Free Energy Structure Research Articles

The loss of a hydrogen bond: Thermodynamic contributions of a non-standard nucleotide.

Non-standard nucleotides are ubiquitous in RNA. Thermodynamic studies with RNA duplexes containing non-standard nucleotides, whether incorporated naturally or chemically, can provide insight into the stability of Watson–Crick pairs and the role of specific functional groups in stabilizing a Watson–Crick pair. For example, an A-U, inosine•U and pseudouridine•A pair each form two hydrogen bonds. However, an RNA duplex containing a central I•U pair or central Ψ•A pair is 2.4 kcal/mol less stable or 1.7 kcal/mol more stable, respectively, than the corresponding duplex containing an A-U pair. In the non-standard nucleotide purine, hydrogen replaces the exocyclic amino group of A. This replacement results in a P•U pair containing only one hydrogen bond. Optical melting studies were performed with RNA duplexes containing P•U pairs adjacent to different nearest neighbors. The resulting thermodynamic parameters were compared to RNA duplexes containing A-U pairs in order to determine the contribution of the hydrogen bond involving the exocyclic amino group. Results indicate a loss of 1.78 kcal/mol, on average, when an internal P•U replaces A-U in an RNA duplex. This value is compared to the thermodynamics of a hydrogen bond determined by similar methods. Nearest neighbor parameters were derived for use in free energy and secondary structure prediction software.

Synthesis and Characterization of Coordination Compounds of Silver(I) Nitrite with Ligands Ethylenethiourea and N,N'-diethylthiourea

Silver(I) nitrate and ethylenethiourea ( etu) in 1 : 4 stochiometry have been reported [1]. Coordination compounds of A and B as silver(I) nitrite with etu and silver(I) nitrite with N,N’ -diethylthiourea ( detu) respectively, have never been done. The purposes of this study are to synthesize and characterize coordination compounds of A and B. Synthesis coordination compound of A with 1 : 4, while B with 1 : 2 stoichiometry. Both of coordination compounds are conducted directly in acetonitrile. Compounds obtained are characterized by melting point, electrical conductivity measurement, SEM-EDX , qualitative nitrite test, free energy calculation and structures prediction using Spartan’14 v1.1.0 . Coordination compounds of A and B are colourless needle and prism crystals; have melting point of 189°C and 103-105°C; free energy of -289,2567 and -1182.8101 kJ/mol respectively. Electrical conductivity measurement and qualitative nitrite test show that the obtained compound of A is an ionic and B is a molecular one. EDX analysis gives empirical formula prediction of two coordination compound A is C 12 H 24 AgN 9 O 2 S 4 and B is C 15 H 36 AgN 7 O 2 S 3 .

Combinatorial RNA Design: Designability and Structure-Approximating Algorithm in Watson–Crick and Nussinov–Jacobson Energy Models

We consider the Combinatorial RNA Design problem, a minimal instance of RNA design where one must produce an RNA sequence that adopts a given secondary structure as its minimal free-energy structure. We consider two free-energy models where the contributions of base pairs are additive and independent: the purely combinatorial Watson-Crick model, which only allows equally-contributing A − U and C − G base pairs, and the real-valued Nussinov-Jacobson model, which associates arbitrary energies to A − U, C − G and G − U base pairs. We first provide a complete characterization of designable structures using restricted alphabets and, in the four-letter alphabet, provide a complete characterization for designable structures without unpaired bases. When unpaired bases are allowed, we characterize extensive classes of (non-)designable structures, and prove the closure of the set of designable structures under the stutter operation. Membership of a given structure to any of the classes can be tested in Θ(n) time, including the generation of a solution sequence for positive instances. Finally, we consider a structure-approximating relaxation of the design, and provide a Θ(n) algorithm which, given a structure S that avoids two trivially non-designable motifs, transforms S into a designable structure constructively by adding at most one base-pair to each of its stems.

Confined Water Determines Transport Properties of Guest Molecules in Narrow Pores.

We computed the transport of methane through 1 nm wide slit-shaped pores carved out of solid substrates. Models for silica, magnesium oxide, and alumina were used as solid substrates. The pores were filled with water. The results show that the methane permeability through the hydrated pores is strongly dependent on the solid substrate. Detailed analysis of the simulated systems reveals that local properties of confined water, including its structure, and more importantly, evolution of solvation free energy and hydrogen bond structure are responsible for the pronounced differences observed. The simulations are extended to multicomponent systems representative of natural gas, containing methane, ethane, and H2S. The results show that all pores considered have high affinity for H2S, moderate affinity for methane, and low affinity for ethane. The H2S/methane transport selectivity through the hydrated alumina pore is comparable, or superior, to that reported for existing commercial membranes. A multiscale approach was then implemented to demonstrate that a Smoluchowski one-dimensional model is able to reproduce the molecular-level results for short pores when appropriate values for the local self-diffusion coefficients are used as input parameters. We propose that the model can be extended to predict methane transport through uniform hydrated pores of macroscopic length. When verified by experiments, our simulation results could have important implications in applications such as natural gas sweetening and predictions of methane migration through hydraulically fractured shale formations.

Synteny and comparative analysis of miRNA retention, conservation, and structure across Brassicaceae reveals lineage- and sub-genome-specific changes.

The recent availability of genome sequences together with syntenic block information for Brassicaceae offers an opportunity to study microRNA (miRNA) evolution across this family. We employed a synteny-based comparative genomics strategy to unambiguously identify miRNA homologs from the genome sequence of members of Brassicaceae. Such an analysis of miRNA across Brassicaceae allowed us to classify miRNAs as conserved, lineage-, karyotype- and sub-genome-specific. The differential loss of miRNA from sub-genomes in polyploid genomes of Brassica rapa and Brassica oleracea shows that miRNA also follows the rules of gene fractionation as observed in the case of protein-coding genes. The study of mature and miR* region of precursors revealed instances of in-dels and SNPs which reflect the evolutionary history of the genomes. High level of conservation in miR* regions in some cases points to their functional relevance which needs to be further investigated. We further show that sequence and length variability in precursor sequences can affect the free energy and foldback structure of miRNA which may ultimately affect their biogenesis and expression in the biological system.

VfoldCPX Server for RNA/RNA Complex Structure Prediction

RNA/RNA interactions are essential for genomic RNA dimerization and regulation of gene expression. Predicting the structure and folding stabilities of RNA/RNA complexes is a biologically significant problem. We recently developed a new web server, VfoldCPX, to predict two-dimensional (2D) structures of RNA/RNA complexes from the sequence. The server is based on a new Vfold model that employs coarse-grained entropy parameters for the different structural motifs. By taking into account both the intra- and inter-molecular interactions, the model can predict RNA/RNA structures with cross-linked tertiary contacts. Furthermore, in addition to the minimum free energy structure, the server can predict multiple energetically stable structures ranked by their stabilities. The predicted structures can offer users with extensive insights into the folding and conformational switches in RNA biological functions. The web server is freely accessible at “http://rna.physics.missouri.edu”.

Sequence co-evolutionary information is a natural partner to minimally-frustrated models of biomolecular dynamics.

Experimentally derived structural constraints have been crucial to the implementation of computational models of biomolecular dynamics. For example, not only does crystallography provide essential starting points for molecular simulations but also high-resolution structures permit for parameterization of simplified models. Since the energy landscapes for proteins and other biomolecules have been shown to be minimally frustrated and therefore funneled, these structure-based models have played a major role in understanding the mechanisms governing folding and many functions of these systems. Structural information, however, may be limited in many interesting cases. Recently, the statistical analysis of residue co-evolution in families of protein sequences has provided a complementary method of discovering residue-residue contact interactions involved in functional configurations. These functional configurations are often transient and difficult to capture experimentally. Thus, co-evolutionary information can be merged with that available for experimentally characterized low free-energy structures, in order to more fully capture the true underlying biomolecular energy landscape.

Novel Approach to Analyzing MFE of Noncoding RNA Sequences.

Genomic studies have become noncoding RNA (ncRNA) centric after the study of different genomes provided enormous information on ncRNA over the past decades. The function of ncRNA is decided by its secondary structure, and across organisms, the secondary structure is more conserved than the sequence itself. In this study, the optimal secondary structure or the minimum free energy (MFE) structure of ncRNA was found based on the thermodynamic nearest neighbor model. MFE of over 2600 ncRNA sequences was analyzed in view of its signal properties. Mathematical models linking MFE to the signal properties were found for each of the four classes of ncRNA analyzed. MFE values computed with the proposed models were in concordance with those obtained with the standard web servers. A total of 95% of the sequences analyzed had deviation of MFE values within ±15% relative to those obtained from standard web servers.

Wettability behavior of special microscale ZnO nail-coated mesh films for oil–water separation

The surface free energy and geometrical structure are two important factors to govern the surface wettability. However, the design and simple synthesis of materials with specific surface free energy and geometrical structure, and their elaborate regulations are still a key challenge. Herein, through one-step thermal evaporation method, we successfully synthesized aligned arrays of highly crystallized ZnO with modulated nail structures on the stainless steel meshes for the first time. Owing to the decoration of [0001] oriented nail structures, the wire surface of meshes were indeed enclosed by the ZnO (0002) facets, which had the lowest surface energy in wurtzite structure. Under no any further modifications, just by regulating the nail structure and density as well as the mesh pore sizes, we not only obtained ZnO nail-coated mesh with hydrophobic, oleophilic (oil penetration), and underwater oleophilic properties, but also fabricated one with hydrophilic (water penetration), oleophilic (oil penetration), and underwater superoleophobic properties. Furthermore, interestingly, the separation of oil and water mixture was realized by utilizing two ZnO-nail coated meshes with different wettability. The underlying mechanism was investigated and discussed in the work. Therefore, our study provides interesting insight into the design of novel functional films with desired surface wettability for the separation of oil–water mixture.

Nucleotide Substitution in 3' Arm of Bovine MIR-2467 in Five Cattle Breeds

The T > C single nucleotide polymorphism (SNP) in the MIR2467 gene was investigated in order to confirm its presence in cattle genome and to check for possible differences in its genotype distribution among different breeds. Additional purpose of the study was to investigate in silico potential effect of that substitution on the structure and stability of precursor mir-2467. The study involved 634 individuals of five cattle breeds: Angus, Hereford, Holstein-Friesian, Jersey, and Limousin, which were genotyped using PCR-RFLP assay. In this study, the presence of T > C polymorphism at position 24 was observed in all the cattle breeds excepting Hereford. In addition, the differences in the genotype distribution among analyzed breeds were indicated. On the basis of minimum free energy structure prediction, the C allele was indicated to have possible impact on decreasing the stability of the pre-mir-2467, thus altering its ability to regulate target genes expression.

Octa-Coordination and the Aqueous Ba(2+) Ion.

The hydration structure of Ba(2+) ion is important for understanding blocking mechanisms in potassium ion channels. Here, we combine statistical mechanical theory, ab initio molecular dynamics simulations, and electronic structure methods to calculate the hydration free energy and local hydration structure of Ba(2+)(aq). The predicted hydration free energy (-304 ± 1 kcal/mol) agrees with the experimental value (-303 kcal/mol) when a maximally occupied, unimodal inner solvation shell is treated. In the local environment defined by the first shell of hydrating waters, Ba(2+) is directly and stably coordinated by eight (8) waters. Octa-coordination resembles the crystal structure of Ba(2+) and K(+) bound in potassium ion channels, but differs from the local hydration structure of K(+)(aq) determined earlier.

An RNA secondary structure prediction method based on minimum and suboptimal free energy structures

The function of an RNA-molecule is mainly determined by its tertiary structures. And its secondary structure is an important determinant of its tertiary structure. The comparative methods usually give better results than the single-sequence methods. Based on minimum and suboptimal free energy structures, the paper presents a novel method for predicting conserved secondary structure of a group of related RNAs. In the method, the information from the known RNA structures is used as training data in a SVM (Support Vector Machine) classifier. Our method has been tested on the benchmark dataset given by Puton et al. The results show that the average sensitivity of our method is higher than that of other comparative methods such as CentroidAlifold, MXScrana, RNAalifold, and TurboFold.

RNA secondary structure prediction based on SHAPE data in helix regions

RNA molecules play important and fundamental roles in biological processes. Frequently, the functional form of single-stranded RNA molecules requires a specific tertiary structure. Classically, RNA structure determination has mostly been accomplished by X-Ray crystallography or Nuclear Magnetic Resonance approaches. These experimental methods are time consuming and expensive. In the past two decades, some computational methods and algorithms have been developed for RNA secondary structure prediction. In these algorithms, minimum free energy is known as the best criterion. However, the results of algorithms show that minimum free energy is not a sufficient criterion to predict RNA secondary structure. These algorithms need some additional knowledge about the structure, which has to be added in the methods. Recently, the information obtained from some experimental data, called SHAPE, can greatly improve the consistency between the native and predicted RNA secondary structure.In this paper, we investigate the influence of SHAPE data on four types of RNA substructures, helices, loops, base pairs from the start and end of helices and two base pairs from the start and end of helices. The results show that SHAPE data in helix regions can improve the prediction. We represent a new method to apply SHAPE data in helix regions for finding RNA secondary structure. Finally, we compare the results of the method on a set of RNAs to predict minimum free energy structure based on considering all SHAPE data and only SHAPE data in helix regions as pseudo free energy and without SHAPE data (without any pseudo free energy).The results show that RNA secondary structure prediction based on considering only SHAPE data in helix regions is more successful than not considering SHAPE data and it provides competitive results in comparison with considering all SHAPE data.

Computational estimation of pKa values

The pKa of a compound is one of its most important properties as it defines the specific molecular forms that will prevail under different pH conditions. Accordingly, accurate means for computational estimation of this property are of particular interest. Two main techniques for this purpose have emerged: (1) a first principles approach that relies on basic physical concepts and requires high computational resources, but is independent of experimental input and (2) a linear free energy or quantitative structure–activity relationship (QSAR) approach that combines molecular structural and energetic descriptors with available experimental pKa data to reduce computational demand and yield good accuracy. In this overview, these methods are described and their advantages and limitations are noted. WIREs Comput Mol Sci 2015, 5:290–297. doi: 10.1002/wcms.1218This article is categorized under: Structure and Mechanism > Molecular Structures Structure and Mechanism > Computational Biochemistry and Biophysics Computer and Information Science > Chemoinformatics

A nuclear ribosomal DNA pseudogene in triatomines opens a new research field of fundamental and applied implications in Chagas disease.

A pseudogene, designated as "ps(5.8S+ITS-2)", paralogous to the 5.8S gene and internal transcribed spacer (ITS)-2 of the nuclear ribosomal DNA (rDNA), has been recently found in many triatomine species distributed throughout North America, Central America and northern South America. Among characteristics used as criteria for pseudogene verification, secondary structures and free energy are highlighted, showing a lower fit between minimum free energy, partition function and centroid structures, although in given cases the fit only appeared to be slightly lower. The unique characteristics of "ps(5.8S+ITS-2)" as a processed or retrotransposed pseudogenic unit of the ghost type are reviewed, with emphasis on its potential functionality compared to the functionality of genes and spacers of the normal rDNA operon. Besides the technical problem of the risk for erroneous sequence results, the usefulness of "ps(5.8S+ITS-2)" for specimen classification, phylogenetic analyses and systematic/taxonomic studies should be highlighted, based on consistence and retention index values, which in pseudogenic sequence trees were higher than in functional sequence trees. Additionally, intraindividual, interpopulational and interspecific differences in pseudogene amount and the fact that it is a pseudogene in the nuclear rDNA suggests a potential relationships with fitness, behaviour and adaptability of triatomine vectors and consequently its potential utility in Chagas disease epidemiology and control.

The ViennaRNA web services.

The ViennaRNA package is a widely used collection of programs for thermodynamic RNA secondary structure prediction. Over the years, many additional tools have been developed building on the core programs of the package to also address issues related to noncoding RNA detection, RNA folding kinetics, or efficient sequence design considering RNA-RNA hybridizations. The ViennaRNA web services provide easy and user-friendly web access to these tools. This chapter describes how to use this online platform to perform tasks such as prediction of minimum free energy structures, prediction of RNA-RNA hybrids, or noncoding RNA detection. The ViennaRNA web services can be used free of charge and can be accessed via http://rna.tbi.univie.ac.at.

Free energy minimization to predict RNA secondary structures and computational RNA design.

Determining the RNA secondary structure from sequence data by computational predictions is a long-standing problem. Its solution has been approached in two distinctive ways. If a multiple sequence alignment of a collection of homologous sequences is available, the comparative method uses phylogeny to determine conserved base pairs that are more likely to form as a result of billions of years of evolution than by chance. In the case of single sequences, recursive algorithms that compute free energy structures by using empirically derived energy parameters have been developed. This latter approach of RNA folding prediction by energy minimization is widely used to predict RNA secondary structure from sequence. For a significant number of RNA molecules, the secondary structure of the RNA molecule is indicative of its function and its computational prediction by minimizing its free energy is important for its functional analysis. A general method for free energy minimization to predict RNA secondary structures is dynamic programming, although other optimization methods have been developed as well along with empirically derived energy parameters. In this chapter, we introduce and illustrate by examples the approach of free energy minimization to predict RNA secondary structures.

Structural basis of genomic RNA (gRNA) dimerization and packaging determinants of mouse mammary tumor virus (MMTV).

BackgroundOne of the hallmarks of retroviral life cycle is the efficient and specific packaging of two copies of retroviral gRNA in the form of a non-covalent RNA dimer by the assembling virions. It is becoming increasingly clear that the process of dimerization is closely linked with gRNA packaging, and in some retroviruses, the latter depends on the former. Earlier mutational analysis of the 5’ end of the MMTV genome indicated that MMTV gRNA packaging determinants comprise sequences both within the 5’ untranslated region (5’ UTR) and the beginning of gag.ResultsThe RNA secondary structure of MMTV gRNA packaging sequences was elucidated employing selective 2’hydroxyl acylation analyzed by primer extension (SHAPE). SHAPE analyses revealed the presence of a U5/Gag long-range interaction (U5/Gag LRI), not predicted by minimum free-energy structure predictions that potentially stabilizes the global structure of this region. Structure conservation along with base-pair covariations between different strains of MMTV further supported the SHAPE-validated model. The 5’ region of the MMTV gRNA contains multiple palindromic (pal) sequences that could initiate intermolecular interaction during RNA dimerization. In vitro RNA dimerization, SHAPE analysis, and structure prediction approaches on a series of pal mutants revealed that MMTV RNA utilizes a palindromic point of contact to initiate intermolecular interactions between two gRNAs, leading to dimerization. This contact point resides within pal II (5’ CGGCCG 3’) at the 5’ UTR and contains a canonical “GC” dyad and therefore likely constitutes the MMTV RNA dimerization initiation site (DIS). Further analyses of these pal mutants employing in vivo genetic approaches indicate that pal II, as well as pal sequences located in the primer binding site (PBS) are both required for efficient MMTV gRNA packaging.ConclusionsEmploying structural prediction, biochemical, and genetic approaches, we show that pal II functions as a primary point of contact between two MMTV RNAs, leading to gRNA dimerization and its subsequent encapsidation into the assembling virus particles. The results presented here enhance our understanding of the MMTV gRNA dimerization and packaging processes and the role of structural motifs with respect to RNA-RNA and possibly RNA-protein interactions that might be taking place during MMTV life cycle.Electronic supplementary materialThe online version of this article (doi:10.1186/s12977-014-0096-6) contains supplementary material, which is available to authorized users.

Expected degree for RNA secondary structure networks.

Consider the network of all secondary structures of a given RNA sequence, where nodes are connected when the corresponding structures have base pair distance one. The expected degree of the network is the average number of neighbors, where average may be computed with respect to the either the uniform or Boltzmann probability. Here, we describe the first algorithm, RNAexpNumNbors, that can compute the expected number of neighbors, or expected network degree, of an input sequence. For RNA sequences from the Rfam database, the expected degree is significantly less than the constrained minimum free energy structure, defined to have minimum free energy (MFE) over all structures consistent with the Rfam consensus structure. The expected degree of structural RNAs, such as purine riboswitches, paradoxically appears to be smaller than that of random RNA, yet the difference between the degree of the MFE structure and the expected degree is larger than that of random RNA. Expected degree does not seem to correlate with standard structural diversity measures of RNA, such as positional entropy and ensemble defect. The program RNAexpNumNbors is written in C, runs in cubic time and quadratic space, and is publicly available at http://bioinformatics.bc.edu/clotelab/RNAexpNumNbors.

Re-print of “Gas-phase acid–base properties of homocysteine, homoserine, 5-mercaptonorvaline and 5-hydroxynorvaline from the extended kinetic method”

The gas-phase proton affinities (PA) and gas-phase acidities (GA) for the non-protein amino acids homocysteine (hcys), homoserine (hser), 5-mercaptonorvaline (hhcys), and 5-hydroxynorvaline (hhser) have been determined using the extended kinetic method in an ESI-triple quadrupole instrument. Increasing the length of the side chain of cysteine by one and two methylene units has a dramatic effect on the proton affinity. The PAs of hcys and hhcys were determined to be 932±9kJ/mol and 944±9kJ/mol, 29 and 41kJ/mol more basic than cysteine. The proton affinity enhancement for the serine homologs is more dramatic. PAs of 951±11 and 986±10kJ/mol were measured for hser and hhser, 39 and 74kJ/mol more basic than serine. The proton affinity enhancement can be rationalized by the increased stability of internally hydrogen-bonded structures in the cations of the homo-amino acids with longer side chains. High-level density functional theory calculations confirm the cyclic structures for the cations and give predictions for the proton affinities that are in excellent agreement with the measured results. The GAs for hcys was determined to be 1398±10kJ/mol which is the same as the GA of cysteine (1396±9kJ/mol). Calculations predict that as with cysteine, the preferred site of deprotonation for hcys is the sulfur atom in the side chain rather than the carboxylic acid group. For hhcys, the lowest enthalpy structure is an internally-hydrogen-bonded thiolate, while the lowest free energy structure is a carboxylate with an extended side chain. These conformers lie within 5kJ/mol of each other in both enthalpy and free energy and should both be populated in a gas-phase sample. Theoretical predictions for the acidities of hcys and hhcys predict a slight trend in acidity with increasing side-chain length. The experimental GA for hser was determined to be 1394±10, the same as serine (1393kJ/mol), and calculations predict that Ser, hser, and hhser all have the same acidity within error.