CAREER: Generation of Highly Selective Inhibitory Antibodies by Novel Paratope Design, Function-Based Screening, and Deep Sequencing

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1453645Ge, Xin This research will significantly advance our understanding on the mechanisms of enzymatic inhibition and virus neutralization, and thus will lead to development of a panel of novel methods for the generation of highly potent inhibitory antibodies for a broad range of applications in pharmaceutical and biotechnological industries. Specifically, the work aims to develop antibodies that interfere and inhibit the binding of protein cleaving enzymes or proteases. The project will (i) increase US technological competitiveness; (ii) develop a globally competitive STEM workforce; (iii) increase participation of women and underrepresented minorities; and (iv) contribute to undergraduate and graduate STEM education. UC Riverside is the minority serving institution with the largest Hispanic student population among all UC campuses. More specifically, the PI plans to first prepare UCR STEM undergraduates for a global marketplace and dynamic scientific communities through collaboration with two Chinese universities; and second increase university/college enrollment of high school graduates in Riverside and San Bernardino Counties, especially those from minority and other disadvantaged socio-economic backgrounds, by inspiring their interests in science and engineering programs through lectures, workshops and interacting events. As extremely important signaling molecules, proteases precisely control a wide variety of physiological processes, and thus represent one of the largest families of potential pharmaceutical targets. Considering that ~2% of the human genome is estimated to encode proteases, specificity is highly desired for any protease inhibition therapy. However, proteases share high amino acid similarity among the same class of proteases and their active sites are extensively conserved. It has been a challenging task to develop small molecule inhibitors that can deliver required specificities. Therefore, antibodies are emerging as a very attractive alternative for highly selective inhibition. To date, at least three obstacles make the routine discovery of protease-inhibiting monoclonal antibodies (mAbs) considerably difficult: (i) low antigenicity of the proteolytic active sites, (ii) lack of a function-based selection method, and (iii) loss of beneficial clones during the selection. The long-term goal of this CAREER award is to develop therapeutic monoclonal antibodies (mAbs) or biologics that inhibit specific proteases for biomedical applications. The objective of this research is to overcome the technical hurdles and establish general methodologies that facilitate the identification of inhibitory antibodies. The hypothesis is that convex antigen-binding sites (paratopes) are inhibition-prone. This central hypothesis will be tested by the following three specific approaches: (1) Clearly verify inhibition mechanisms by design, construction and optimization of synthetic human antibody libraries enriched with convex paratopes; (2) Efficiently identify inhibitory antibodies by developing a function-based high-throughput screening method; (3) Systematically understand sequence-inhibition landscapes by deep sequencing and data mining.