Influenza is a major public health threat, and current vaccines and antivirals are not always effective. We have developed a high-affinity computationally designed anti-influenza protein (HB36.6) that when administered intranasally affords strong prophylactic and therapeutic protection in mice lethally challenged with Group 1 influenza viruses, a result that demonstrated for the first time, transformation of a theoretical target designed by our computational method into a new antiviral with strong biopotency in vivo. HB36.6 is highly effective against the human Group 1 influenza strains (i.e. H1, H5) but not against Group 2 strains (i.e. H3, H7). In this application, we propose to build on our promising findings with the Group 1 binder and broaden efficacy for protection against both Group 1 and 2 strains by computationally designing and testing a second antiviral protein that broadly binds the Group 2 strains and when combined with HB36.6, will provide pan-specific protection against a wide range of all influenza subtypes including avian and drug resistant strains. In the R21 phase, we will: Identify computationally designed peptides that optimally bind the HA stem region of Group 2 influenza subtypes (R21, Aim 1); identify a single design that affords prophylactic and therapeutic protection in mice challenged with a Group 2 virus (Aim 2, R21); and determine if combining the optimized Group 2 binder with HB36.6 (Group 1) affords broad protection against seasonal and avian influenza strains in mice (Aim 3, R21). If we identify an effective group 2 binder in the R21 phase then in the R33 phase, we will determine if the combined binders afford superior prophylactic (Aim 1, R33) and therapeutic (R33, Aim 2) protective efficacy against representative Group 1 and 2 seasonal and drug resistant influenza strains in the preclinical ferret model and determine the relationship between protein distribution and persistence in the lung and localized effects on suppressing viral replication and inflammation in the mouse and ferret lung (R33, Aim 3).
Influenza is a leading cause of morbidity and death especially among the elderly and current antivirals for influenza incur high resistance rates, side effects and have low efficacy. We propose to develop a new class of computationally designed proteins that will interfere with influenza infection and provide prophylactic and therapeutic protection against a wide range of seasonal, pandemic and drug resistant strain of influenza.
| Strauch, Eva-Maria; Bernard, Steffen M; La, David et al. (2017) Computational design of trimeric influenza-neutralizing proteins targeting the hemagglutinin receptor binding site. Nat Biotechnol 35:667-671 |
| Chevalier, Aaron; Silva, Daniel-Adriano; Rocklin, Gabriel J et al. (2017) Massively parallel de novo protein design for targeted therapeutics. Nature 550:74-79 |
