Learning from prepandemic data to forecast viral escape.

Effective pandemic preparedness relies on anticipating viral mutations that are able to evade host immune responses to facilitate vaccine and therapeutic design. However, current strategies for viral evolution prediction are not available early in a pandemic-experimental approaches require host polyclonal antibodies to test against1-16, and existing computational methods draw heavily from current strain prevalence to make reliable predictions of variants of concern17-19. To address this, we developed EVEscape, a generalizable modular framework that combines fitness predictions from a deep learning model of historical sequences with biophysical and structural information. EVEscape quantifies the viral escape potential of mutations at scale and has the advantage of being applicable before surveillance sequencing, experimental scans or three-dimensional structures of antibody complexes are available. We demonstrate that EVEscape, trained on sequences available before 2020, is as accurate as high-throughput experimental scans at anticipating pandemic variation for SARS-CoV-2 and is generalizable to other viruses including influenza, HIV and understudied viruses with pandemic potential such as Lassa and Nipah. We provide continually revised escape scores for all current strains of SARS-CoV-2 and predict probable further mutations to forecast emerging strains as a tool for continuing vaccine development ( evescape.org ).

Simultaneous enhancement of multiple functional properties using evolution-informed protein design.

Designing optimized proteins is important for a range of practical applications. Protein design is a rapidly developing field that would benefit from approaches that enable many changes in the amino acid primary sequence, rather than a small number of mutations, while maintaining structure and enhancing function. Homologous protein sequences contain extensive information about various protein properties and activities that have emerged over billions of years of evolution. Evolutionary models of sequence co-variation, derived from a set of homologous sequences, have proven effective in a range of applications including structure determination and mutation effect prediction. In this work we apply one of these models (EVcouplings) to computationally design highly divergent variants of the model protein TEM-1 ß-lactamase, and characterize these designs experimentally using multiple biochemical and biophysical assays. Nearly all designed variants were functional, including one with 84 mutations from the nearest natural homolog. Surprisingly, all functional designs had large increases in thermostability and most had a broadening of available substrates. These property enhancements occurred while maintaining a nearly identical structure to the wild type enzyme. Collectively, this work demonstrates that evolutionary models of sequence co-variation (1) are able to capture complex epistatic interactions that successfully guide large sequence departures from natural contexts, and (2) can be applied to generate functional diversity useful for many applications in protein design.

Natural and Designed Proteins Inspired by Extremotolerant Organisms Can Form Condensates and Attenuate Apoptosis in Human Cells.

Many organisms can survive extreme conditions and successfully recover to normal life. This extremotolerant behavior has been attributed in part to repetitive, amphipathic, and intrinsically disordered proteins that are upregulated in the protected state. Here, we assemble a library of approximately 300 naturally occurring and designed extremotolerance-associated proteins to assess their ability to protect human cells from chemically induced apoptosis. We show that several proteins from tardigrades, nematodes, and the Chinese giant salamander are apoptosis-protective. Notably, we identify a region of the human ApoE protein with similarity to extremotolerance-associated proteins that also protects against apoptosis. This region mirrors the phase separation behavior seen with such proteins, like the tardigrade protein CAHS2. Moreover, we identify a synthetic protein, DHR81, that shares this combination of elevated phase separation propensity and apoptosis protection. Finally, we demonstrate that driving protective proteins into the condensate state increases apoptosis protection, and highlights the ability of DHR81 condensates to sequester caspase-7. Taken together, this work draws a link between extremotolerance-associated proteins, condensate formation, and designing human cellular protection.

Frustration and Direct-Coupling Analyses to Predict Formation and Function of Adeno-Associated Virus.

Adeno-associated virus (AAV) is a promising gene therapy vector because of its efficient gene delivery and relatively mild immunogenicity. To improve delivery target specificity, researchers use combinatorial and rational library design strategies to generate novel AAV capsid variants. These approaches frequently propose high proportions of nonforming or noninfective capsid protein sequences that reduce the effective depth of synthesized vector DNA libraries, thereby raising the discovery cost of novel vectors. We evaluated two computational techniques for their ability to estimate the impact of residue mutations on AAV capsid protein-protein interactions and thus predict changes in vector fitness, reasoning that these approaches might inform the design of functionally enriched AAV libraries and accelerate therapeutic candidate identification. The Frustratometer computes an energy function derived from the energy landscape theory of protein folding. Direct-coupling analysis (DCA) is a statistical framework that captures residue coevolution within proteins. We applied the Frustratometer to select candidate protein residues predicted to favor assembled or disassembled capsid states, then predicted mutation effects at these sites using the Frustratometer and DCA. Capsid mutants were experimentally assessed for changes in virus formation, stability, and transduction ability. The Frustratometer-based metric showed a counterintuitive correlation with viral stability, whereas a DCA-derived metric was highly correlated with virus transduction ability in the small population of residues studied. Our results suggest that coevolutionary models may be able to elucidate complex capsid residue-residue interaction networks essential for viral function, but further study is needed to understand the relationship between protein energy simulations and viral capsid metastability.

Site-Specific Post-translational Surface Modification of Adeno-Associated Virus Vectors Using Leucine Zippers.

Adeno-associated virus (AAV) is widely favored as a gene therapy vector, tested in over 200 clinical trials internationally. To improve targeted delivery a variety of genetic capsid modifications, such as insertion of targeting proteins/peptides into the capsid shell, have been explored with some success but larger insertions often have unpredictable deleterious impacts on capsid formation and gene delivery. Here, we demonstrate a modular platform for the integration of exogenous peptides and proteins onto the AAV capsid post-translationally while preserving vector functionality. We decorated the AAV capsid with leucine-zipper coiled-coil binding motifs that exhibit specific noncovalent heterodimerization. AAV capsids successfully display hexahistidine tagged-peptides using this approach, as demonstrated through nickel column affinity. This protein display platform may facilitate the incorporation of biological moieties on the AAV surface, expanding possibilities for vector enhancement and engineering.

Reprogramming the Activatable Peptide Display Function of Adeno-Associated Virus Nanoparticles.

We harnessed an intrinsic activatable peptide display behavior shared by several parvoviruses, including the adeno-associated virus (AAV), in order to design protein-based nanodevices that can carry out an exogenous functional output in response to stimulus detection. Specifically, we generated truncated viral capsid subunits that, when combined with native capsid components into mosaic capsids, can perform robust activatable peptide display. By modulating the ratio of subunits in the mosaic capsid, properties of the activatable peptide display function can be optimized. Interestingly, the truncated subunits can form homomeric capsids not observed in nature, but at the price of losing the ability to carry out activatable peptide display. Collectively, our results demonstrate the importance of capsid mosaicism when activatable peptide display is desired and help explain why the wild-type AAV capsid exists as a mosaic of different subunits. This proof-of-concept study illustrates a strategy for reprogramming a particular conformational output behavior of AAV in pursuit of the long-term vision of creating stimulus-responsive nanodevices.

Preparation and catalytic evaluation of ruthenium-nickel dendrimer encapsulated nanoparticles via intradendrimer redox displacement of nickel nanoparticles.

Ru and Ru(x)Ni(30) dendrimer encapsulated nanoparticles (DENs) were synthesized using a redox-displacement method. DEN catalytic activity for the reduction of p-nitrophenol was evaluated and found to be dependent on the ratio of metals present.