Cited by 165RNA and protein synthesis mechanismsProtein Structure and DynamicsGenomics and Phylogenetic Studies

3D RNA and Functional Interactions from Evolutionary Couplings

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Weinreb, Caleb, Riesselman, Adam J., Ingraham, John B., Gross, Torsten, Sander, Chris, Marks, Debora S.·2016·Cell

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Abstract

Non-coding RNAs are ubiquitous, but the discovery of new RNA gene sequences far outpaces the research on the structure and functional interactions of these RNA gene sequences. We mine the evolutionary sequence record to derive precise information about the function and structure of RNAs and RNA-protein complexes. As in protein structure prediction, we use maximum entropy global probability models of sequence co-variation to infer evolutionarily constrained nucleotide-nucleotide interactions within RNA molecules and nucleotide-amino acid interactions in RNA-protein complexes. The predicted contacts allow all-atom blinded 3D structure prediction at good accuracy for several known RNA structures and RNA-protein complexes. For unknown structures, we predict contacts in 160 non-coding RNA families. Beyond 3D structure prediction, evolutionary couplings help identify important functional interactions-e.g., at switch points in riboswitches and at a complex nucleation site in HIV. Aided by increasing sequence accumulation, evolutionary coupling analysis can accelerate the discovery of functional interactions and 3D structures involving RNA.

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Crossref · 10.1016/j.cell.2016.03.030

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  • The deeper layers of current transformer-based PLMs focus relatively more on learning protein contacts, whereas secondary structure information is spread more evenly across both shallow and deep layers.

    “An important observation is that the deeper layers of current transformer-based PLMs focus relatively more on learning protein contacts, whereas the secondary structure information is spread more evenly across both shallow and deep layers (15).”

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Authors
Weinreb, C., Riesselman, A. J., Ingraham, J. B., Gross, T., Sander, C., & Marks, D. S.
Affiliations
Harvard University (US)
Corresponding author
Marks, Debora S.
Venue
Cell
Publisher
Elsevier BV
Published
2016-05
Volume
165
Issue
4
Pages
963-975
ISSN
0092-8674 (ISSN-L)
OpenAlex
W2342307854
Cited by
159
References
116
Citations by year
2026: 4 · 2025: 10 · 2024: 14 · 2023: 4 · 2022: 21 · 2021: 13 · 2020: 24 · 2019: 18 · 2018: 27 · 2017: 20 · 2016: 4
FWCI
11.96
Type
journal article
Language
en
Open access
Locations
  • Cell (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
Funders
  • DOE (DE-FG02-97ER25308)
  • NSF Graduate Research Fellowship
  • NIH (R01 GM106303)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Keywords
evolutionary coupling, RNA structure prediction, protein-RNA complex, non-coding RNA, maximum entropy model, riboswitches, HIV, functional interactions, RNA tertiary structure
MeSH terms
Models, Molecular, Nucleic Acid Conformation, Ribosomes, RNA-Binding Proteins, Evolution, Molecular, Entropy, RNA, Untranslated, RNA Folding

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