Influenza is a serious public health concern, and new therapeutics that protect against this virus are urgently needed. Scientists at the IPD have used computational methods to design small proteins to serve as anti-flu therapeutics and diagnostics. The designed proteins inhibit the function of the hemagglutinin flu coat protein and prevent viral infectivity, representing a novel class of protein therapeutics for infectious diseases.
As reported in Nature Biotechnology, David Baker and scientists at the IPD published exciting new methods to improve the potency and breadth of computer-designed protein inhibitors of influenza.
The ability to engineer structures of protein complexes and to design interactions of high affinity and specificity would have countless applications in biology, medicine and public health. With the advent of next-generation sequencing, this long-standing goal may now be within reach. Exciting new methods that combine sequencing with techniques for protein display and selection allow the functional properties of hundred of thousands of mutants to be measured simultaneously. Also called ‘deep mutational scanning’, this approach is exploited in a milestone study in this issue by Baker and colleagues to optimize the binding properties of two computationally designed protein inhibitors of H1N1 influenza hemagglutinin.
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