Antibodies can evolve to recognize essentially any protein with high specificity and affinity. While natural antigen binding sites utilize all 20 natural amino acids to some extent, analysis of functional antibodies reveals clear biases for or against some amino acids. Most significantly, tyrosine and serine are highly abundant in antigen binding sites in general and at antigen contact positions in particular.

The increased understanding of antibody sequence and structure in relation to function has enabled the development of synthetic antibody libraries. Having entirely artificially constructed antigen binding sites, the use of synthetic libraries and in vitro display methods completely circumvents the machinery of the immune system. We have used human synthetic antibody phage libraries to investigate the roles of different chemical diversity in antigen recognition. Using a tetranomial genetic code that allows for only four amino acids (tyrosine, serine, alanine and aspartate) we were able to generate antibodies against vascular endothelial growth factor (VEGF) that bound with high affinity and specificity. Structural and mutational analyses indicated that tyrosine was the major mediator of binding energy of the anti-VEGF Fabs, and the results suggested that it might be possible to further simplify the code for antigen recognition. Hence, a Fab library was constructed in which the combining sites were randomized with a binary genetic code that only allowed for tyrosine and serine. Remarkably, this very restricted library was extremely effective in generating highly specific antibodies against a wide array of antigens. Furthermore, the binary Fabs exhibited exquisite specificity in cell-based assays. The structures of these antibody fragments in complex with antigen revealed that the highly homogonous binding surfaces are dominated by tyrosine, but nonetheless, recognized diverse chemical groups of the antigens. In contrast, the serines seem to have a more subordinate role in providing space and conformational flexibility between the tyrosines and the antigen.

To further explore the mechanisms mediating molecular recognition we systematically added back chemical and conformational diversity into the binary background in a precisely defined manner. These studies indicated that certain amino acids possess features that increase the likelihood of making productive contributions to binding affinity and specificity. Thus, biased libraries that favor such amino acids are likely to be much more effective in generating antibodies with high affinity and specificity. As a corollary, other amino acids are ill suited for productive contacts, and the absence or depletion of such amino acids will likely improve naive antigen recognition.

Up to now, most of our work has focused on finding binders to soluble protein antigens. In ongoing studies, however, we are now exploring an extension of the synthetic approach to also include targeting of integral membrane proteins. Membrane proteins are crucial players in cellular biology and take centre stage in a large variety of biological functions, including translocation of molecules and ions into and out of cells and signal transduction across membranes. Furthermore, membrane proteins are prime targets for drug development. Yet the function of these proteins is poorly understood. Antibodies targeting these could be used as tools, in structural as well as functional studies, to help elucidate the mechanism of this important group of molecules. Building on our previous studies, various design principles will be investigated to define optimal conditions to efficiently accommodate binders to membrane proteins. The findings will have significant implications for the fundamental principles and mechanisms that mediate molecular recognition at protein-protein interfaces. In addition, given the fundamental importance of membrane proteins, the obtained antibody fragments are likely to find utility in applications ranging across basic research, disease diagnostics and the development of therapeutics.

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