Base Pair Distance Research Articles

Insights into elastic properties of coarse-grained DNA models: q-stiffness of cgDNA vs cgDNA.

Coarse-grained models have emerged as valuable tools to simulate long DNA molecules while maintaining computational efficiency. These models aim at preserving interactions among coarse-grained variables in a manner that mirrors the underlying atomistic description. We explore here a method for testing coarse-grained vs all-atom models using stiffness matrices in Fourier space (q-stiffnesses), which are particularly suited to probe DNA elasticity at different length scales. We focus on a class of coarse-grained rigid base DNA models known as cgDNA and its most recent version, cgDNA+. Our analysis shows that while cgDNA+ closely follows the q-stiffnesses of the all-atom model, the original cgDNA shows some deviations for twist and bending variables, which are rather strong in the q → 0 (long length scale) limit. The consequence is that while both cgDNA and cgDNA+ give a suitable description of local elastic behavior, the former misses some effects that manifest themselves at longer length scales. In particular, cgDNA performs poorly on twist stiffness, with a value much lower than expected for long DNA molecules. Conversely, the all-atom and cgDNA+ twist are strongly length scale dependent: DNA is torsionally soft at a few base pair distances but becomes more rigid at distances of a few dozen base pairs. Our analysis shows that the bending persistence length in all-atom and cgDNA+ is somewhat overestimated.

Large bubble drives circular DNA melting.

We investigate the melting transition of non-supercoiled circular DNA of different lengths, employing Brownian dynamics simulations. In the absence of supercoiling, we find that melting of circular DNA is driven by a large bubble, which agrees with the previous predictions of circular DNA melting in the presence of supercoiling. By analyzing sector-wise changes in average base-pair distance, our study reveals that the melting behavior of circular DNA closely resembles that of linear DNA. Additionally, we find a marked difference in the thermal stability of circular DNA over linear DNA at very short length scales, an effect that diminishes as the length of circular DNA increases. The stability of smaller circular DNA is linked to the occurrence of transient small bubbles, characterized by a lower probability of growth.

Ab initio Modeling of Hydrogen Bonding of Remdesivir and Adenosine with Uridine.

Remdesivir (RDV) emerged as an effective drug against the SARS-CoV-2 virus pandemic. One of the crucial steps in the mechanism of action of RDV is its incorporation into the growing RNA strand. RDV, an adenosine analogue, forms Watson-Crick (WC) type hydrogen bonds with uridine in the complementary strand and the strength of this interaction will control efficacy of RDV. While there is a plethora of structural and energetic information available about WC H-bonds in natural base pairs, the interaction of RDV with uridine has not been studied yet at the atomic level. In this article, we aim to bridge this gap, to understand RDV and its hydrogen bonding interactions, by employing density functional theory (DFT) at the M06-2X/cc-pVDZ level. The interaction energy, QTAIM analysis, NBO and SAPT2 are performed for RDV, adenosine, and their complex with uridine to gain insights into the nature of hydrogen bonding. The computations show that RDV has similar geometry, energetic, molecular orbitals, and aromaticity as adenosine, suggesting that RDV is an effective adenosine analogue. The important geometrical parameters, such as bond distances and red-shift in the stretching vibrational modes of adenosine, RDV and uridine identify two WC-type H-bonds. The relative strength of these two H-bonds is computed using QTAIM parameters and the computed hydrogen bond energy. Finally, the SAPT2 study is performed at the minima and at non-equilibrium base pair distances to understand the dominant intermolecular physical force. This study, based on a thorough analysis of a variety of computations, suggests that both adenosine and RDV have similar structure, energetic, and hydrogen bonding behaviour.

RNA Secondary Structure Alteration Caused by Single Nucleotide Variants.

A point mutation in coding RNA can cause not only an amino acid substitution but also a dynamic change of RNA secondary structure, leading to a dysfunctional RNA. Although in silico structure prediction has been used to detect structure-disrupting point mutations known as riboSNitches, exhaustive simulation of long RNAs is needed to detect a significant enrichment or depletion of riboSNitches in functional RNAs. Here, we have developed a novel algorithm Radiam (RNA secondary structure Analysis with Deletion, Insertion, And substitution Mutations) for a comprehensive riboSNitch analysis of long RNAs. Radiam is based on the ParasoR framework, which efficiently computes local RNA secondary structures for long RNAs. ParasoR can compute a variety of structure scores over globally consistent structures with maximal span constraints for the base pair distance. Using the reusable structure database made by ParasoR, Radiam performs an efficient recomputation of the secondary structures for mutated sequences. An exhaustive simulation of Radiam is expected to find reliable riboSNitch candidates on long RNAs by evaluating their statistical significance in terms of the change of local structure stability.

Effect of COF Presence on DNA Molecular Interactions: A QM/MM and MD Simulations Study

AbstractFour models of DNA including A‐DNA, B‐DNA, Triple helix‐DNA (T‐DNA), and Z‐DNA along with a COF molecule were prepared. Molecular dynamics simulations were performed on all DNAs and their complex with COF (embedded DNAs in the central hole of COF). Comprehensive analyses such as Base pair distance, hydrogen bonding, Van der Waals, and electrostatic interaction numbers were carried out to investigate the effect of COF molecule on DNA intermolecular interactions. Furthermore, quantum‐mechanics studies were performed to explore the accuracy of intermolecular and intramolecular interactions. The results obtained based on promolecular density in two selected base pairs. Noncovalent interaction (NCI) analysis to investigate the strength of hydrogen bonds, Van der Waals interactions, and steric effect was done. Density Overlap Regions Indicator (DORI) analysis was accomplished to study the accuracy of π‐π stacking interactions between adjacent bases. δg functions were evaluated to analyze the strength of chemical bonds, hydrogen bonds and also the steric effect. The average distance between O…H, N…H, and H…O that are contributing in H‐bonding are ∼1.88, 1.97, and 1.95 Å in A‐DNA, respectively. Also, the average number of H‐bonding numbers in A‐DNA calculated to be 14.43 and 13.04 in pure and complex form. All the achieved results showed that designed COF did not make any changes in DNA structures, but in some cases, had some effects on the interactions of DNAs.

Qtlizer: comprehensive QTL annotation of GWAS results

Exploration of genetic variant-to-gene relationships by quantitative trait loci such as expression QTLs is a frequently used tool in genome-wide association studies. However, the wide range of public QTL databases and the lack of batch annotation features complicate a comprehensive annotation of GWAS results. In this work, we introduce the tool “Qtlizer” for annotating lists of variants in human with associated changes in gene expression and protein abundance using an integrated database of published QTLs. Features include incorporation of variants in linkage disequilibrium and reverse search by gene names. Analyzing the database for base pair distances between best significant eQTLs and their affected genes suggests that the commonly used cis-distance limit of 1,000,000 base pairs might be too restrictive, implicating a substantial amount of wrongly and yet undetected eQTLs. We also ranked genes with respect to the maximum number of tissue-specific eQTL studies in which a most significant eQTL signal was consistent. For the top 100 genes we observed the strongest enrichment with housekeeping genes (P = 2 × 10–6) and with the 10% highest expressed genes (P = 0.005) after grouping eQTLs by r2 > 0.95, underlining the relevance of LD information in eQTL analyses. Qtlizer can be accessed via https://genehopper.de/qtlizer or by using the respective Bioconductor R-package (https://doi.org/10.18129/B9.bioc.Qtlizer).

GVCHAP: A Computing Pipeline for Genomic Prediction and Variance Component Estimation Using Haplotypes and SNP Markers.

Haplotype prediction models open many possibilities to improve the accuracy of genomic selection but require more data processing and computing time than single-SNP prediction models. To facilitate haplotype analysis for genomic prediction and estimation using structural and functional genomic information, we developed a computing pipeline to implement haplotype analysis with capabilities for preparation of input data for haplotype analysis, genomic prediction and estimation using GVCHAP, and analysis of GVCHAP results. Data preparation includes utility programs for haplotype imputing; defining haplotype blocks by a fixed number of SNPs, a fixed distance in base pairs per block, or user defined block lengths based on structural or functional genomic information or a mixture of both types of information; and defining haplotype genotypes within each haplotype block. GVCHAP is the main program for genomic prediction and estimation, calculates GREML (genomic restricted maximum likelihood) estimates of variance components and heritabilities, and calculates GBLUP (genomic best linear unbiased prediction) for additive and dominance values of single SNPs as well as additive values of haplotypes with reliability estimates for training and validation populations. A two-step strategy and a method of multi-node processing are implemented to remove the computing bottleneck due to the creation of genomic relationship matrices for large samples. The analysis of GVCHAP results includes calculation of observed prediction accuracies from validation studies and preparation of input files for graphical visualization of heritability estimates of haplotype blocks as well as estimates of SNP effects and heritabilities. The entire pipeline provides an efficient and versatile computing tool for identifying the most accurate haplotype model among many candidate haplotype models utilizing structural and functional genomic information for genomic selection.

DNA Multilayers with Mono-, Hetero-, and Mixed-Type Plasmonic Nanoparticles for Broadband Absorption and Energy Storage.

DNA incorporated with functional materials has led to development of hybrids with different functionalities. Among the functional materials, metal nanoparticles such as Au, Ag, and Cu (also known as plasmonic nanoparticles [PNPs]), which can exhibit surface plasmon resonance, are good candidates to fabricate useful optoelectronic devices and sensors. Here, we constructed PNP-assorted DNA (PNP-DNA) layers with mono-, hetero-, and mixed-type PNPs formed by successive spin-coating to obtain the required number of layers. Further, structural analysis of PNP-DNA was performed by scanning electron microscopy (SEM), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). The optical evaluation was carried out by Raman, UV-visible, and photoluminescence (PL) spectroscopies followed by measurement of capacitance. Cross-sectional SEM images of DNA single, DNA triple, and PNP-DNA triple layers indicated their thicknesses (i.e., 90, 280, and 395 nm, respectively), while the base pair distance of double helixes (∼0.4 nm) for the PNP-DNA multilayers was measured by XRD. The presence of Ag, Au, and Cu PNPs was confirmed by existence of spin-orbit coupling in the corresponding XPS spectra. The addition of PNPs in DNA multilayers caused significant enhancement in the intensities of Raman bands (especially in the range of 1200-1850 cm-1) due to Raman resonance. UV-vis absorption and PL demonstrated stacking-order-dependent and layer-dependent light absorption and energy transfer (observed as quenching of fluorescence between PNPs and DNA), respectively. We observed n-type semiconducting behavior with a relatively higher dielectric constant for a PNP-assorted DNA single layer at a low frequency of 5 kHz. The dielectric constants of all samples decreased exponentially with increased frequency. Upon addition of PNPs, enhancement in the dielectric constant as well as capacitance was noted. Consequently, the simple fabrication method used in this study can be adopted to construct various nanomaterial-assorted DNA multilayers whose specific functionalities may be controlled with high efficiency.

A Boltzmann Sampler for 1-Pairs with Double Filtration.

Recently, a framework considering RNA sequences and their RNA secondary structures as pairs led to some information-theoretic perspectives on how the semantics encoded in RNA sequences can be inferred. This pairing arises naturally from the energy model of RNA secondary structures. Fixing the sequence in the pairing produces the RNA energy landscape, whose partition function was discovered by McCaskill. Dually, fixing the structure induces the energy landscape of sequences. The latter has been considered originally for designing more efficient inverse folding algorithms and subsequently enhanced by facilitating the sampling of sequences. We present here a partition function of sequence/structure pairs, with endowed Hamming distance and base pair distance filtration. This partition function is an augmentation of the previous mentioned (dual) partition function. We develop an efficient dynamic programming routine to recursively compute the partition function with this double filtration. Our framework is capable of dealing with RNA secondary structures as well as 1-structures, where a 1-structure is an RNA pseudoknot structure consisting of "building blocks" of genus 0 or 1. In particular, 0-structures, consisting of only "building blocks" of genus 0, are exactly RNA secondary structures. The time complexity for calculating the partition function of 1-pairs, that is, sequence/structure pairs where the structures are 1-structures, is O(h3b3n6), where h, b, n denote the Hamming distance, base pair distance, and sequence length, respectively. The time complexity for the partition function of 0-pairs is O(h2b2n3).

End-to-end distance and contour length distribution functions of DNA helices.

I present a computational method to evaluate the end-to-end and the contour length distribution functions of short DNA molecules described by a mesoscopic Hamiltonian. The method generates a large statistical ensemble of possible configurations for each dimer in the sequence, selects the global equilibrium twist conformation for the molecule, and determines the average base pair distances along the molecule backbone. Integrating over the base pair radial and angular fluctuations, I derive the room temperature distribution functions as a function of the sequence length. The obtained values for the most probable end-to-end distance and contour length distance, providing a measure of the global molecule size, are used to examine the DNA flexibility at short length scales. It is found that, also in molecules with less than ∼60 base pairs, coiled configurations maintain a large statistical weight and, consistently, the persistence lengths may be much smaller than in kilo-base DNA.

A comparative study of sequence- and structure-based features of small RNAs and other RNAs of bacteria

ABSTRACTSmall RNAs (sRNAs) in bacteria have emerged as key players in transcriptional and post-transcriptional regulation of gene expression. Here, we present a statistical analysis of different sequence- and structure-related features of bacterial sRNAs to identify the descriptors that could discriminate sRNAs from other bacterial RNAs. We investigated a comprehensive and heterogeneous collection of 816 sRNAs, identified by northern blotting across 33 bacterial species and compared their various features with other classes of bacterial RNAs, such as tRNAs, rRNAs and mRNAs. We observed that sRNAs differed significantly from the rest with respect to G+C composition, normalized minimum free energy of folding, motif frequency and several RNA-folding parameters like base-pairing propensity, Shannon entropy and base-pair distance. Based on the selected features, we developed a predictive model using Random Forests (RF) method to classify the above four classes of RNAs. Our model displayed an overall predictive accuracy of 89.5%. These findings would help to differentiate bacterial sRNAs from other RNAs and further promote prediction of novel sRNAs in different bacterial species.

Abstract 13: Chromatin unfolding small molecules as a novel type of anticancer agents

Abstract Although targeted therapy was the major focus of anti-cancer drug development, recently revealed enormous heterogeneity of tumors planted a seed of doubt in it as a potential cure for cancer. Very few universal cancer targets are known and they lack cancer specificity. DNA is one of this sort, but activity of drugs targeting DNA was traditionally attributed to their ability to block DNA replication and cause DNA damage with a plethora of harmful long lasting effects in normal cells. We have found that reversible binding of DNA by non-DNA damaging small molecules, curaxins, has strong anticancer effect in different preclinical models without deleterious consequences associated with DNA damage (REF). In this study we explained the mechanism of activity of curaxin clinical lead, CBL0137, through alteration of chromatin organization in tumor cells. Intercalation of the curaxin carbazole moiety between base pairs and DNA major and minor groove binding with curaxin side chains cause an increase in inter base pair distance and untwisting of the double helix (~18o). Such alteration of DNA helical shape leads to decreased nucleosome stability and chromatin opening, creating sites for the high affinity binding of histone chaperone complex FACT. We named this phenomenon “chromatin trapping of FACT” or c-trapping. Consequences of C-trapping are much more deleterious for tumor, than for normal cells. First, c-trapping is an equivalent of functional inactivation of FACT. FACT is critical for oncogenic transformation and tumor, but not normal cell, viability and growth (REF). FACT is essential for the activity of several transcription factors, such as NF-kappaB, HSF1, MYC etc., with important roles in tumor cell proliferation and survival (REF). Further, deregulation of transcription caused by curaxin-dependent chromatin decondensation leads to upregulation of transcription from heterochromatin. This leads to the formation of double stranded RNAs from centromeric and pericentromeric repetitive elements, which mimics a viral infection and induces an IFN response, a powerful inhibitor of tumor cell growth. Additionally, c-trapping of FACT leads to casein kinase 2 mediated phosphorylation and activation of wild type p53 leading to p53-dependent death of cells. Thus non-DNA damaging DNA binding small molecules compromise cancer cell viability via alteration of nucleosome stability and chromatin organization. This is a novel mechanism of anti-cancer activity of small molecules with broad applicability to different types of cancer while lacking the harmful effects of DNA damaging chemotherapy. Citation Format: Katerina V. Gurova. Chromatin unfolding small molecules as a novel type of anticancer agents [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 13. doi:10.1158/1538-7445.AM2017-13

Computational Evaluation of Nucleotide Insertion Opposite Expanded and Widened DNA by the Translesion Synthesis Polymerase Dpo4.

Expanded (x) and widened (y) deoxyribose nucleic acids (DNA) have an extra benzene ring incorporated either horizontally (xDNA) or vertically (yDNA) between a natural pyrimidine base and the deoxyribose, or between the 5- and 6-membered rings of a natural purine. Far-reaching applications for (x,y)DNA include nucleic acid probes and extending the natural genetic code. Since modified nucleobases must encode information that can be passed to the next generation in order to be a useful extension of the genetic code, the ability of translesion (bypass) polymerases to replicate modified bases is an active area of research. The common model bypass polymerase DNA polymerase IV (Dpo4) has been previously shown to successfully replicate and extend past a single modified nucleobase on a template DNA strand. In the current study, molecular dynamics (MD) simulations are used to evaluate the accommodation of expanded/widened nucleobases in the Dpo4 active site, providing the first structural information on the replication of (x,y)DNA. Our results indicate that the Dpo4 catalytic (palm) domain is not significantly impacted by the (x,y)DNA bases. Instead, the template strand is displaced to accommodate the increased C1’–C1’ base-pair distance. The structural insights unveiled in the present work not only increase our fundamental understanding of Dpo4 replication, but also reveal the process by which Dpo4 replicates (x,y)DNA, and thereby will contribute to the optimization of high fidelity and efficient polymerases for the replication of modified nucleobases.

Base pair distance analysis in single DNA molecule by direct stochastic optical reconstruction microscopy

Abstract Precise fluorescence imaging of single λ-DNA molecules for base pair distance analysis requires a super-resolution technique, as these distances are on the order of diffraction limit. Individual λ-DNA molecules intercalated with the fluorescent dye YOYO-1 were investigated at subdiffraction spatial resolution by direct stochastic optical reconstruction microscopy (dSTORM). Various dye-to-DNA base pair ratios were imaged by photoswitching YOYO-1 between the fluorescent state and the dark state using two laser sources. The acquired images were reconstructed into a super-resolution image by applying Gaussian fitting to the centroid of the point spread function. By measuring the distances between localized fluorophores, the base pair distances in single DNA molecules for dye-to-DNA base pair ratios of 1:50, 1:100, and 1:500 were calculated to be 17.1 ± 0.8 nm, 34.3 ± 2.2 nm, and 170.3 ± 8.1 nm, respectively, which were in agreement with theoretical values. These results demonstrate that intercalating dye in a single DNA molecule can be photoswitched without the use of an activator fluorophore, and that super-localization precision at a spatial resolution of ∼17 nm was experimentally achieved.

Computational prediction of miRNAs and their targets in Phaseolus vulgaris using simple sequence repeat signatures.

BackgroundMicroRNAs (miRNAs) are endogenous, noncoding, short RNAs directly involved in regulating gene expression at the post-transcriptional level. In spite of immense importance, limited information of P. vulgaris miRNAs and their expression patterns prompted us to identify new miRNAs in P. vulgaris by computational methods. Besides conventional approaches, we have used the simple sequence repeat (SSR) signatures as one of the prediction parameter. Moreover, for all other parameters including normalized Shannon entropy, normalized base pairing index and normalized base-pair distance, instead of taking a fixed cut-off value, we have used 99 % probability range derived from the available data.ResultsWe have identified 208 mature miRNAs in P. vulgaris belonging to 118 families, of which 201 are novel. 97 of the predicted miRNAs in P. vulgaris were validated with the sequencing data obtained from the small RNA sequencing of P. vulgaris. Randomly selected predicted miRNAs were also validated using qRT-PCR. A total of 1305 target sequences were identified for 130 predicted miRNAs. Using 80 % sequence identity cut-off, proteins coded by 563 targets were identified. The computational method developed in this study was also validated by predicting 229 miRNAs of A. thaliana and 462 miRNAs of G. max, of which 213 for A. thaliana and 397 for G. max are existing in miRBase 20.ConclusionsThere is no universal SSR that is conserved among all precursors of Viridiplantae, but conserved SSR exists within a miRNA family and is used as a signature in our prediction method. Prediction of known miRNAs of A. thaliana and G. max validates the accuracy of our method. Our findings will contribute to the present knowledge of miRNAs and their targets in P. vulgaris. This computational method can be applied to any species of Viridiplantae for the successful prediction of miRNAs and their targets.Electronic supplementary materialThe online version of this article (doi:10.1186/s12870-015-0516-3) contains supplementary material, which is available to authorized users.

Fast, approximate kinetics of RNA folding.

In this article, we introduce the software suite Hermes, which provides fast, novel algorithms for RNA secondary structure kinetics. Using the fast Fourier transform to efficiently compute the Boltzmann probability that a secondary structure S of a given RNA sequence has base pair distance x (resp. y) from reference structure A (resp. B), Hermes computes the exact kinetics of folding from A to B in this coarse-grained model. In particular, Hermes computes the mean first passage time from the transition probability matrix by using matrix inversion, and also computes the equilibrium time from the rate matrix by using spectral decomposition. Due to the model granularity and the speed of Hermes, it is capable of determining secondary structure refolding kinetics for large RNA sequences, beyond the range of other methods. Comparative benchmarking of Hermes with other methods indicates that Hermes provides refolding kinetics of accuracy suitable for use in the computational design of RNA, an important area of synthetic biology. Source code and documentation for Hermes are available.

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.

RNA folding pathways and kinetics using 2D energy landscapes

RNA folding pathways play an important role in various biological processes, such as (i) the hok/sok (host-killing/suppression of killing) system in E. coli to check for sufficient plasmid copy number, (ii) the conformational switch in spliced leader (SL) RNA from Leptomonas collosoma, which controls trans splicing of a portion of the '5 exon, and (iii) riboswitches--portions of the 5' untranslated region of messenger RNA that regulate genes by allostery. Since RNA folding pathways are determined by the energy landscape, we describe a novel algorithm, FFTbor2D, which computes the 2D projection of the energy landscape for a given RNA sequence. Given two metastable secondary structures A, B for a given RNA sequence, FFTbor2D computes the Boltzmann probability p(x, y) = Z(x,y)/Z that a secondary structure has base pair distance x from A and distance y from B. Using polynomial interpolationwith the fast Fourier transform,we compute p(x, y) in O(n(5)) time and O(n(2)) space, which is an improvement over an earlier method, which runs in O(n(7)) time and O(n(4)) space. FFTbor2D has potential applications in synthetic biology, where one might wish to design bistable switches having target metastable structures A, B with favorable pathway kinetics. By inverting the transition probability matrix determined from FFTbor2D output, we show that L. collosoma spliced leader RNA has larger mean first passage time from A to B on the 2D energy landscape, than 97.145% of 20,000 sequences, each having metastable structures A, B. Source code and binaries are freely available for download at http://bioinformatics.bc.edu/clotelab/FFTbor2D. The program FFTbor2D is implemented in C++, with optional OpenMP parallelization primitives.

Effect of Axial Ligand on the Binding Mode of M-Meso-Tetrakis(N-Methylpyridinium-4-Yl)Porphyrin to DNA and their Efficiency as an Acceptor in DNA-Mediated Energy Transfer

The binding modes of cationic porphyrins, namely M-meso-tetrakis(N-methylpyridinium-4-yl)porphyrin (MTMPyP, where M=free base, Cu(II), Ni(II), Co(III), Mn(III), V(IV)=O and Ti(IV)=O), to native DNA were systematically investigated by polarized light spectroscopies. At low [porphyrin]/[DNA] ratio, planar porphyrins including TMPyP, CuTMPyP and NiTMPyP exhibited intercalative binding mode. In the intercalation pocket, the molecular plane of porphyrin is skewed to a large extent. As the mixing ratio was increased the coupling of the electric transition moments of the intercalated porphyrins was observed. Coupling can occur between the porphyrins when they are separated at least two DNA base. The porphyrins with axial ligands, namely VOTMPyP, TiOTMPyP, MnTMPyP and CoTMPyP bind to the exterior of the DNA at a low [porphyrin]/[DNA] ratio. The angle of one the two electric transitions of the porphyrin is in the range of 56°∼59°, while the other is in the range of 59°∼65°. Increasing the porphyrin density resulted in the appearance of an interaction between the bound porphyrins. All porphyrins were able to quench the fluorescence of intercalated ethidium. The mechanism behind the energy transfer is, at least in part, the Forster type resonance energy transfer (FRET). The minimum distance in base pairs between ethidium and porphyrin required to permit the excited ethidium to emit a photon was the longest for CoTMPyP being 17.6 base-pairs and was the shortest for CuTMPyP and NiTMPyP at 8.0 base-pairs. The variation in the distance was almost proportional to the extent of the spectral overlap, the common area under emission spectrum of ethidium and absorption spectrum of porphyrin, supporting the FRET mechanism, while the effect of the orientation factor which was considered by relative binding geometry was limited.

Maximum expected accuracy structural neighbors of an RNA secondary structure

BackgroundSince RNA molecules regulate genes and control alternative splicing by allostery, it is important to develop algorithms to predict RNA conformational switches. Some tools, such as paRNAss, RNAshapes and RNAbor, can be used to predict potential conformational switches; nevertheless, no existent tool can detect general (i.e., not family specific) entire riboswitches (both aptamer and expression platform) with accuracy. Thus, the development of additional algorithms to detect conformational switches seems important, especially since the difference in free energy between the two metastable secondary structures may be as large as 15-20 kcal/mol. It has recently emerged that RNA secondary structure can be more accurately predicted by computing the maximum expected accuracy (MEA) structure, rather than the minimum free energy (MFE) structure.ResultsGiven an arbitrary RNA secondary structure S0 for an RNA nucleotide sequence a = a1,..., an, we say that another secondary structure S of a is a k-neighbor of S0, if the base pair distance between S0 and S is k. In this paper, we prove that the Boltzmann probability of all k-neighbors of the minimum free energy structure S0 can be approximated with accuracy ε and confidence 1 - p, simultaneously for all 0 ≤ k < K, by a relative frequency count over N sampled structures, provided that , where Φ(z) is the cumulative distribution function (CDF) for the standard normal distribution. We go on to describe the algorithm RNAborMEA, which for an arbitrary initial structure S0 and for all values 0 ≤ k < K, computes the secondary structure MEA(k), having maximum expected accuracy over all k-neighbors of S0. Computation time is O(n3 · K2), and memory requirements are O(n2 · K). We analyze a sample TPP riboswitch, and apply our algorithm to the class of purine riboswitches.ConclusionsThe approximation of RNAbor by sampling, with rigorous bound on accuracy, together with the computation of maximum expected accuracy k-neighbors by RNAborMEA, provide additional tools toward conformational switch detection. Results from RNAborMEA are quite distinct from other tools, such as RNAbor, RNAshapes and paRNAss, hence may provide orthogonal information when looking for suboptimal structures or conformational switches. Source code for RNAborMEA can be downloaded from http://sourceforge.net/projects/rnabormea/ or http://bioinformatics.bc.edu/clotelab/RNAborMEA/.