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The functions of RNA-dependent RNA polymerases (RdRps) in RNA viruses are
demonstrably modulated by native substrates of dynamic and interconvertible
conformational ensembles. Many of these are populated by essential flexible or
intrinsically disordered regions (IDRs) that lack a stable three-dimensional (3D)
structure and that make up nearly 16% of the conserved RdRp domains across
Riboviria lineages. Typical structural models of RdRps are conversely generally
agnostic of multiple conformations and their fluctuations, whether derived from
protein structure predictors or from experimentally resolved structures from
crystal states or dynamic conformer sets. In this review, we highlight how
biophysics-inspired prediction tools combined with advanced deep learning
algorithms, such as AlphaFold2 (AF2), can help efficiently infer the
conformational heterogeneity and dynamics of RdRps. We discuss the use of
AF2 for protein structure prediction, together with its limitations and impacts on
RNA virus protein characterization, and specifically address its low-confidence
prediction scores, which largely capture IDRs. Key examples illustrate how
biophysical-encoded preferences of generic sequence–ensemble relationships
can help estimate the global RdRp structural diversity and RNA virus discovery.
The quantitative perception we present also highlights the challenging
magnitude of the emergent sequence-to-conformations relationships of
proteins and illustrates more robust and accurate annotations of novel or
divergent RdRps. Finally, the coarse-grained IDR-based structural depiction of
RdRp conformations offers concrete perspectives on an integrative framework to directly generate innovative avenues to better understand viral replication in the early disease stages and the protein–protein affinities through the folding
dynamics of these viral proteins. Overall, tapping into the current knowledge of
RdRp conformational heterogeneity will serve further RNA virus discovery as
similarities in the global RdRp landscape emerge with more clarity.
demonstrably modulated by native substrates of dynamic and interconvertible
conformational ensembles. Many of these are populated by essential flexible or
intrinsically disordered regions (IDRs) that lack a stable three-dimensional (3D)
structure and that make up nearly 16% of the conserved RdRp domains across
Riboviria lineages. Typical structural models of RdRps are conversely generally
agnostic of multiple conformations and their fluctuations, whether derived from
protein structure predictors or from experimentally resolved structures from
crystal states or dynamic conformer sets. In this review, we highlight how
biophysics-inspired prediction tools combined with advanced deep learning
algorithms, such as AlphaFold2 (AF2), can help efficiently infer the
conformational heterogeneity and dynamics of RdRps. We discuss the use of
AF2 for protein structure prediction, together with its limitations and impacts on
RNA virus protein characterization, and specifically address its low-confidence
prediction scores, which largely capture IDRs. Key examples illustrate how
biophysical-encoded preferences of generic sequence–ensemble relationships
can help estimate the global RdRp structural diversity and RNA virus discovery.
The quantitative perception we present also highlights the challenging
magnitude of the emergent sequence-to-conformations relationships of
proteins and illustrates more robust and accurate annotations of novel or
divergent RdRps. Finally, the coarse-grained IDR-based structural depiction of
RdRp conformations offers concrete perspectives on an integrative framework to directly generate innovative avenues to better understand viral replication in the early disease stages and the protein–protein affinities through the folding
dynamics of these viral proteins. Overall, tapping into the current knowledge of
RdRp conformational heterogeneity will serve further RNA virus discovery as
similarities in the global RdRp landscape emerge with more clarity.
| Oorspronkelijke taal | Engels |
|---|---|
| Tijdschrift | Frontiers in Virology |
| Volume | 5 |
| Pagina's (van-tot) | 1-23 |
| Aantal pagina’s | 23 |
| ISSN | 2673-818X |
| DOI's | |
| Publicatiestatus | Gepubliceerd - 22-aug-2025 |
Trefwoorden
- AlphaFold2 (AF2)
- RNA virus discovery
- RNA-dependent RNA polymerase
- conformational ensembles
- folding dynamics
- intrinsic disorder (IDP/IDR)
- modulome and artificial intelligence
- structural biology
Vingerafdruk
Bekijk de onderzoeksthema's van 'Viral replication modulated by hallmark conformational ensembles: how AlphaFoldpredicted features of RdRp folding dynamics combined with intrinsic disorder-mediated function enable RNA virus discovery'. Samen vormen ze een unieke vingerafdruk.Projecten
- 1 Afgerond
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GENOPREDICT: Genoom gebaseerde risicoinschatting voor virale pathogenen in een "OneHealth" context
De Jonghe, K. (Projectverantwoordelijke) & Tahzima, R. (Onderzoeker)
15/04/22 → 14/04/25
Project: Onderzoek
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