ArticleNature communications2018
Global pairwise RNA interaction landscapes reveal core features of protein recognition.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
25 citing papers in PubMed, 44 citations in OpenAlex.
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- Characterizing DNA recognition preferences of transcription factors using global couplings and high-throughput sequencing.Nucleic acids research · 2025Article
- Simultaneous enhancement of multiple functional properties using evolution-informed protein design.Nature communications · 2024Article
- Coevolutionary Information Captures Catalytic Functions and Reveals Divergent Roles of Terpene Synthase Interdomain Connections.Biochemistry · 2024Article
- In vivo functional phenotypes from a computational epistatic model of evolution.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Latent generative landscapes as maps of functional diversity in protein sequence space.Nature communications · 2023Article
- Two distinct binding modes provide the RNA-binding protein RbFox with extraordinary sequence specificity.Nature communications · 2023Article
- Computational compensatory mutation discovery approach: Predicting a PARP1 variant rescue mutation.Biophysical journal · 2022Article
- Generative and interpretable machine learning for aptamer design and analysis of in vitro sequence selection.PLoS computational biology · 2022Article
- Coupling a Live Cell Directed Evolution Assay with Coevolutionary Landscapes to Engineer an Improved Fluorescent Rhodopsin Chloride Sensor.ACS synthetic biology · 2022Article
- Modeling Sequence-Space Exploration and Emergence of Epistatic Signals in Protein Evolution.Molecular biology and evolution · 2022Article
- Terminal uridyltransferase 7 regulates TLR4-triggered inflammation by controlling Regnase-1 mRNA uridylation and degradation.Nature communications · 2021Article
- Metabolomics Analysis of Viral Therapeutics.Methods in molecular biology (Clifton, N.J.) · 2021Article
- RNA-protein coevolution study of Gemin5 uncovers the role of the PXSS motif of RBS1 domain for RNA binding.RNA biology · 2020Article
- High throughput approaches to study RNA-protein interactions in vitro.Methods (San Diego, Calif.) · 2020Review
- Molecular entrapment by RNA: an emerging tool for disrupting protein-RNA interactionsRNA biology · 2020Article
- Epistatic contributions promote the unification of incompatible models of neutral molecular evolution.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Coevolutionary Couplings Unravel PAM-Proximal Constraints of CRISPR-SpCas9.Biophysical journal · 2019Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
RNA-protein interactions permeate biology. Transcription, translation, and splicing all hinge on the recognition of structured RNA elements by RNA-binding proteins. Models of RNA-protein interactions are generally limited to short linear motifs and structures because of the vast sequence sampling required to access longer elements. Here, we develop an integrated approach that calculates global pairwise interaction scores from in vitro selection and high-throughput sequencing. We examine four RNA-binding proteins of phage, viral, and human origin. Our approach reveals regulatory motifs, discriminates between regulated and non-regulated RNAs within their native genomic context, and correctly predicts the consequence of mutational events on binding activity. We design binding elements that improve binding activity in cells and infer mutational pathways that reveal permissive versus disruptive evolutionary trajectories between regulated motifs. These coupling landscapes are broadly applicable for the discovery and characterization of protein-RNA recognition at single nucleotide resolution.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.