SBIR/STTR Award attributes
The goal of this proposal is it to use computational protein design to develop a set of stable, non-immunogenic enzymes for G-agent and V-agent neurotoxin deactivation based on an engineered human PON1 scaffold suitable for mass production. Chemical warfare nerve agents (CWNAs) have existed for over a century and remain a serious threat to the safety of mankind. Therapeutic enzyme treatments offer a promising defense against CWNAs, but must satisfy several criteria beyond high catalytic activity if they are to prove practical. First, these enzymes must not provoke an immune response upon administration. Second, they must be expressed at high titer for mass production. Third, enzyme activities targeting diverse CWNAs would ideally be engineered into a single scaffold to expedite regulatory approval. The inability of state-of-the-art enzymes to satisfy simultaneously these criteria prevents the deployment of enzymatic therapeutics for CWNAs. Current high activity enzymes, often derived from bacterial sources, have immunogenicity concerns due to antibodies being formed against the enzymes after administration. The Paraoxonase 1 enzyme from humans (HsPON1) is one of the most promising proteins for CWNA deactivation, but the native protein expresses very poorly in E. coli, which is the preferred method for mass production. Engineered versions of HsPON1 obtained from directed evolution exhibit high activity against G-agents and good recombinant expression, but the number of necessary mutations (particularly on the protein surface) introduce significant immunogenicity risk. Attempts to improve the solubility of HsPON1 by rational (rather than computational) design have met with only limited success. We propose to use computational design methods to address the multiple and disparate requirements therapeutic enzymes must satisfy in order to provide a practical solution to the danger posed by CWNAs. Our preliminary results engineering HsPON1 suggest that we can accomplish this goal; our computationally designed enzymes are competitive with the most active HsPON1 candidates for CWNA bio-scavenging. In addition, our enzymes exhibit similar titers from recombinant expression and purification. Furthermore, compared to previous state-of-the-art HsPON1 variants, our enzymes differ from wild-type HsPON1 by many fewer mutations and are predicted to have reduced immunogenicity based on analysis of potential T-cell epitopes. We plan to further exploit computational design of the HsPON1 scaffold to target a full complement of CWNA targets, obtaining a cocktail of therapeutic enzymes that are non-immunogenic, stable, soluble, and amenable to mass production.
