Target Discovery and Validation Reviews and Protocols

Protein Arrays 337
Table 1
Classification of Protein Arrays by Capture/Target Molecules
Target molecular
Capture molecular (immobilized) (hybridized with) References
Monoclonal antibodies, Serum, cellular lysates, (27,28,54–56)
single-chain Fv antibodies antibodies
Atigens (proteins, peptides, Serum (29–32,57)
enzyme complexes,
ribonucleoprotein
complexes, DNA)
Protein fraction from Serum (33,34)
chromatographic separation
(that may be further identified
with mass spectrometry)
(reverse phase arrays)
Yeast two-hybrid system (colony Binding constructs (3–5,58)
arrays)
Recombinant proteins Serum, antibodies, (37–39,41,59,60)
kinases
Random peptides/cDNA libraries Serum, antibodies (11,13–16,18–20,
displayed on phage 43,45,61–66)
Ribosome display Serum, antibodies (48,49)
reproducible, and quantitative (23–27). Together, these experimental features
provide the technology with great potential to have a significant impact on
cancer research.
A protein microarray may consist of antibodies, proteins, protein fragments,
peptides, aptamers, or carbohydrate elements that are coated or immobilized in
a grid-like pattern on small surfaces. The arrayed molecules are then used to
screen and assess patterns of interaction with samples containing distinct
proteins or classes of proteins. There is great variation in use of the protein
microarray technique, when considering selection of the capture molecules.
Aspects of protein coupling to surfaces, sensitivity, dynamic range of detection
techniques, and standardization of data remain to be solved.
One of the critical factors for construction of protein microarrays is the
choice of captures molecules that could optimally find proteins/antibodies in
a complex sample. A diverse set of capture molecules have been used for
screening of serum/antibodies (Table 1). Notably, screening protein arrays
with sera from patients with either cancer or autoimmune diseases would
facilitate the identification of potentially new autoantigens that could be valuable
for diagnosis and classification of patients. Here, a summary is provided of