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Free, publicly-accessible full text available June 24, 2023
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Abstract Potts models and variational autoencoders (VAEs) have recently gained popularity as generative protein sequence models (GPSMs) to explore fitness landscapes and predict mutation effects. Despite encouraging results, current model evaluation metrics leave unclear whether GPSMs faithfully reproduce the complex multi-residue mutational patterns observed in natural sequences due to epistasis. Here, we develop a set of sequence statistics to assess the “generative capacity” of three current GPSMs: the pairwise Potts Hamiltonian, the VAE, and the site-independent model. We show that the Potts model’s generative capacity is largest, as the higher-order mutational statistics generated by the model agree with those observedmore »
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The SARS-CoV-2 pandemic has necessitated the rapid development of prophylactic vaccines. Two mRNA vaccines have been approved for emergency use by the FDA and have demonstrated extraordinary effectiveness. The success of these mRNA vaccines establishes the speed of development and therapeutic potential of mRNA. These authorized vaccines encode full-length versions of the SARS-CoV-2 spike protein. They are formulated with lipid nanoparticle (LNP) delivery vehicles that have inherent immunostimulatory properties. Different vaccination strategies and alternative mRNA delivery vehicles would be desirable to ensure flexibility of future generations of SARS-CoV-2 vaccines and the development of mRNA vaccines in general. Here, we reportmore »