Molecular dynamics reveal a cryptic pocket in VP35 impacting nucleoprotein binding, suggesting potential therapeutic targets via deep learning.
Ebola is a challenging and lethal threat to public health. The C terminal interferon inhibitory domain of Ebola viral protein 35 (VP35 IID) mediates several molecular interactions crucial to the virulence of Ebola. Among these, its interaction with the viral nucleoprotein (NP) is known to be critical to the formation of the viral nucleocapsid and the viral replication complex. Mutations to VP35 IID residues mediating these interactions have shown that weakening the affinity of VP35 for its binding partners, including NP, can attenuate replication of the Ebola virus. Consequently, this protein has been the subject of attempts at drug targeting to combat viral infection. Such efforts have been hindered by the apparent lack of obvious pockets for small molecules to bind anywhere on the protein’s surface based on crystal structures. Here, a combination of simulations and experiments illustrates a new cryptic pocket in VP35 IID and its control over NP binding. Molecular dynamics (MD) simulations using adaptive sampling reveal a new cryptic pocket in VP35 IID near the N terminus of the protein. Previous thiol labeling experiments had demonstrated the ability of a cysteine buried near this pocket to be labeled by DTNB, corroborating the existence of a cryptic pocket in this region as seen from MD. Fluorescence polarization assays reveal that labeling this cysteine, and thereby opening the pocket, disrupts binding of a peptide from NP which interacts with VP35 IID. Thus, the newly discovered cryptic pocket controls an essential viral protein-protein interaction, highlighting the therapeutic value of targeting this cryptic pocket. Initial attempts using deep learning tools to design peptides that bind to this pocket and inhibit the VP35 IID-NP interaction show some initial promise, and optimization is underway.
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Kelly et al. (2026) studied this question.
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