A cryptic pocket in Ebola VP35 allosterically controls RNA binding

Protein-protein and protein-nucleic acid interactions are often considered difficult drug targets because the surfaces involved lack obvious druggable pockets. Cryptic pockets could present opportunities for targeting these interactions, but identifying and exploiting these pockets remains challengi...

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Vydáno v:	Nature communications Ročník 13; číslo 1; s. 2269 - 10
Hlavní autoři:	Cruz, Matthew A., Frederick, Thomas E., Mallimadugula, Upasana L., Singh, Sukrit, Vithani, Neha, Zimmerman, Maxwell I., Porter, Justin R., Moeder, Katelyn E., Amarasinghe, Gaya K., Bowman, Gregory R.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London Nature Publishing Group UK 27.04.2022 Nature Publishing Group Nature Portfolio
Témata:	119/118 38/71 45/70 631/45/612/1230 631/45/612/1256 631/57/2266 82/80 82/83 96/34 Adaptive sampling Algorithms Allosteric properties Binding sites Computer applications DNA Viruses - genetics Double-stranded RNA Drug development Ebola virus Ebolavirus Ebolavirus - genetics Hemorrhagic Fever, Ebola Humanities and Social Sciences Humans Interferon Machine learning multidisciplinary Nucleic acids Proteins RNA, Double-Stranded - genetics RNA-binding protein Science Science (multidisciplinary) Therapeutic targets Viral diseases Viral Proteins - genetics Viral Regulatory and Accessory Proteins - genetics
ISSN:	2041-1723, 2041-1723
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Shrnutí:	Protein-protein and protein-nucleic acid interactions are often considered difficult drug targets because the surfaces involved lack obvious druggable pockets. Cryptic pockets could present opportunities for targeting these interactions, but identifying and exploiting these pockets remains challenging. Here, we apply a general pipeline for identifying cryptic pockets to the interferon inhibitory domain (IID) of Ebola virus viral protein 35 (VP35). VP35 plays multiple essential roles in Ebola’s replication cycle but lacks pockets that present obvious utility for drug design. Using adaptive sampling simulations and machine learning algorithms, we predict VP35 harbors a cryptic pocket that is allosterically coupled to a key dsRNA-binding interface. Thiol labeling experiments corroborate the predicted pocket and mutating the predicted allosteric network supports our model of allostery. Finally, covalent modifications that mimic drug binding allosterically disrupt dsRNA binding that is essential for immune evasion. Based on these results, we expect this pipeline will be applicable to other proteins. Many viral proteins are thought to be unlikely candidates for drug discovery as they lack obvious drug binding sites. Here, the authors use computational approaches followed by experimental validation to identify a cryptic pocket within the Ebola virus protein VP35.
Bibliografie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
ISSN:	2041-1723 2041-1723
DOI:	10.1038/s41467-022-29927-9