Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Classification and energetics of the base-phosphate interactions in RNA.

ABSTRACT: Structured RNA molecules form complex 3D architectures stabilized by multiple interactions involving the nucleotide base, sugar and phosphate moieties. A significant percentage of the bases in structured RNA molecules in the Protein Data Bank (PDB) hydrogen-bond with phosphates of other nucleotides. By extracting and superimposing base-phosphate (BPh) interactions from a reduced-redundancy subset of 3D structures from the PDB, we identified recurrent phosphate-binding sites on the RNA bases. Quantum chemical calculations were carried out on model systems representing each BPh interaction. The calculations show that the centers of each cluster obtained from the structure superpositions correspond to energy minima on the potential energy hypersurface. The calculations also show that the most stable phosphate-binding sites occur on the Watson-Crick edge of guanine and the Hoogsteen edge of cytosine. We modified the 'Find RNA 3D' (FR3D) software suite to automatically find and classify BPh interactions. Comparison of the 3D structures of the 16S and 23S rRNAs of Escherichia coli and Thermus thermophilus revealed that most BPh interactions are phylogenetically conserved and they occur primarily in hairpin, internal or junction loops or as part of tertiary interactions. Bases that form BPh interactions, which are conserved in the rRNA 3D structures are also conserved in homologous rRNA sequence alignments.

SUBMITTER: Zirbel CL

PROVIDER: S-EPMC2731888 | biostudies-literature | 2009 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Geometric nomenclature and classification of RNA base pairs.

Project description:Non-Watson-Crick base pairs mediate specific interactions responsible for RNA-RNA self-assembly and RNA-protein recognition. An unambiguous and descriptive nomenclature with well-defined and nonoverlapping parameters is needed to communicate concisely structural information about RNA base pairs. The definitions should reflect underlying molecular structures and interactions and, thus, facilitate automated annotation, classification, and comparison of new RNA structures. We propose a classification based on the observation that the planar edge-to-edge, hydrogen-bonding interactions between RNA bases involve one of three distinct edges: the Watson-Crick edge, the Hoogsteen edge, and the Sugar edge (which includes the 2'-OH and which has also been referred to as the Shallow-groove edge). Bases can interact in either of two orientations with respect to the glycosidic bonds, cis or trans relative to the hydrogen bonds. This gives rise to 12 basic geometric types with at least two H bonds connecting the bases. For each geometric type, the relative orientations of the strands can be easily deduced. High-resolution examples of 11 of the 12 geometries are presently available. Bifurcated pairs, in which a single exocyclic carbonyl or amino group of one base directly contacts the edge of a second base, and water-inserted pairs, in which single functional groups on each base interact directly, are intermediate between two of the standard geometries. The nomenclature facilitates the recognition of isosteric relationships among base pairs within each geometry, and thus facilitates the recognition of recurrent three-dimensional motifs from comparison of homologous sequences. Graphical conventions are proposed for displaying non-Watson-Crick interactions on a secondary structure diagram. The utility of the classification in homology modeling of RNA tertiary motifs is illustrated.

| S-EPMC1370104 | biostudies-other

Comprehensive survey and geometric classification of base triples in RNA structures.

Project description:Base triples are recurrent clusters of three RNA nucleobases interacting edge-to-edge by hydrogen bonding. We find that the central base in almost all triples forms base pairs with the other two bases of the triple, providing a natural way to geometrically classify base triples. Given 12 geometric base pair families defined by the Leontis-Westhof nomenclature, combinatoric enumeration predicts 108 potential geometric base triple families. We searched representative atomic-resolution RNA 3D structures and found instances of 68 of the 108 predicted base triple families. Model building suggests that some of the remaining 40 families may be unlikely to form for steric reasons. We developed an on-line resource that provides exemplars of all base triples observed in the structure database and models for unobserved, predicted triples, grouped by triple family, as well as by three-base combination (http://rna.bgsu.edu/Triples). The classification helps to identify recurrent triple motifs that can substitute for each other while conserving RNA 3D structure, with applications in RNA 3D structure prediction and analysis of RNA sequence evolution.

| S-EPMC3287178 | biostudies-literature

Energetics of protein-DNA interactions.

Project description:Protein-DNA interactions are vital for many processes in living cells, especially transcriptional regulation and DNA modification. To further our understanding of these important processes on the microscopic level, it is necessary that theoretical models describe the macromolecular interaction energetics accurately. While several methods have been proposed, there has not been a careful comparison of how well the different methods are able to predict biologically important quantities such as the correct DNA binding sequence, total binding free energy and free energy changes caused by DNA mutation. In addition to carrying out the comparison, we present two important theoretical models developed initially in protein folding that have not yet been tried on protein-DNA interactions. In the process, we find that the results of these knowledge-based potentials show a strong dependence on the interaction distance and the derivation method. Finally, we present a knowledge-based potential that gives comparable or superior results to the best of the other methods, including the molecular mechanics force field AMBER99.

| S-EPMC1851630 | biostudies-literature

Evolutionary Analyses of Base-Pairing Interactions in DNA and RNA Secondary Structures.

Project description:Pairs of nucleotides within functional nucleic acid secondary structures often display evidence of coevolution that is consistent with the maintenance of base-pairing. Here, we introduce a sequence evolution model, MESSI (Modeling the Evolution of Secondary Structure Interactions), that infers coevolution associated with base-paired sites in DNA or RNA sequence alignments. MESSI can estimate coevolution while accounting for an unknown secondary structure. MESSI can also use graphics processing unit parallelism to increase computational speed. We used MESSI to infer coevolution associated with GC, AU (AT in DNA), GU (GT in DNA) pairs in noncoding RNA alignments, and in single-stranded RNA and DNA virus alignments. Estimates of GU pair coevolution were found to be higher at base-paired sites in single-stranded RNA viruses and noncoding RNAs than estimates of GT pair coevolution in single-stranded DNA viruses. A potential biophysical explanation is that GT pairs do not stabilize DNA secondary structures to the same extent that GU pairs do in RNA. Additionally, MESSI estimates the degrees of coevolution at individual base-paired sites in an alignment. These estimates were computed for a SHAPE-MaP-determined HIV-1 NL4-3 RNA secondary structure. We found that estimates of coevolution were more strongly correlated with experimentally determined SHAPE-MaP pairing scores than three nonevolutionary measures of base-pairing covariation. To assist researchers in prioritizing substructures with potential functionality, MESSI automatically ranks substructures by degrees of coevolution at base-paired sites within them. Such a ranking was created for an HIV-1 subtype B alignment, revealing an excess of top-ranking substructures that have been previously identified as having structure-related functional importance, among several uncharacterized top-ranking substructures.

| S-EPMC6993869 | biostudies-literature

Detecting Multivariate Gene Interactions in RNA-Seq Data Using Optimal Bayesian Classification.

Project description:Differential gene expression testing is an analysis commonly applied to RNA-Seq data. These statistical tests identify genes that are significantly different across phenotypes. We extend this testing paradigm to multivariate gene interactions from a classification perspective with the goal to detect novel gene interactions for the phenotypes of interest. This is achieved through our novel computational framework comprised of a hierarchical statistical model of the RNA-Seq processing pipeline and the corresponding optimal Bayesian classifier. Through Markov Chain Monte Carlo sampling and Monte Carlo integration, we compute quantities where no analytical formulation exists. The performance is then illustrated on an expression dataset from a dietary intervention study where we identify gene pairs that have low classification error yet were not identified as differentially expressed. Additionally, we have released the software package to perform OBC classification on RNA-Seq data under an open source license and is available at http://bit.ly/obc_package.

| S-EPMC4818202 | biostudies-other

CompAnnotate: a comparative approach to annotate base-pairing interactions in RNA 3D structures.

Project description:The analysis of RNA tertiary structure is hindered by the fact that not too many structural data are available and a significant amount of them are in low resolution. Due to the atomic coordinate errors posed by the limitations of low-resolution RNA three-dimensional structures, it becomes a critical challenge to extract key geometric characteristics of RNA, particularly, the interaction of bases. To address this issue, we have devised a comparative method, named CompAnnotate, that utilizes more precise structural information of high-resolution homologs to annotate the base-pairing interactions in the low-resolution structures, by aligning and making comparative geometric assessments. The benchmarking results show that our method can improve the annotations of the existing methods significantly. We have achieved different levels of improvements for various methods and datasets, including an example of significant sensitivity and precision enhancement from 28 to 57% and from 53 to 82%, respectively.

| S-EPMC5737500 | biostudies-literature

A Max-Margin Model for Predicting Residue-Base Contacts in Protein-RNA Interactions.

Project description:Protein-RNA interactions (PRIs) are essential for many biological processes, so understanding aspects of the sequences and structures involved in PRIs is important for unraveling such processes. Because of the expensive and time-consuming techniques required for experimental determination of complex protein-RNA structures, various computational methods have been developed to predict PRIs. However, most of these methods focus on predicting only RNA-binding regions in proteins or only protein-binding motifs in RNA. Methods for predicting entire residue-base contacts in PRIs have not yet achieved sufficient accuracy. Furthermore, some of these methods require the identification of 3D structures or homologous sequences, which are not available for all protein and RNA sequences. Here, we propose a prediction method for predicting residue-base contacts between proteins and RNAs using only sequence information and structural information predicted from sequences. The method can be applied to any protein-RNA pair, even when rich information such as its 3D structure, is not available. In this method, residue-base contact prediction is formalized as an integer programming problem. We predict a residue-base contact map that maximizes a scoring function based on sequence-based features such as k-mers of sequences and the predicted secondary structure. The scoring function is trained using a max-margin framework from known PRIs with 3D structures. To verify our method, we conducted several computational experiments. The results suggest that our method, which is based on only sequence information, is comparable with RNA-binding residue prediction methods based on known binding data.

| S-EPMC8624843 | biostudies-literature

Energetics and Vibrational Signatures of Nucleobase Argyrophilic Interactions.

Project description:This study investigates the interactions of both purine (adenine and guanine) and pyrimidine (cytosine, thymine, and uracil) nucleobases with a pair of silver atoms (Ag2). Full geometry optimizations were performed on several structures of each nucleobase/Ag2 complex and the corresponding isolated monomers using the M06-2X density functional with a correlation consistent triple-? basis set augmented with diffuse functions on all atoms and a relativistic pseudopotential on Ag (aug-cc-pVTZ for H, C, N, and O and aug-cc-pVTZ-PP for Ag; denoted aVTZ). Harmonic vibrational frequency computations indicate that each optimized structure corresponds to a minimum on the M06-2X/aVTZ potential energy surface. Relative electronic energies for interactions between Ag2 and each nucleobase were compared to elucidate energetic differences between isomers. Further analysis of the changes in vibrational frequencies, infrared intensities, and Raman scattering activities reveals how different Ag2 binding sites might be differentiated spectroscopically. These results provide molecular-level insight into the interactions between nucleobases and silver, which may lead to better understanding and interpretation of surface-enhanced Raman spectroscopy experiments on nucleobases and related systems.

| S-EPMC6645001 | biostudies-literature

Single-molecule analysis of DNA base-stacking energetics using patterned DNA nanostructures.

Project description:The DNA double helix structure is stabilized by base-pairing and base-stacking interactions. However, a comprehensive understanding of dinucleotide base-stacking energetics is lacking. Here we combined multiplexed DNA-based point accumulation in nanoscale topography (DNA-PAINT) imaging with designer DNA nanostructures and measured the free energy of dinucleotide base stacking at the single-molecule level. Multiplexed imaging enabled us to extract the binding kinetics of an imager strand with and without additional dinucleotide stacking interactions. The DNA-PAINT data showed that a single additional dinucleotide base stacking results in up to 250-fold stabilization for the DNA duplex nanostructure. We found that the dinucleotide base-stacking energies vary from -0.95 ± 0.12 kcal mol-1 to -3.22 ± 0.04 kcal mol-1 for C|T and A|C base-stackings, respectively. We demonstrate the application of base-stacking energetics in designing DNA-PAINT probes for multiplexed super-resolution imaging, and efficient assembly of higher-order DNA nanostructures. Our results will aid in designing functional DNA nanostructures, and DNA and RNA aptamers, and facilitate better predictions of the local DNA structure.

| S-EPMC10716042 | biostudies-literature

Widespread transient Hoogsteen base pairs in canonical duplex DNA with variable energetics.

Project description:Hoogsteen (HG) base pairing involves a 180° rotation of the purine base relative to Watson-Crick (WC) base pairing within DNA duplexes, creating alternative DNA conformations that can play roles in recognition, damage induction and replication. Here, using nuclear magnetic resonance R1ρ relaxation dispersion, we show that transient HG base pairs occur across more diverse sequence and positional contexts than previously anticipated. We observe sequence-specific variations in HG base pair energetic stabilities that are comparable with variations in WC base pair stability, with HG base pairs being more abundant for energetically less favourable WC base pairs. Our results suggest that the variations in HG stabilities and rates of formation are dominated by variations in WC base pair stability, suggesting a late transition state for the WC-to-HG conformational switch. The occurrence of sequence and position-dependent HG base pairs provide a new potential mechanism for achieving sequence-dependent DNA transactions.

| S-EPMC4537320 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data