Small molecule-based binding environments: Combinatorial construction of microarrays for multiplexed affinity screening

Article abstract of DOI:10.1021/ja9046944

(Figure Presented) This paper describes the construction of a combinatorial artificial receptor array (CARA) and the application of the array to differentiation of proteins based on their binding patterns. Microarrays displaying 5035 unique binding enviro

Full text of DOI:10.1021/ja9046944

Published on Web 10/29/2009
Small Molecule-Based Binding Environments: Combinatorial Construction of
Microarrays for Multiplexed Affinity Screening
Rachel L. Weller Roska, Tenzing Gawa Surshar Lama, Jay P. Hennes, and Robert E. Carlson*
RECEPTORS LLC, 1107 Hazeltine BouleVard, Suite 510, Chaska, Minnesota 55318
Received June 9, 2009; E-mail: bc@receptorsllc.com
Chart 1. Building Block Library
The preparation of stable and diverse binding agents in an
addressable format is an objective with myriad applications in
proteomics, diagnostics, pharmaceutical development, and related
fields. Significant advances toward this aim have been made, and
among them microarray-based technologies stand out on the basis
of a high-throughput and miniaturized format. In particular, small
molecule microarrays1 (SMMs) have contributed to the expansion
of our capabilities in high-throughput screening. The use of synthetic
molecules as capture agents bypasses the limitations of approaches
that rely on inherently unstable biomolecules, such as antibodies,
which can also be laborious and expensive to prepare.2 The number
and variety of small molecules available for immobilization in
microarray format have vastly increased through the development
of diversity-oriented synthesis.3 However, the diversity and speci-
ficity of the most prominent microarray capture agents, antibodies,2c
are still unparalleled.4 Pattern-based molecular recognition, which
takes into account the composite binding response of a target across
an entire array, has taken us a step closer to resolving this problem
and extends the utility of the SMM beyond straightforward lead
discovery.5 However, these microarray strategies still require that
each binding agent be discretely synthesized and they principally
rely on monovalent interactions with the target.
Microarrays composed of multicomponent,6 small molecule-
based binding enVironments would more closely mimic receptor-
like polyvalent binding and facilitate rapid and flexible access to
the breadth and depth of binding space. We report here a com-
binatorial artificial receptor array (CARA) constructed from indi-
vidual small molecule building blocks immobilized in combinations
to form unique and diverse binding environments. A small but
diverse library of building blocks (Chart 1, 1-19), designed to
incorporate a range of size, polarity, log P, and aromaticity, was
synthesized. The strategy behind building block design was to
mimic and expand upon the functional group diversity of nature’s
library of amino acids, for example, as presented in an antibody
binding pocket. Our library is naive to the target analyte. Each
building block was equipped with a pendant carboxylic acid,
allowing mixtures of the building blocks to be spotted onto the
surface of an amine functionalized slide for covalent immobilization
as subunits of the binding environment. In this way, the surface7
serves as an efficient platform for the combinatorial construction
of thousands of discrete binding environments from a concise library
of individual small molecules, eliminating the need to discretely
synthesize thousands of individual binding agents.
building blocks arrayed in combinations displaying one, two, three,
or four different building blocks in each binding environment
(microarray “spot”)). Each binding environment was printed in
duplicate, along with control spots for a total of 10 468 spots per
microarray. The binding environments are covalently formed and
stable,8 and the building blocks present in every binding environ-
ment are known. This strategy contrasts with existing methods1,5,7
which are dependent on the production of molecular libraries equal
in size to the desired number of capture agents for an array,
including other methods which rely on in situ synthesis on the
surface. Moreover, many of these methods require a deconvolution
step to identify the compounds printed in a particular spot.1c
Four fluorescently labeled proteins, ubiquitin, myoglobin, R-1-
acid glycoprotein, and lysozyme, were incubated with N19n1-4 arrays
to demonstrate the reproducibility of binding and the differentiation
of analytes that can be achieved with CARA binding environments.
Each array was incubated with 100 nM protein and scanned using
a GenePix Personal 4100A fluorescence microarray scanner (Axon
Instruments). Figure 2a shows a fluorescence scan of one entire
Microarrays displaying 5035 unique binding environments were
prepared using our library of 19 small molecule building blocks.
The pendant carboxylic acids of the individual building blocks were
activated as sulfo-NHS esters, followed by preparation of solutions
containing individual activated building blocks or combinations of
two, three, or four building blocks, which were then spotted onto
the surface of the amine-functionalized glass slide (Figure 1). This
array configuration is referred to as an N19n1-4 array (19 individual
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C O M M U N I C A T I O N S
Figure 1. A schematic representation of the CARA building block
combination and printing process.
array that was incubated with ubiquitin. The range of binding across
the binding environments spans from 1779 to 65 535 fluorescence
units (FU). Lower protein concentrations can be used, and a similar
range of fluorescence signal can be achieved by adjusting the
instrument gain (data not shown). A reduction in binding pattern
diversity was typically observed with incubation concentrations
below 15 nM (pg/mL range) (data not shown). Figure 2b-e shows
one segment of the N19n1-4 array from each of four individual
protein incubations. The binding differences of the proteins are
evident upon simple visual inspection of these fluorescence scans.
Quantitation of the binding patterns for each of the proteins
further illustrates the binding differences and highlights the
reproducibility of binding, as well as the reproducibility of array
construction. Quadruplicate incubations were completed for each
protein, and the fluorescence values for each binding environment
were quantitated using GenePix Pro 6.1 software. Figure 3a shows
a scatter plot comparing the binding data for the first of each
duplicate spot on a ubiquitin-incubated array vs the second duplicate
spot on the same array. Binding reproducibility is exemplified by
the correlation coefficient, 0.99, which is representative of those
observed for the other protein incubations (data not shown). A
scatter plot illustrating the reproducibility of binding across two
separate array incubations for ubiquitin is shown in Figure 3b.
Corresponding scatter plots for the other three proteins are shown
in Figures S2-S4 in the Supporting Information. The correlation
coefficients for each protein were 0.98 for ubiquitin, 0.97 for R-1-
acid glycoprotein, 0.98 for myoglobin, and 0.96 for lysozyme. This
high correlation of binding across duplicate arrays clearly demon-
strates the reproducibility of our approach to binding environment
construction. The fluorescence units from the quadruplicate incuba-
tions for each protein were averaged,9 and scatter plots comparing
binding data for each protein vs the other three proteins are shown
in Figure 3c-h. It is apparent that the binding patterns for the
proteins are dramatically different. There is a range of differentiation
among the protein pairings, with some of the binding patterns
differing more than others. In the case of two more similar binding
patterns, such as those of ubiquitin and myoglobin (Figure 3h),
Figure 2. Fluorescence scans of incubated microarrays. (a) Full array
incubated with ubiquitin. Zooms of one section of a microarray incubated
with (b) ubiquitin, (c) R-1-acid glycoprotein, (d) myoglobin, and (e)
lysozyme. Stray flecks of fluorescence visible outside the printed spots in
(a), (d), and (e) are artifacts, most likely due to imperfections in the slide
surface.
there are still numerous binding environments within the array that
distinguish the proteins. These data clearly demonstrate the capacity
of the combinatorial binding environments to differentiate proteins
via their binding patterns, which underscores the potential value
the arrays hold for a variety of applications.
An advantage of the CARA strategy is the enormous flexibility
it enables in the preparation of alternate microarray configurations,
which can be tailored for specific applications. A recognized
bottleneck in microarray technology is synthesis and display of
binding agents.1b Addition of a single building block to the N19n1-4
array configuration would result in an N20n1-4 array affording 1159
new binding environments, for a total of 6195. For some applica-
tions it may be advantageous to probe binding environments of
greater complexity (more building blocks per binding environment).
Arraying the original 19 building blocks in combinations of up to
five building blocks per environment (an N19n1-5 array) would yield
16 663 binding environments. Alternatively, binding environments
with increased chemical complexity can be screened through the
sequential use of two array configurations. An N29n1-2 array (435
binding environments) displays 29 building blocks singly or in pairs.
This array allows a wider diversity of chemical functionality to be
screened through the use of a larger building block library, while
maintaining a manageable number of binding environments. Binding
data from this array can be used to select the building blocks that
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using the microarrays to screen for candidate binding environments
with binding characteristics appropriate for biosensor applications
and for construction on self-assembled monolayers for surface
plasmon resonance, as well as surfaces appropriate for mass
spectrometric analysis. Nonprotein analytes currently under inves-
tigation with CARA microarrays include small molecules, microbes,
nucleic acids and cells. The fact that the binding environments are
constructed from synthetic small molecules makes them readily
scalable to large batch sizes for a wide range of formats and
applications.
We constructed combinatorial artificial receptor arrays, which
offer significant advantages over existing small molecule microarray
strategies, and demonstrated their capacity for protein differentiation.
The CARA strategy employs the microarray surface as the com-
binatorial synthesis platform, which allows for flexibility in array
preparation and agility in application. Thousands of unique and
diverse binding environments were generated from 19 discretely
synthesized building blocks. Binding is reproducible, indicating that
array construction is also reproducible, and the diversity of binding
across the array shows that a wide range of binding interactions
are possible.
Acknowledgment. We are grateful to Robert M. Carlson and
Thomas Kodadek for helpful discussions; Robert Kaufman, Bryan
Jones, Erika Walden, and Diane Isabell for their contributions to
this manuscript; and the University of Minnesota NMR lab.
Supporting Information Available: General synthetic scheme,
characterization data for 1-19, experimental procedures for building
block activation and printing and protein labeling and incubation. This
material is available free of charge via the Internet at http://pubs.acs.org.
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Figure 3. Scatter plots comparing binding data for (a) duplicate spots from
one microarray incubated with ubiquitin, (b) two separate ubiquitin
incubations, (c) R-1-acid glycoprotein vs lysozyme incubations, (d) R-1-
acid glycoprotein vs myoglobin incubations, (e) R-1-acid glycoprotein vs
ubiquitin incubations, (f) lysozyme vs myoglobin incubations, (g) lysozyme
vs ubiquitin incubations, and (h) myoglobin vs ubiquitin incubations.
exhibit the desired affinity characteristics. These building blocks
are then arrayed in a more focused, but higher order configuration,
such as an N9n1-9 array (511 binding environments). Using arrays
in tandem facilitates access to a depth of binding space that is
comparable to, but more targeted than, a single array that incor-
porates more building blocks in more combinations. For example,
an N29n1-9 array would require printing and analysis of greater than
16 million binding environments. This sequential array workflow
also provides the advantage of preselection of targeted binding
characteristics using the first array and further fine-tuning of those
binding results in the second array.
Ongoing work in our lab is focused on application of CARA
microarrays to a wider variety of analytes and adaptation of binding
environments to supports other than glass slides. We are using the
sequential array workflow described above to identify lead binding
environments for construction of selective affinity purification
supports on polymeric and controlled-pore glass beads. We are also
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(8) The binding characteristics of the arrays did not deteriorate after heating at
80 °C in an oven or boiling in 20% aqueous ethanol for 2 h (data not shown).
(9) The average coefficients of variation (CV) for the binding environments
within a quadruplicate set were 8% for ubiquitin, 13% for R-1-acid
glycoprotein, 14% for myoglobin, and 9% for lysozyme.
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