The Crucial Role of Conserved Intermolecular H-bonds Inaccessible to the Solvent in Formation and Stabilization of the TL5·5 SrRNA Complex

XGBPRH: Prediction of Binding Hot Spots at Protein⁻RNA Interfaces Utilizing Extreme Gradient Boosting

Hot spot residues at protein⁻RNA complexes are vitally important for investigating the underlying molecular recognition mechanism. Accurately identifying protein⁻RNA binding hot spots is critical for drug designing and protein engineering. Although some progress has been made by utilizing various available features and a series of machine learning approaches, these methods are still in the infant stage. In this paper, we present a new computational method named XGBPRH, which is based on an eXtreme Gradient Boosting (XGBoost) algorithm and can effectively predict hot spot residues in protein⁻RNA interfaces utilizing an optimal set of properties. Firstly, we download 47 protein⁻RNA complexes and calculate a total of 156 sequence, structure, exposure, and network features. Next, we adopt a two-step feature selection algorithm to extract a combination of 6 optimal features from the combination of these 156 features. Compared with the state-of-the-art approaches, XGBPRH achieves better performances with an area under the ROC curve (AUC) score of 0.817 and an F1-score of 0.802 on the independent test set. Meanwhile, we also apply XGBPRH to two case studies. The results demonstrate that the method can effectively identify novel energy hotspots.

Computational identification of binding energy hot spots in protein-RNA complexes using an ensemble approach

Motivation

Identifying RNA-binding residues, especially energetically favored hot spots, can provide valuable clues for understanding the mechanisms and functional importance of protein-RNA interactions. Yet, limited availability of experimentally recognized energy hot spots in protein-RNA crystal structures leads to the difficulties in developing empirical identification approaches. Computational prediction of RNA-binding hot spot residues is still in its infant stage.

Results

Here, we describe a computational method, PrabHot (Prediction of protein-RNA binding hot spots), that can effectively detect hot spot residues on protein-RNA binding interfaces using an ensemble of conceptually different machine learning classifiers. Residue interaction network features and new solvent exposure characteristics are combined together and selected for classification with the Boruta algorithm. In particular, two new reference datasets (benchmark and independent) have been generated containing 107 hot spots from 47 known protein-RNA complex structures. In 10-fold cross-validation on the training dataset, PrabHot achieves promising performances with an AUC score of 0.86 and a sensitivity of 0.78, which are significantly better than that of the pioneer RNA-binding hot spot prediction method HotSPRing. We also demonstrate the capability of our proposed method on the independent test dataset and gain a competitive advantage as a result.

Availability and implementation

The PrabHot webserver is freely available at http://denglab.org/PrabHot/.

Contact

leideng@csu.edu.cn.

Supplementary information

Supplementary data are available at Bioinformatics online.

Dynamics of Dof domain-DNA interaction in wheat: Insights from atomistic simulations and free energy landscape

DNA-binding one zinc finger protein (Dof) is a plant-specific transcription factor involved in numerous biological processes. In the current study, the plausible mechanism underlying Dof domain-DNA interaction in wheat was investigated using extensive molecular dynamics (MD) simulations analysis. We depicted that one key residue Lys29, possessing the ability to disturb the interaction between Dof domain-DNA upon substitution to Arg29. Frequent conformational changes were observed in Lys29Arg (K29R)-DNA complex during the entire MD simulation period, which significantly altered the interactions, thereby indicating the importance of Lys29 in complex stability. Principal component analysis and free energy landscape results also suggested strong affinity between wild-type Dof domain and DNA due to restricted atomic movement. Our study not only substantiates the structural and mechanistic insights of Dof transcription factor but also provides new avenues toward employment of these key amino acid residues in genetic engineering for development of abiotic stress tolerance crop plant.

Studying the properties of domain I of the ribosomal protein l1: incorporation into ribosome and regulation of the l1 operon expression

L1 is a conserved protein of the large ribosomal subunit. This protein binds strongly to the specific region of the high molecular weight rRNA of the large ribosomal subunit, thus forming a conserved flexible structural element--the L1 stalk. L1 protein also regulates translation of the operon that comprises its own gene. Crystallographic data suggest that L1 interacts with RNA mainly by means of its domain I. We show here for the first time that the isolated domain I of the bacterial protein L1 of Thermus thermophilus and Escherichia coli is able to incorporate in vivo into the E. coli ribosome. Furthermore, domain I of T. thermophilus L1 can regulate expression of the L1 gene operon of Archaea in the coupled transcription-translation system in vitro, as well as the intact protein. We have identified the structural elements of domain I of the L1 protein that may be responsible for its regulatory properties.

Bacterial 5S rRNA-binding proteins of the CTC family

The presence of CTC family proteins is a unique feature of bacterial cells. In the CTC family, there are true ribosomal proteins (found in ribosomes of exponentially growing cells), and at the same time there are also proteins temporarily associated with the ribosome (they are produced by the cells under stress only and incorporate into the ribosome). One feature is common for these proteins - they specifically bind to 5S rRNA. In this review, the history of investigations of the best known representatives of this family is described briefly. Structural organization of the CTC family proteins and their occurrence among known taxonomic bacterial groups are discussed. Structural features of 5S rRNA and CTC protein are described that predetermine their specific interaction. Taking into account the position of a CTC protein and its intermolecular contacts in the ribosome, a possible role of its complex with 5S rRNA in ribosome functioning is discussed.

New insights into the interaction of ribosomal protein L1 with RNA

The RNA-binding ability of ribosomal protein L1 is of profound interest, since L1 has a dual function as a ribosomal structural protein that binds rRNA and as a translational repressor that binds its own mRNA. Here, we report the crystal structure at 2.6 A resolution of ribosomal protein L1 from the bacterium Thermus thermophilus in complex with a 38 nt fragment of L1 mRNA from Methanoccocus vannielii. The conformation of RNA-bound T.thermophilus L1 differs dramatically from that of the isolated protein. Analysis of four copies of the L1-mRNA complex in the crystal has shown that domain II of the protein does not contribute to mRNA-specific binding. A detailed comparison of the protein-RNA interactions in the L1-mRNA and L1-rRNA complexes identified amino acid residues of L1 crucial for recognition of its specific targets on the both RNAs. Incorporation of the structure of bacterial L1 into a model of the Escherichia coli ribosome revealed two additional contact regions for L1 on the 23S rRNA that were not identified in previous ribosome models.

How essential are nonessential genes?

Gene essentiality in bacteria has been identified in silico, focusing on gene persistence, or experimentally, focusing on the growth of knockouts in rich media. Comparing 55 genomes of Firmicutes and Gamma-proteobacteria to identify the genes which, while persistent among genomes, do not lead to a lethal phenotype when inactivated, we show that the characteristics of persistence, conservation, expression, and location are shared between persistent nonessential (PNE) genes and experimentally essential genes. PNE genes show an overrepresentation of genes related to maintenance and stress response. This outlines the limits of current experimental techniques to define gene essentiality and highlights the essential role of genes implicated in maintenance which, although dispensable for growth, are not dispensable from an evolutionary point of view. Firmicutes and Gamma-proteobacteria are mostly differing in the construction of the cell envelope, DNA replication and proofreading, and RNA degradation. In addition to suggesting functions for persistent genes that had until now resisted identification, we show that these genes have many characters in common with experimentally identified essential genes. They should then be regarded as truly essential genes.