A structure-based model for the prediction of protein–RNA binding affinity

Nithin, Chandran; Mukherjee, Sunandan; Bahadur, Ranjit Prasad

doi:10.1261/rna.071779.119

Cited by 13 publications

(7 citation statements)

References 158 publications

(169 reference statements)

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“…2E). Overall, these results demonstrate that RbpB binds ssRNA with some degree of specificity at affinities comparable to known RNA-binding proteins (56)(57)(58).…”

Section: B Thetaiotaomicron Rbpb Is a Single-stranded Rna-binding Promentioning

confidence: 57%

A Novel Family of RNA-Binding Proteins Regulate Polysaccharide Metabolism inBacteroides thetaiotaomicron

Adams

Azam

Costliow

et al. 2021

Preprint

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Human gut microbiome composition is constantly changing, and diet is a major driver of these changes. Gut microbial species that persist in mammalian hosts for long periods of time must possess mechanisms for sensing and adapting to nutrient shifts to avoid being outcompeted. Global regulatory mechanisms mediated by RNA-binding proteins (RBPs) that govern responses to nutrient shifts have been characterized in Proteobacteria and Firmicutes but remain undiscovered in the Bacteroidetes. Here we report the identification of RBPs that are broadly distributed across the Bacteroidetes, with many genomes encoding multiple copies. Genes encoding these RBPs are highly expressed in many Bacteroides species. A purified RBP, RbpB, from Bacteroides thetaiotaomicron binds to single-stranded RNA in vitro with an affinity similar to other characterized regulatory RBPs. B. thetaiotaomicron mutants lacking RBPs show dramatic shifts in expression of polysaccharide utilization and capsular polysaccharide loci, suggesting that these RBPs may act as global regulators of polysaccharide metabolism. A B. thetaiotaomicron ΔrbpB mutant shows a growth defect on dietary sugars belonging to the raffinose family of oligosaccharides (RFOs). The ΔrbpB mutant had reduced expression of BT1871, encoding a predicted RFO-degrading melibiase, compared to the wild-type strain. Mutation of BT1871 confirmed that the enzyme it encodes is essential for growth on melibiose and promotes growth on the RFOs raffinose and stachyose. Our data reveal that RbpB is required for optimal expression of BT1871 and other polysaccharide-related genes, suggesting that we have identified an important new family of global regulatory proteins in the Bacteroidetes.

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“…2E). Overall, these results demonstrate that RbpB binds ssRNA with some degree of specificity at affinities comparable to known RNA-binding proteins (56)(57)(58).…”

Section: B Thetaiotaomicron Rbpb Is a Single-stranded Rna-binding Promentioning

confidence: 57%

A Novel Family of RNA-Binding Proteins Regulate Polysaccharide Metabolism inBacteroides thetaiotaomicron

Adams

Azam

Costliow

et al. 2021

Preprint

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“…Any would-be stable complex must meet at least one of the following requirements: (i) it must have a relatively low dissociation constant, at least in the sub-micromolar range (thermodynamic stability) and/or (ii) its off-rate must be fairly slow, typically <10 –4 s –1 (kinetic stability). We refer the reader to the following publications for examples of these parameters among some well-studied RNPs ( Yang et al, 2013 ; Nithin et al, 2019 ; Licatalosi et al, 2020 ). It is also instrumental to consider two operational definitions of stability: (i) the “ in vivo stability,” when the complex is long-lived within the dynamic cell milieu teeming with thousands of other molecules (which may in various ways influence its integrity), and (ii) the “ in vitro stability,” when the complex only needs to be intrinsically robust in (effective) isolation from other cellular components ( Helder et al, 2016 ; Gehring et al, 2017 ).…”

Section: What Is a Stable Rnp?mentioning

confidence: 99%

The World of Stable Ribonucleoproteins and Its Mapping With Grad-Seq and Related Approaches

Gerovac

Vogel

Smirnov

2021

Front. Mol. Biosci.

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Macromolecular complexes of proteins and RNAs are essential building blocks of cells. These stable supramolecular particles can be viewed as minimal biochemical units whose structural organization, i.e., the way the RNA and the protein interact with each other, is directly linked to their biological function. Whether those are dynamic regulatory ribonucleoproteins (RNPs) or integrated molecular machines involved in gene expression, the comprehensive knowledge of these units is critical to our understanding of key molecular mechanisms and cell physiology phenomena. Such is the goal of diverse complexomic approaches and in particular of the recently developed gradient profiling by sequencing (Grad-seq). By separating cellular protein and RNA complexes on a density gradient and quantifying their distributions genome-wide by mass spectrometry and deep sequencing, Grad-seq charts global landscapes of native macromolecular assemblies. In this review, we propose a function-based ontology of stable RNPs and discuss how Grad-seq and related approaches transformed our perspective of bacterial and eukaryotic ribonucleoproteins by guiding the discovery of new RNA-binding proteins and unusual classes of noncoding RNAs. We highlight some methodological aspects and developments that permit to further boost the power of this technique and to look for exciting new biology in understudied and challenging biological models.

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“…Dias et al 18 developed a generalized linear modeling (GLM)‐score to predict protein–RNA binding affinity, which uses structural features including hydrogen bonds, hydrophobic contacts, van der Waals, and the deformation effect. Nithin et al 19 predicted the binding affinity by using the molecules conformation change and other structural features with bound and unbound structure. In most instances, it is difficult to find the unbound structure of the complex.…”

Section: Introductionmentioning

confidence: 99%

An updated dataset and a structure‐based prediction model for protein–RNA binding affinity

Tong

Xie

et al. 2023

Proteins

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Understanding the process of protein–RNA interaction is essential for structural biology. The thermodynamic process is an important part to uncover the protein–RNA interaction mechanism. The regulatory networks between protein and RNA in organisms are dominated by the binding or dissociation in the cells. Therefore, determining the binding affinity for protein–RNA complexes can help us to understand the regulation mechanism of protein–RNA interaction. Since it is time‐consuming and labor‐intensive to determine the binding affinity for protein–RNA complexes by experimental methods, it is necessary and urgent to develop computational methods to predict that. To develop a binding affinity prediction model, first we update the dataset of protein–RNA binding affinity benchmark (PRBAB), which includes 145 complexes now. Second, we extract the structural features based on complex structure, and then we analyze and select the representative structural features to train the regression model. Third, we random select the subset from the PRBAB2.0 to fit the protein–RNA binding affinity determined by experiment. In the end, we tested our model on the nonredundant PDBbind dataset, and the results showed that Pearson correlation coefficient r = .57 and RMSE = 2.51 kcal/mol. The Pearson correlation coefficient achieves 0.7 while removing 5 complex structures with modified residues/nucleotides and metal ions. While testing on ProNAB, the results showed that 71.60% of the prediction achieves Pearson correlation coefficient r = .61 and RMSE = 1.56 kcal/mol with experiment values.

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A structure-based model for the prediction of protein–RNA binding affinity

Cited by 13 publications

References 158 publications

A Novel Family of RNA-Binding Proteins Regulate Polysaccharide Metabolism inBacteroides thetaiotaomicron

A Novel Family of RNA-Binding Proteins Regulate Polysaccharide Metabolism inBacteroides thetaiotaomicron

The World of Stable Ribonucleoproteins and Its Mapping With Grad-Seq and Related Approaches

An updated dataset and a structure‐based prediction model for protein–RNA binding affinity

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