An account of solvent accessibility in protein-RNA recognition

@article{Mukherjee2018AnAO,
  title={An account of solvent accessibility in protein-RNA recognition},
  author={Sunandan Mukherjee and R. Bahadur},
  journal={Scientific Reports},
  year={2018},
  volume={8}
}
Protein–RNA recognition often induces conformational changes in binding partners. Consequently, the solvent accessible surface area (SASA) buried in contact estimated from the co-crystal structures may differ from that calculated using their unbound forms. To evaluate the change in accessibility upon binding, we compare SASA of 126 protein-RNA complexes between bound and unbound forms. We observe, in majority of cases the interface of both the binding partners gain accessibility upon binding… Expand
A structure-based model for the prediction of protein-RNA binding affinity.
TLDR
A binding affinity dataset of 40 protein-RNA complexes, for which at least one unbound partner is available in the docking benchmark, is curated and the best fit model with the lowest maximum error is provided with three interface parameters: relative hydrophobicity, conformational change upon binding and relative hydration pattern. Expand
Structural basis for mRNA recognition by human RBM38.
RNA-binding protein RBM38 was reported to bind the mRNA of several p53-related genes through its RRM domain and to up-regulate or down-regulate protein translation by increasing mRNA stability orExpand
Structural basis for mRNA recognition by human RBM38.
TLDR
The crystal structure of the RRM domain of human RBM38 in complex with a single-stranded RNA revealed the RNA-recognition mechanism of human G(U/C/A)GUG sequence single-Stranded RNA in a sequence-specific and structure-specific manner and provided structural information for understanding theRNA-binding property of R BM38. Expand
Single-sequence and profile-based prediction of RNA solvent accessibility using dilated convolutional neural network
TLDR
This work has developed RNAsnap2 that uses a dilated convolutional neural network with a new feature, based on predicted base-pairing probabilities from LinearPartition, that is expected to be useful for searching structural signatures and locating functional regions of non-coding RNAs. Expand
Investigating the mechanism of recognition and structural dynamics of nucleoprotein-RNA complex from Peste des petits ruminants virus via Gaussian accelerated molecular dynamics simulations.
TLDR
The root-mean-squared deviation analysis reveals that although MT2 deviates most significantly from the initial structure, the RNA binding region is more stable compared to WT or MT1, and the flexible nature of the N protein is revealed from the principal component analysis. Expand
Bioinformatics Tools and Benchmarks for Computational Docking and 3D Structure Prediction of RNA-Protein Complexes
TLDR
Currently available methods for macromolecular docking and for scoring 3D structural models of RNP complexes in particular are discussed and benchmarks that have been developed to assess the accuracy of these methods are reviewed. Expand
BIAPSS - BioInformatic Analysis of liquid-liquid Phase-Separating protein Sequences
TLDR
A novel open-source web platform named BIAPSS (BioInformatic Analysis of liquid-liquid Phase-Separating protein Sequences) which contains interactive data analytic tools in combination with a comprehensive repository of bioinformatic data for on-the-fly exploration of sequence-dependent properties of proteins with known LLPS behavior. Expand
Structural alterations in the catalytic core of hSIRT2 enzyme predict therapeutic benefits of Garcinia mangostana derivatives in Alzheimer's disease: molecular dynamics simulation study
Recent studies have shown that inhibition of the hSIRT2 enzyme provides favorable effects in neurodegenerative diseases such as Alzheimer's disease. Prenylated xanthone phytochemicals includingExpand
NCodR: A multi-class SVM classification to distinguish between non-coding RNAs in Viridiplantae
TLDR
This study analyses seven classes of ncRNAs in plants using sequence and secondary structure-based RNA folding measures, and trains eight different classifiers to discriminate various ncRNA classes in plants. Expand
Multi-feature fusion for deep learning to predict plant lncRNA-protein interaction.
TLDR
An integrative model, namely DRPLPI, which combines categorical boosting and extra trees into a single meta-learner, shows significant enhancement in the prediction performance compared with existing state-of-the-art methods. Expand

References

SHOWING 1-10 OF 51 REFERENCES
Probing binding hot spots at protein–RNA recognition sites
TLDR
A Random Forests model is developed that accurately predicts 80% of the instances of experimental ΔΔG values in a particular class, and provides a stepping-stone towards the engineering of protein–RNA recognition sites with desired affinity. Expand
Relative Solvent Accessible Surface Area Predicts Protein Conformational Changes upon Binding
TLDR
It is demonstrated that the relative solvent accessible surface area of monomeric proteins can be used as a simple proxy for protein flexibility, revealing a powerful connection between the flexibility of unbound proteins and their binding-induced conformational changes, consistent with the conformational selection model of molecular recognition. Expand
Functional Advantages of Conserved Intrinsic Disorder in RNA-Binding Proteins
TLDR
It is concluded that the functional role of intrinsically disordered protein segments in RNA-binding is two-fold: first, these regions establish extended, conserved electrostatic interfaces with RNAs via induced fit, and second, conformational flexibility enables them to target different RNA partners, providing multi-functionality, while also ensuring specificity. Expand
Protein-RNA interactions: a structural analysis.
TLDR
Although similar modes of secondary structure interactions have been observed in RNA and DNA binding proteins, the current analysis emphasises the differences that exist between the two types of nucleic acid binding protein at the atomic contact level. Expand
Reassessing buried surface areas in protein–protein complexes
TLDR
An examination of the bound and unbound structures points to a possible origin: local movements optimize contacts with the other component at the cost of internal contacts, and presumably also the binding free energy. Expand
Binding of the bacteriophage P22 N-peptide to the boxB RNA motif studied by molecular dynamics simulations.
TLDR
It was found that the electrostatic field of the RNA has a favorable influence on the coil-to-alpha-helix transition of the N-peptide already outside of the peptide-binding site, which indicates that electrostatic interactions near RNA molecules can lead to a shift in the equilibrium toward the bound form of an interacting partner before it enters the binding pocket. Expand
Dissecting protein–RNA recognition sites
TLDR
The 2′OH is a major player inprotein–RNA recognition, and shape complementarity an important determinant, whereas electrostatics and direct base–protein interactions play a lesser part than in protein–DNA recognition. Expand
The role of positively charged amino acids and electrostatic interactions in the complex of U1A protein and U1 hairpin II RNA
TLDR
Electrostatic roles of well-positioned positively charged residues can be important for both initial complex formation and complex maintenance, illustrating the multiple roles of electrostatic interactions in protein–RNA complexes. Expand
A protein–RNA docking benchmark (I): Nonredundant cases
TLDR
It is found that RNA is generally more flexible than the protein in the complexes, and the interface region is as flexible as the molecule as a whole. Expand
Hydration of protein–RNA recognition sites
TLDR
The role of water molecules in 89 protein–RNA complexes taken from the Protein Data Bank is investigated and preserved waters contribute toward the affinity in protein– RNA recognition and should be carefully treated while engineering protein-RNA interfaces. Expand
...
1
2
3
4
5
...