Systematic computer-aided disulfide design as a general strategy to stabilize prefusion class I fusion proteins.

Numerous enveloped viruses, such as coronaviruses, influenza, and respiratory syncytial virus (RSV), utilize class I fusion proteins for cell entry. During this process, the proteins transition from a prefusion to a postfusion state, undergoing substantial and irreversible conformational changes. The prefusion conformation has repeatedly shown significant potential in vaccine development. However, the instability of this state poses challenges for its practical application in vaccines. While non-native disulfides have been effective in maintaining the prefusion structure, identifying stabilizing disulfide bonds remains an intricated task. Here, we present a general computational approach to systematically identify prefusion-stabilizing disulfides. Our method assesses the geometric constraints of disulfide bonds and introduces a ranking system to estimate their potential in stabilizing the prefusion conformation. We found, for the RSV F protein, that disulfides restricting the initial stages of the conformational switch can offer higher stability to the prefusion state than those preventing unfolding at a later stage. The implementation of our algorithm on the RSV F protein led to the discovery of prefusion-stabilizing disulfides, providing evidence that supports our hypothesis. Furthermore, the evaluation of our top design as a vaccine candidate in a cotton rat model demonstrated robust protection against RSV infection, highlighting the potential of our approach for vaccine development.

A general computational design strategy for stabilizing viral class I fusion proteins.

Many pathogenic viruses rely on class I fusion proteins to fuse their viral membrane with the host cell membrane. To drive the fusion process, class I fusion proteins undergo an irreversible conformational change from a metastable prefusion state to an energetically more stable postfusion state. Mounting evidence underscores that antibodies targeting the prefusion conformation are the most potent, making it a compelling vaccine candidate. Here, we establish a computational design protocol that stabilizes the prefusion state while destabilizing the postfusion conformation. With this protocol, we stabilize the fusion proteins of the RSV, hMPV, and SARS-CoV-2 viruses, testing fewer than a handful of designs. The solved structures of these designed proteins from all three viruses evidence the atomic accuracy of our approach. Furthermore, the humoral response of the redesigned RSV F protein compares to that of the recently approved vaccine in a mouse model. While the parallel design of two conformations allows the identification of energetically sub-optimal positions for one conformation, our protocol also reveals diverse molecular strategies for stabilization. Given the clinical significance of viruses using class I fusion proteins, our algorithm can substantially contribute to vaccine development by reducing the time and resources needed to optimize these immunogens.

A general computational design strategy for stabilizing viral class I fusion proteins.

Many pathogenic viruses, including influenza virus, Ebola virus, coronaviruses, and Pneumoviruses, rely on class I fusion proteins to fuse viral and cellular membranes. To drive the fusion process, class I fusion proteins undergo an irreversible conformational change from a metastable prefusion state to an energetically more favorable and stable postfusion state. An increasing amount of evidence exists highlighting that antibodies targeting the prefusion conformation are the most potent. However, many mutations have to be evaluated before identifying prefusion-stabilizing substitutions. We therefore established a computational design protocol that stabilizes the prefusion state while destabilizing the postfusion conformation. As a proof of concept, we applied this principle to the fusion protein of the RSV, hMPV, and SARS-CoV-2 viruses. For each protein, we tested less than a handful of designs to identify stable versions. Solved structures of designed proteins from the three different viruses evidenced the atomic accuracy of our approach. Furthermore, the immunological response of the RSV F design compared to a current clinical candidate in a mouse model. While the parallel design of two conformations allows identifying and selectively modifying energetically less optimized positions for one conformation, our protocol also reveals diverse molecular strategies for stabilization. We recaptured many approaches previously introduced manually for the stabilization of viral surface proteins, such as cavity-filling, optimization of polar interactions, as well as postfusion-disruptive strategies. Using our approach, it is possible to focus on the most impacting mutations and potentially preserve the immunogen as closely as possible to its native version. The latter is important as sequence re-design can cause perturbations to B and T cell epitopes. Given the clinical significance of viruses using class I fusion proteins, our algorithm can substantially contribute to vaccine development by reducing the time and resources needed to optimize these immunogens.

Decreased vaccine protection of egg-based influenza vaccine in the elderly and nonhemagglutinin-focused immunity.

Severe influenza illness or death is a serious concern among the elderly population despite vaccination. To investigate how the adaptive immune response after vaccination varies with the patient's age, Jung et al., in a recent issue of the JCI, extensively analyzed the serum antibody response in different age groups after immunization with the egg-based influenza vaccine Fluzone. As expected, the immune response in young adults was dominated by antibodies targeting the influenza hemagglutinin (HA) protein. On the contrary, the serological repertoire of elderly donors was characterized by cross-reactive (CR) antibodies recognizing non-HA antigens. Surprisingly, a substantial fraction of these CR antibodies targeted sulfated glycans typical of egg-produced proteins, which does not provide protection against human influenza viruses. Overall, these findings are of great value in understanding suboptimal immunity after influenza vaccination and shaping future vaccine efforts that will achieve increased protection in the elderly.

Targeting Viral Surface Proteins through Structure-Based Design.

The emergence of novel viral infections of zoonotic origin and mutations of existing human pathogenic viruses represent a serious concern for public health. It warrants the establishment of better interventions and protective therapies to combat the virus and prevent its spread. Surface glycoproteins catalyzing the fusion of viral particles and host cells have proven to be an excellent target for antivirals as well as vaccines. This review focuses on recent advances for computational structure-based design of antivirals and vaccines targeting viral fusion machinery to control seasonal and emerging respiratory viruses.

Skp1 Dimerization Conceals Its F-Box Protein Binding Site.

Skp1 is an adapter that links F-box proteins to cullin-1 in the Skp1/cullin-1/F-box (SCF) protein family of E3 ubiquitin ligases that targets specific proteins for polyubiquitination and subsequent protein degradation. Skp1 from the amoebozoan Dictyostelium forms a stable homodimer in vitro with a Kd of 2.5 µM as determined by sedimentation velocity studies yet is monomeric in crystal complexes with F-box proteins. To investigate the molecular basis for the difference, we determined the solution NMR structure of a doubly truncated Skp1 homodimer (Skp1ΔΔ). The solution structure of the Skp1ΔΔ dimer reveals a 2-fold symmetry with an interface that buries ∼750 Å2 of predominantly hydrophobic surface. The dimer interface overlaps with subsite 1 of the F-box interaction area, explaining why only the Skp1 monomer binds F-box proteins (FBPs). To confirm the model, Rosetta was used to predict amino acid substitutions that might disrupt the dimer interface, and the F97E substitution was chosen to potentially minimize interference with F-box interactions. A nearly full-length version of Skp1 with this substitution (Skp1ΔF97E) behaved as a stable monomer at concentrations of ≤500 µM and actively bound a model FBP, mammalian Fbs1, which suggests that the dimeric state is not required for Skp1 to carry out a basic biochemical function. Finally, Skp1ΔF97E is expected to serve as a monomer model for high-resolution NMR studies previously hindered by dimerization.

In silico identification of potential inhibitors against human 2'-5'- oligoadenylate synthetase (OAS) proteins.

As part of the type I IFN signaling, the 2'-5'- oligoadenylate synthetase (OAS) proteins have been involved in the progression of several non-viral diseases. Notably, OAS has been correlated with immune-modulatory functions that promote chronic inflammatory conditions, autoimmune disorders, cancer, and infectious diseases. In spite of this, OAS enzymes have been ignored as drug targets, and to date, there are no reports of compounds that can inhibit their activity. In this study, we have used homology modeling and virtual high-throughput screening to identify potential inhibitors of the human proteins OAS1, OAS2, and OAS3. Altogether, we have found 37 molecules that could exert a competitive inhibition in the ATP binding sites of OAS proteins, independently of the activation state of the enzyme. This latter characteristic, which might be crucial for a versatile inhibitor, was observed in compounds interacting with the residues Asp75, Asp77, Gln229, and Tyr230 in OAS1, and their equivalents in OAS2 and OAS3. Although there was little correlation between specific chemical fragments and their interactions, intermolecular contacts with OAS catalytic triad and other critical amino acids were mainly promoted by heterocycles with π electrons and hydrogen bond acceptors. In conclusion, this study provides a potential set of OAS inhibitors as well as valuable information for their design, development, and optimization.