,
and the preference for GalNAc over Gal was more prominent
at lower neoglycoprotein densities, suggesting that they would
be better soluble inhibitors. The best ligands at low neoglyco-
protein density are listed in Table 3 (complete data can be found
in Table S9, Supporting Information). Solution inhibition was
evaluated in an ELISA-based assay for two of the best ligands
to confirm the predicted activity. On the basis of the inhibition
curves, GA2di-37-BSA had an IC50 of 15 ( 6 nM, and Ac-
TnSer-TnSer-TnSer-G-27-BSA had an IC50 of 28 ( 12 nM. Thus,
within a single day, we were able to identify potent neoglyco-
protein inhibitors for mMGL-2.
Conclusion
Multivalent interactions play a critical role in a wide variety
of biological processes and are especially important for recogni-
tion of carbohydrates. To achieve a multivalent complex, the
spacing and orientation of ligands must be properly matched to
the binding sites of the receptor. Therefore, both ligand structure
and ligand presentation are critical features for binding in natural
systems and for the design of inhibitors or probes to modulate
natural recognition events. Identification of the optimal com-
bination of ligand structure and multivalent presentation can
be challenging, especially in the absence of structural informa-
tion on the receptor.
The array format described in this study provides a high-
throughput tool for rapidly evaluating relationships between
ligand structure, presentation, and recognition. In particular, it
allows one to discriminate between different types of multivalent
complexes on the array surface. To illustrate the utility of this
array format, it was used to identify multivalent neoglycoprotein
inhibitors/probes of several lectins. The construction of the array
is simple and economical, and the screening process can be
completed in a single day. In addition, no structural information
on the receptor is required to identify a multivalent probe. The
array format will be useful for other applications as well. For
example, many proteins, especially glycan-binding proteins,
(59) Tsuiji, M.; Fujimori, M.; Ohashi, Y.; Higashi, N.; Onami, T. M.;
Hedrick, S. M.; Irimura, T. J. Biol. Chem. 2002, 277, 28892–28901.
(60) Singh, S. K.; Streng-Ouwehand, I.; Litjens, M.; Weelij, D. R.; Garcı̃a-
Vallejo, J. J.; van Vliet, S. J.; Saeland, E.; van Kooyk, Y. Mol.
Immunol. 2009, 46, 1240–1249.
(61) van Vliet, S. J.; Saeland, E.; van Kooyk, Y. Trends Immunol. 2008,
29, 83–90.
(62) Oo-puthinan, S.; Maenuma, K.; Sakakura, M.; Denda-Nagai, K.; Tsuiji,
M.; Shimada, I.; Nakamura-Tsuruta, S.; Hirabayashi, J.; Bovin, N. V.;
Irimura, T. Biochim. Biophys. Acta 2008, 1780, 89–100.
Table 3. Binding Dataa for Mouse Macrophage Galactose-Type
Lectin-2 (mMGL-2)
apparent Kd (nM) solution inhibition
ligand at 1:7 p valueb IC50(nM) p valueb
GA2di-37 3.6 ( 0.8 - 15 ( 6 -
Ac-A-TnThr-S-G-23 4.9 ( 2.0 0.48
Ac-S-TnThr-A-G-22 4.1 ( 1.4 0.70
Ac-S-TnThr-G-G-19 4.6 ( 1.9 0.56
Ac-S-TnThr-S-G-24 3.8 ( 1.5 0.88
Ac-TnThr-G-21 5.1 ( 1.5 0.34
Ac-TnSer-TnSer-TnSer-G-27 4.4 ( 2.4 0.70 28 ( 12 0.30
Ac-V-TnThr-S-G-19 5.4 ( 1.9 0.34
GA2di-16 5.1 ( 1.7 0.38
GalNAc-R-22 5.0 ( 1.2 0.30 89 ( 53 0.19
a Values have not been adjusted for valency. Complete binding data
can be found in the Supporting Information. b p values refer to a
comparison between the Kd and the IC50 of GA2di-37 and the other
neoglycoproteins (paired t-test).
J. AM. CHEM. SOC. 9 VOL. 132, NO. 28, 2010 9661
Array-Based Method To Identify Multivalent Inhibitors A R T I C L E S
have overlapping specificities. The array format described in
this study provides one approach to distinguish proteins with
similar ligand preferences but distinct architectures. In principle,
it could also be used to distinguish different forms or oligomeric
states of the same protein. Therefore, variation of neoglyco-
protein density provides a more comprehensive view of
carbohydrate recognition and is a useful element of diversity
for inclusion on glycan arrays. While this study focused on
interactions between carbohydrates and proteins, the approach
could also be used to discover multivalent inhibitors for
interactions between other biomolecules.
Acknowledgment. We thank Professor Lara Mahal for the
generous gift of PA-IL. We thank the Optical Microscopy and
Analysis Laboratory, SAIC-Frederick, Inc., Advanced Technology
Program for use of the confocal microscope. This research was
supported by the Intramural Research Program of the NIH, NCI.
Supporting Information Available: Confocal microscope
images of AF488-BSA on the array surface at 1:0, 1:1, 1:3,
and 1:7; characterization of the AF555-BSA conjugates; full
array data and fluorescence intensities for ConA, VVL-B4,
RCA120, PA-IL, and mMGL-2; and a full list of array
components. This material is available free of charge via the
Internet at http://pubs.acs.org.
JA100608W
9662 J. AM. CHEM. SOC. 9 VOL. 132, NO. 28, 2010
A R T I C L E S Zhang et al.