Global pairwise RNA interaction landscapes reveal core features of protein recognition

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.

Epistatic contributions promote the unification of incompatible models of neutral molecular evolution

“…In recent years, new methods have been developed to analyze MSAs of protein families using a joint probability model that takes into account pairwise and single-site interactions. Particularly, direct coupling analysis (DCA) (20,21) has been shown to be a powerful tool for predicting sites that are coupled during evolution and have been utilized as guides in inferring protein structures (22)(23)(24)(25)(26), understanding the thermodynamics of folding (27,28), predicting protein-protein interactions (29)(30)(31)(32)(33)(34)(35)(36)(37), conformational dynamics (38), and uncovering mutational landscapes (39)(40)(41)(42), as well as possible biomedical applications (43)(44)(45)(46)(47)(48)(49)(50).…”

Affinity Profiles Categorize RNA-Binding Proteins into Distinctive Groups

“…In some cases, RBPs just connect RNAs to proteins to form cellular structures [24,42,43]. Versatility of RBP functions endows wide ranges of affinity of their binding capacity [44][45][46]. RBPs are characterized by proficiency of RNA perception and possess divergent capability in living cells.…”

Shedding light on the dark matter of the biomolecular structural universe: Progress in RNA 3D structure prediction

“…A further confirmation in [55] highlights that prediction RMSDs for the same structures as analyzed in [24,42] are lowered by about 30% when using the tertiary contacts predicted via mfDCA in the 3dRNA method [21] compared to not using such tertiary contact constraints. [42] and [57] also demonstrated how Figure 4: (a) DCA contact-guided RNA structure prediction improvement with respect to the state of the art (Rosetta-based) method for the six riboswitches from [24]. (b) Overlay of the DCA-contact guided predicted (blue) and the experimental structure (green) for the thiamine pyrophosphate-specific (TPP) riboswitch (PDB code 2gdi).…”