Thermostabilization represents a critical and often obligatory step toward enhancing the robustness of enzymes for organic synthesis and other applications. While directed evolution methods have provided valuable tools for this purpose, these protocols are laborious and time-consuming and typically require the accumulation of several mutations, potentially at the expense of catalytic function. Here, we report a minimally invasive strategy for enzyme stabilization that relies on the installation of genetically encoded, nonreducible covalent staples in a target protein scaffold using computational design. This methodology enables the rapid development of myoglobin-based cyclopropanation biocatalysts featuring dramatically enhanced thermostability (Δ = +18.0 °C and Δ = +16.0 °C) as well as increased stability against chemical denaturation [Δ (GndHCl) = 0.53 M], without altering their catalytic efficiency and stereoselectivity properties. In addition, the stabilized variants offer superior performance and selectivity compared with the parent enzyme in the presence of a high concentration of organic cosolvents, enabling the more efficient cyclopropanation of a water-insoluble substrate. This work introduces and validates an approach for protein stabilization which should be applicable to a variety of other proteins and enzymes.

In pseudocyclic proteins such as TIM barrels, β barrels, and some helical transmembrane channels, a single subunit is repeated in a cyclic pattern, giving rise to a central cavity which can serve as a pocket for ligand binding or enzymatic activity. Inspired by these proteins, we devised a deep learning-based approach to broadly exploring the space of closed repeat proteins starting from only a specification of the repeat number and length. Biophysical data for 38 structurally diverse pseudocyclic designs produced in E. coli are consistent with the design models, and two crystal structures we were able to obtain are very close to the designed structures. Docking studies suggest the diversity of folds and central pockets provide effective starting points for designing small molecule binders or enzymes.

17 18Biophysical interactions between proteins and peptides are key determinants of genotype-19 fitness landscapes, but an understanding of how molecular structure and residue-level 20 energetics at protein-peptide interfaces shape functional landscapes remains elusive. 21Combining information from yeast-based library screening, next-generation sequencing 22 and structure-based modeling, we report comprehensive sequence-energetics-function 23 mapping of the specificity landscape of the Hepatitis C Virus (HCV) NS3/4A protease, 24 whose function -site-specific cleavages of the viral polyprotein -is a key determinant of 25 viral fitness. We elucidate the cleavability of 3.2 million substrate variants by the HCV 26 protease and find extensive clustering of cleavable and uncleavable motifs in sequence 27 . CC-BY 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/172197 doi: bioRxiv preprint first posted online Aug. 3, 2017; 2 space indicating mutational robustness, and thereby providing a plausible molecular 1 mechanism to buffer the effects of low replicative fidelity of this RNA virus. Specificity 2 landscapes of known drug-resistant mutations in the protease are similarly clustered, 3 indicating mutational robustness in both the enzyme and its substrates. Our results 4 highlight the key and constraining role of molecular-level energetics, acting as a 5 "biophysical capacitor", in shaping plateau-like fitness landscapes predicted by viral 6 quasispecies theory. 7 8 Keywords: 9HCV NS3 protease, substrate specificity, computational modeling, protease-peptide 10 interactions, next-generation sequencing, mutational robustness, negative selection 11 12 Introduction: 13RNA viruses, e.g., influenza, Hepatitis C virus (HCV) and Human Immunodeficiency 14 virus (HIV), are under a heavy mutational load due to the extremely high error-rates of 15 their RNA polymerases (Domingo and Holland, 1997; Holland et al., 1982; Lauring et al., 16 2013). As a result of this low replication fidelity, these viruses exist as a population of 17 variants called quasispecies (Andino and Domingo, 2015; Eigen, 1993), even within a 18 single host individual (Cristina et al., 2007). While this genetic diversity and a large 19 population size is believed to increase viral adaptive potential against antiviral 20 therapies( Elde et al., 2012; Goldberg et al., 2012; Wilke et al., 2001), low replication 21 fidelity may also lead to too many mutations, causing an "error catastrophe" and 22 extinction (Eigen, 2002; Lauring and Andino, 2010). The underlying biomolecular 23 . CC-BY 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/172197 doi: bioRxiv preprint first posted online Aug. 3, 2017; 3 structures and interactions in the virus must, therefore, be robust to genetic variability 1 such that ...