Protein functional analysis in the post-genomic era is a huge task that has to be approached by different methods in parallel. The use of protein-specific antibodies in conjunction with tissue microarrays has proven to be one important technology. In this study, we present a strategy for the optimized design of protein subfragments for subsequent antibody production. The fragments are selected based on a principle of lowest sequence similarity to other human proteins, optimally to generate antibodies with high selectivity. Furthermore, the fragments should have properties optimized for efficient protein production in Escherichia coli. The strategy has been implemented in Bishop, which is a Java-based software enabling the high-throughput production of protein fragments. Bishop allows for the avoidance of certain restriction enzyme sites, transmembrane regions, and signal peptides. A Basic Local Alignment Search Tool (BLAST) scanning procedure permits the selection of fragments of a selected size with a minimal sequence similarity to other proteins. The software and the strategy were evaluated on a human test data set and verified to fulfill the requested criteria.

Here, we present an antigen selection strategy based on a whole-genome bioinformatics approach, which is facilitated by an interactive visualization tool displaying protein features from both public resources and in-house generated data. The web-based bioinformatics platform has been designed for selection of multiple, non-overlapping recombinant protein epitope signature tags by display of predicted information relevant for antigens, including domain- and epitope sized sequence similarities to other proteins, transmembrane regions and signal peptides. The visualization tool also displays shared and exclusive protein regions for genes with multiple splice variants. A genome-wide analysis demonstrates that antigens for approximately 80% of the human protein-coding genes can be selected with this strategy.

A great need exists for prediction of antibody response for the generation of antibodies toward protein targets. Earlier studies have suggested that prediction methods based on hydrophilicity propensity scale, in which the degree of exposure of the amino acid in an aqueous solvent is calculated, has limited value. Here, we show a comparative analysis based on 12,634 affinity-purified antibodies generated in a standardized manner against human recombinant protein fragments. The antibody response (yield) was measured and compared to theoretical predictions based on a large number (544) of published propensity scales. The results show that some of the scales have predictive power, although the overall Pearson correlation coefficient is relatively low (0.2) even for the best performing amino acid indices. Based on the current data set, a new propensity scale was calculated with a Pearson correlation coefficient of 0.25. The values correlated in some extent to earlier scales, including large penalty for hydrophobic and cysteine residues and high positive contribution from acidic residues, but with relatively low positive contribution from basic residues. The fraction of immunogens generating low antibody responses was reduced from 30% to around 10% if immunogens with a high propensity score (>0.48) were selected as compared to immunogens with lower scores (<0.29). The study demonstrates that a propensity scale might be useful for prediction of antibody response generated by immunization of recombinant protein fragments. The data set presented here can be used for further studies to design new prediction tools for the generation of antibodies to specific protein targets.

We describe a method for mapping the epitopes recognized by antibodies, based on bacterial surface expression of antigen protein fragments followed by antibody-based flow-cytometric sorting. We analyzed the binding sites of both monoclonal and polyclonal antibodies directed to three human protein targets: (i) the human epidermal growth factor receptor 2 (HER2), (ii) ephrin-B3 and (iii) the transcription factor SATB2. All monoclonal antibodies bound a single epitope, whereas the polyclonal antibodies showed, in each case, a binding pattern with one to five separate epitopes. A comparison of polyclonal and monoclonal antibodies raised to the same antigen showed overlapping binding epitopes. We also demonstrated that bacterial cells with displayed protein fragments can be used as affinity ligands to generate epitope-specific antibodies. Our approach shows a path forward for systematic validation of antibodies for epitope specificity and cross-reactivity on a whole-proteome level.

Antibodies have become valuable therapeutic agents for targeting of extracellular proteins in various diseases, including cancer, autoimmunity and cardiovascular disorders. For breast cancer, antibodies targeting the human HER2 have been shown to result in cell growth inhibition both in vitro and in patients with breast tumors. There is evidence to suggest that targeting multiple HER2 epitopes may result in increased growth inhibition making it interesting to find antibodies targeting new epitopes. Here, we report on a new scheme to discover antibodies directed to new epitopes using the extracellular domain of the HER2 as a model. Polyclonal antibodies were generated using recombinant protein fragments and affinity purified fractions of the antibodies were functionally characterized and precisely epitope mapped using bacterial surface display. Polyclonal antibodies towards a 127 amino acid recombinant protein fragment spanning between domains II and III of the HER2 were shown to bind to human ductal carcinoma cell line BT474 resulting in growth inhibition. Affinity purification demonstrated that antibodies to two separate regions from the N- and C-terminal end of the fragment exhibited the growth inhibition. Epitope mapping of the C-terminal antibodies revealed a 25 amino acid region (LPESFDGDPASNTAPLQPEQLQVF) with two distinct epitopes mediating efficient growth inhibition. The results suggest that antibodies directed towards this region of domain III of the HER2, distinct from the well-known monoclonal antibodies trastuzumab and pertuzumab, bind to the HER2 on living cells and exhibit growth inhibition. The work describes a new strategy to develop antibodies directed to non-overlapping epitopes and shows a path of pursuit to explore the epitope space of a target protein.