RESUMO
While deep learning models have seen increasing applications in protein science, few have been implemented for protein backbone generation-an important task in structure-based problems such as active site and interface design. We present a new approach to building class-specific backbones, using a variational auto-encoder to directly generate the 3D coordinates of immunoglobulins. Our model is torsion- and distance-aware, learns a high-resolution embedding of the dataset, and generates novel, high-quality structures compatible with existing design tools. We show that the Ig-VAE can be used with Rosetta to create a computational model of a SARS-CoV2-RBD binder via latent space sampling. We further demonstrate that the model's generative prior is a powerful tool for guiding computational protein design, motivating a new paradigm under which backbone design is solved as constrained optimization problem in the latent space of a generative model.
Assuntos
COVID-19 , RNA Viral , Humanos , Imunoglobulinas , Proteínas/química , SARS-CoV-2RESUMO
Staphylococcus aureus expresses several hemolytic pore-forming toxins (PFTs), which are all commonly composed of three domains: cap, rim and stem. PFTs are expressed as soluble monomers and assemble to form a transmembrane ß-barrel pore in the erythrocyte cell membrane. The stem domain undergoes dramatic conformational changes to form a pore. Staphylococcal PFTs are classified into two groups: one-component α-hemolysin (α-HL) and two-component γ-hemolysin (γ-HL). The α-HL forms a homo-heptamer, whereas γ-HL is an octamer composed of F-component (LukF) and S-component (Hlg2). Because PFTs are used as materials for nanopore-based sensors, knowledge of the functional properties of PFTs is used to develop new, engineered PFTs. However, it remains challenging to design PFTs with a ß-barrel pore because their formation as transmembrane protein assemblies requires large conformational changes. In the present study, aiming to investigate the design principles of the ß-barrel formed as a consequence of the conformational change, chimeric mutants composed of the cap/rim domains of α-HL and the stem of LukF or Hlg2 were prepared. Biochemical characterization and electron microscopy showed that one of them assembles as a heptameric one-component PFT, whereas another participates as both a heptameric one- and heptameric/octameric two-component PFT. All chimeric mutants intrinsically assemble into SDS-resistant oligomers. Based on these observations, the role of the stem domain of these PFTs is discussed. These findings provide clues for the engineering of staphylococcal PFT ß-barrels for use in further promising applications.
Assuntos
Toxinas Bacterianas , Proteínas Hemolisinas , Toxinas Bacterianas/metabolismo , Proteínas Hemolisinas/metabolismo , Hemólise , Leucocidinas/química , Leucocidinas/metabolismo , Staphylococcus aureus/genética , Staphylococcus aureus/metabolismoRESUMO
RNA hydrolysis presents problems in manufacturing, long-term storage, world-wide delivery and in vivo stability of messenger RNA (mRNA)-based vaccines and therapeutics. A largely unexplored strategy to reduce mRNA hydrolysis is to redesign RNAs to form double-stranded regions, which are protected from in-line cleavage and enzymatic degradation, while coding for the same proteins. The amount of stabilization that this strategy can deliver and the most effective algorithmic approach to achieve stabilization remain poorly understood. Here, we present simple calculations for estimating RNA stability against hydrolysis, and a model that links the average unpaired probability of an mRNA, or AUP, to its overall hydrolysis rate. To characterize the stabilization achievable through structure design, we compare AUP optimization by conventional mRNA design methods to results from more computationally sophisticated algorithms and crowdsourcing through the OpenVaccine challenge on the Eterna platform. We find that rational design on Eterna and the more sophisticated algorithms lead to constructs with low AUP, which we term 'superfolder' mRNAs. These designs exhibit a wide diversity of sequence and structure features that may be desirable for translation, biophysical size, and immunogenicity. Furthermore, their folding is robust to temperature, computer modeling method, choice of flanking untranslated regions, and changes in target protein sequence, as illustrated by rapid redesign of superfolder mRNAs for B.1.351, P.1 and B.1.1.7 variants of the prefusion-stabilized SARS-CoV-2 spike protein. Increases in in vitro mRNA half-life by at least two-fold appear immediately achievable.
Assuntos
Algoritmos , RNA de Cadeia Dupla/química , RNA Mensageiro/química , RNA Viral/química , SARS-CoV-2/genética , Glicoproteína da Espícula de Coronavírus/genética , Pareamento de Bases , Sequência de Bases , COVID-19/prevenção & controle , Humanos , Hidrólise , Estabilidade de RNA , RNA de Cadeia Dupla/genética , RNA de Cadeia Dupla/imunologia , RNA Mensageiro/genética , RNA Mensageiro/imunologia , RNA Viral/genética , RNA Viral/imunologia , SARS-CoV-2/imunologia , Glicoproteína da Espícula de Coronavírus/imunologia , TermodinâmicaRESUMO
RNA hydrolysis presents problems in manufacturing, long-term storage, world-wide delivery, and in vivo stability of messenger RNA (mRNA)-based vaccines and therapeutics. A largely unexplored strategy to reduce mRNA hydrolysis is to redesign RNAs to form double-stranded regions, which are protected from in-line cleavage and enzymatic degradation, while coding for the same proteins. The amount of stabilization that this strategy can deliver and the most effective algorithmic approach to achieve stabilization remain poorly understood. Here, we present simple calculations for estimating RNA stability against hydrolysis, and a model that links the average unpaired probability of an mRNA, or AUP, to its overall hydrolysis rate. To characterize the stabilization achievable through structure design, we compare AUP optimization by conventional mRNA design methods to results from more computationally sophisticated algorithms and crowdsourcing through the OpenVaccine challenge on the Eterna platform. These computational tests were carried out on both model mRNAs and COVID-19 mRNA vaccine candidates. We find that rational design on Eterna and the more sophisticated algorithms lead to constructs with low AUP, which we term 'superfolder' mRNAs. These designs exhibit wide diversity of sequence and structure features that may be desirable for translation, biophysical size, and immunogenicity, and their folding is robust to temperature, choice of flanking untranslated regions, and changes in target protein sequence, as illustrated by rapid redesign of superfolder mRNAs for B.1.351, P.1, and B.1.1.7 variants of the prefusion-stabilized SARS-CoV-2 spike protein. Increases in in vitro mRNA half-life by at least two-fold appear immediately achievable.
RESUMO
The functionality of most secreted proteins depends on their assembly into a defined quaternary structure. Despite this, it remains unclear how cells discriminate unassembled proteins en route to the native state from misfolded ones that need to be degraded. Here we show how chaperones can regulate and control assembly of heterodimeric proteins, using interleukin 23 (IL-23) as a model. We find that the IL-23 α-subunit remains partially unstructured until assembly with its ß-subunit occurs and identify a major site of incomplete folding. Incomplete folding is recognized by different chaperones along the secretory pathway, realizing reliable assembly control by sequential checkpoints. Structural optimization of the chaperone recognition site allows it to bypass quality control checkpoints and provides a secretion-competent IL-23α subunit, which can still form functional heterodimeric IL-23. Thus, locally-restricted incomplete folding within single-domain proteins can be used to regulate and control their assembly.