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Rotation-Activated and Cooperative Zipping Characterize Class I Viral Fusion Protein Dynamics.

ABSTRACT: Class I viral fusion proteins are ?-helical proteins that facilitate membrane fusion between viral and host membranes through large conformational transitions. Although prefusion and postfusion crystal structures have been solved for many of these proteins, details about how they transition between these states have remained elusive. This work presents the first, to our knowledge, computational survey of transitions between pre- and postfusion configurations for several class I viral fusion proteins using structure-based models to analyze their dynamics. As suggested by their structural similarities, all proteins share common mechanistic features during their transitions that can be characterized by a diffusive rotational search followed by cooperative N- and C-terminal zipping. Instead of predicting a stable spring-loaded intermediate, our model suggests that helical bundle formation is mediated by N- and C-terminal interactions late in the transition. Shared transition features suggest a global mechanism in which fusion is activated by slow protein-core rotation.

SUBMITTER: Eddy NR

PROVIDER: S-EPMC5937144 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Rotation-Activated and Cooperative Zipping Characterize Class I Viral Fusion Protein Dynamics.

Eddy Nathanial R NR Onuchic José N JN

Biophysical journal 20180401 8

Class I viral fusion proteins are α-helical proteins that facilitate membrane fusion between viral and host membranes through large conformational transitions. Although prefusion and postfusion crystal structures have been solved for many of these proteins, details about how they transition between these states have remained elusive. This work presents the first, to our knowledge, computational survey of transitions between pre- and postfusion configurations for several class I viral fusion prot ...[more]

PMID: 29694865

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Project description: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.

Dataset Information

Rotation-Activated and Cooperative Zipping Characterize Class I Viral Fusion Protein Dynamics.

Publications

Rotation-Activated and Cooperative Zipping Characterize Class I Viral Fusion Protein Dynamics.

Similar Datasets

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