Orderly aligned manganese-based nanotube arrays with controllable secondary structures

Abstract RNA molecules play crucial roles in various biological processes. Their three-dimensional configurations determine the functions and, in turn, influences the interaction with other molecules. RNAs and their interaction structures, the so-called RNA–RNA interactions, can be abstracted in terms of secondary structures, i.e., a list of the nucleotide bases paired by hydrogen bonding within its nucleotide sequence. Each secondary structure, in turn, can be abstracted into cores and shadows. Both are determined by collapsing nucleotides and arcs properly. We formalize all of these abstractions as arc diagrams, whose arcs determine loops. A secondary structure, represented by an arc diagram, is pseudoknot-free if its arc diagram does not present any crossing among arcs otherwise, it is said pseudoknotted. In this study, we face the problem of identifying a given structural pattern into secondary structures or the associated cores or shadow of both RNAs and RNA–RNA interactions, characterized by arbitrary pseudoknots. These abstractions are mapped into a matrix, whose elements represent the relations among loops. Therefore, we face the problem of taking advantage of matrices and submatrices. The algorithms, implemented in Python, work in polynomial time. We test our approach on a set of 16S ribosomal RNAs with inhibitors of Thermus thermophilus, and we quantify the structural effect of the inhibitors.

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Use of synchrotron-based FTIR microspectroscopy to determine protein secondary structures of raw and heat-treated brown and golden flaxseeds: A novel approach

Canadian Journal of Animal Science ◽

10.4141/a05-004 ◽

2005 ◽

Vol 85 (4) ◽

pp. 437-448 ◽

Cited By ~ 21

Author(s):

P. Yu ◽

J. J. McKinnon ◽

H. W. Soita ◽

C. R. Christensen ◽

D. A. Christensen

Keyword(s):

Secondary Structure ◽

Matrix Protein ◽

Protein Secondary Structure ◽

Secondary Structures ◽

Heat Processing ◽

Lower Percentage ◽

Protein Secondary Structures ◽

Novel Approach ◽

Α Helix ◽

Β Sheet

The objectives of the study were to use synchrotron Fourier transform infrared microspectroscopy (S-FTIR) as a novel approach to: (1) reveal ultra-structural chemical features of protein secondary structures of flaxseed tissues affected by variety (golden and brown) and heat processing (raw and roasted), and (2) quantify protein secondary structures using Gaussian and Lorentzian methods of multi-component peak modeling. By using multi-component peak modeling at protein amide I region of 1700–1620 cm-1, the results showed that the golden flaxseed contained relatively higher percentage of α-helix (47.1 vs. 36.9%), lower percentage of β-sheet (37.2 vs. 46.3%) and higher (P < 0.05) ratio of α-helix to β-sheet than the brown flaxseed (1.3 vs. 0.8). The roasting reduced (P < 0.05) percentage of α-helix (from 47.1 to 36.1%), increased percentage of β-sheet (from 37.2 to 49.8%) and reduced α-helix to β-sheet ratio (1.3 to 0.7) of the golden flaxseed tissues. However, the roasting did not affect percentage and ratio of α-helix and β-sheet in the brown flaxseed tissue. No significant differences were found in quantification of protein secondary structures between Gaussian and Lorentzian methods. These results demonstrate the potential of highly spatially resolved S-FTIR to localize relatively pure protein in the tissue and reveal protein secondary structures at a cellular level. The results indicated relative differences in protein secondary structures between flaxseed varieties and differences in sensitivities of protein secondary structure to the heat processing. Further study is needed to understand the relationship between protein secondary structure and protein digestion and utilization of flaxseed and to investigate whether the changes in the relative amounts of protein secondary structures are primarily responsible for differences in protein availability. Key words: Synchrotron, FTIR microspectrosopy, flaxseeds, intrinsic structural matrix, protein secondary structures, protein nutritive value

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Amount of RNA secondary structure required to induce an alternative splice.

Molecular and Cellular Biology ◽

10.1128/mcb.7.9.3194 ◽

1987 ◽

Vol 7 (9) ◽

pp. 3194-3198 ◽

Cited By ~ 63

Author(s):

D Solnick ◽

S I Lee

Keyword(s):

Alternative Splicing ◽

Secondary Structure ◽

Alternative Splice ◽

Rna Secondary Structure ◽

Secondary Structures ◽

Splice Sites ◽

Perfect Complementarity ◽

Set Up

We set up an alternative splicing system in vitro in which the relative amounts of two spliced RNAs, one containing and the other lacking a particular exon, were directly proportional to the length of an inverted repeat inserted into the flanking introns. We then used the system to measure the effect of intramolecular complementarity on alternative splicing in vivo. We found that an alternative splice was induced in vivo only when the introns contained more than approximately 50 nucleotides of perfect complementarity, that is, only when the secondary structure was much more stable than most if not all possible secondary structures in natural mRNA precursors. We showed further that intron insertions containing long complements to splice sites and a branch point inhibited splicing in vitro but not in vivo. These results raise the possibility that in cells most pre-mRNA secondary structures either are not maintained long enough to influence splicing choices, or never form at all.

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RNA secondary structure prediction using deep learning with thermodynamic integration

10.1101/2020.08.10.244442 ◽

2020 ◽

Author(s):

Kengo Sato ◽

Manato Akiyama ◽

Yasubumi Sakakibara

Keyword(s):

Deep Learning ◽

Secondary Structure ◽

Structure Prediction ◽

Rna Secondary Structure ◽

Secondary Structure Prediction ◽

Secondary Structures ◽

Thermodynamic Integration ◽

Rna Secondary Structure Prediction ◽

Rna Secondary Structures ◽

Non Coding Rnas

RNA secondary structure prediction is one of the key technologies for revealing the essential roles of functional non-coding RNAs. Although machine learning-based rich-parametrized models have achieved extremely high performance in terms of prediction accuracy, the risk of overfitting for such models has been reported. In this work, we propose a new algorithm for predicting RNA secondary structures that uses deep learning with thermodynamic integration, thereby enabling robust predictions. Similar to our previous work, the folding scores, which are computed by a deep neural network, are integrated with traditional thermodynamic parameters to enable robust predictions. We also propose thermodynamic regularization for training our model without overfitting it to the training data. Our algorithm (MXfold2) achieved the most robust and accurate predictions in computational experiments designed for newly discovered non-coding RNAs, with significant 2–10 % improvements over our previous algorithm (MXfold) and standard algorithms for predicting RNA secondary structures in terms of F-value.

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Three-Dimensional Graph Matching to Identify Secondary Structure Correspondence of Medium-Resolution Cryo-EM Density Maps

Biomolecules ◽

10.3390/biom11121773 ◽

2021 ◽

Vol 11 (12) ◽

pp. 1773

Author(s):

Bahareh Behkamal ◽

Mahmoud Naghibzadeh ◽

Mohammad Reza Saberi ◽

Zeinab Amiri Tehranizadeh ◽

Andrea Pagnani ◽

...

Keyword(s):

Secondary Structure ◽

Graph Matching ◽

Protein Complexes ◽

Three Dimensional ◽

Protein Structure Determination ◽

Secondary Structures ◽

Computational Method ◽

Target Sequence ◽

Matching Problem ◽

Medium Resolution

Cryo-electron microscopy (cryo-EM) is a structural technique that has played a significant role in protein structure determination in recent years. Compared to the traditional methods of X-ray crystallography and NMR spectroscopy, cryo-EM is capable of producing images of much larger protein complexes. However, cryo-EM reconstructions are limited to medium-resolution (~4–10 Å) for some cases. At this resolution range, a cryo-EM density map can hardly be used to directly determine the structure of proteins at atomic level resolutions, or even at their amino acid residue backbones. At such a resolution, only the position and orientation of secondary structure elements (SSEs) such as α-helices and β-sheets are observable. Consequently, finding the mapping of the secondary structures of the modeled structure (SSEs-A) to the cryo-EM map (SSEs-C) is one of the primary concerns in cryo-EM modeling. To address this issue, this study proposes a novel automatic computational method to identify SSEs correspondence in three-dimensional (3D) space. Initially, through a modeling of the target sequence with the aid of extracting highly reliable features from a generated 3D model and map, the SSEs matching problem is formulated as a 3D vector matching problem. Afterward, the 3D vector matching problem is transformed into a 3D graph matching problem. Finally, a similarity-based voting algorithm combined with the principle of least conflict (PLC) concept is developed to obtain the SSEs correspondence. To evaluate the accuracy of the method, a testing set of 25 experimental and simulated maps with a maximum of 65 SSEs is selected. Comparative studies are also conducted to demonstrate the superiority of the proposed method over some state-of-the-art techniques. The results demonstrate that the method is efficient, robust, and works well in the presence of errors in the predicted secondary structures of the cryo-EM images.

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Characterization and expression of a spliced leader RNA in the parasitic nematode Ascaris lumbricoides var. suum

Molecular and Cellular Biology ◽

10.1128/mcb.9.8.3543-3547.1989 ◽

1989 ◽

Vol 9 (8) ◽

pp. 3543-3547

Author(s):

T W Nilsen ◽

J Shambaugh ◽

J Denker ◽

G Chubb ◽

C Faser ◽

...

Keyword(s):

Caenorhabditis Elegans ◽

Secondary Structure ◽

Rna Polymerase ◽

Binding Site ◽

Rna Polymerase Ii ◽

Ascaris Lumbricoides ◽

Parasitic Nematode ◽

Secondary Structures ◽

Spliced Leader ◽

C Elegans

The parasitic nematode Ascaris spp. contains a 22-nucleotide spliced-leader (SL) sequence identical to the trans-SL previously described in Caenorhabditis elegans and other nematodes. The SL comprises the first 22 nucleotides of a approximately 110-base RNA and is transcribed by RNA polymerase II. The SL RNA contains a trimethylguanosine cap and a consensus Sm binding site. Furthermore, the Ascaris SL RNA has the potential to adopt a secondary structure which is nearly identical to potential secondary structures of similar SL RNAs in C. elegans and Brugia malayi.

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Relationship of Secondary Structures and Wear Resistance of Antifriction Aluminum Alloys for Journal Bearings from the Point of View of Self-Organization During Friction

Entropy ◽

10.3390/e21111048 ◽

2019 ◽

Vol 21 (11) ◽

pp. 1048 ◽

Cited By ~ 2

Author(s):

Gershman ◽

Mironov ◽

Podrabinnik ◽

Kuznetsova ◽

Gershman ◽

...

Keyword(s):

Secondary Structure ◽

Organization Theory ◽

Secondary Structures ◽

Point Of View ◽

Self Organization ◽

Friction Surfaces ◽

Relationship Of ◽

The Relationship ◽

Secondary Structure Composition ◽

Antifriction Alloys

The paper investigates the relationship between the tribological properties/compositions of new aluminum antifriction alloys and compositions of the secondary structures formed on their friction surfaces. Eight alloys with various compositions have been analyzed. The elemental compositions of the secondary structures on their friction surfaces have been determined. The relationship between the alloy secondary structure compositions with wear rate has been found. An attempt has been made to determine the secondary structure composition patterns based on the non-equilibrium thermodynamics and self-organization theory.

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Base-pair ambiguity and the kinetics of RNA folding

BMC Bioinformatics ◽

10.1186/s12859-019-3303-6 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 2

Author(s):

Guangyao Zhou ◽

Jackson Loper ◽

Stuart Geman

Keyword(s):

Free Energy ◽

Secondary Structure ◽

Thermodynamic Equilibrium ◽

Secondary Structures ◽

Minimum Free Energy ◽

Nucleotide Sequences ◽

Biologically Relevant ◽

Rna Molecules ◽

Comparative Structure ◽

Kinetic Traps

Abstract Background A folding RNA molecule encounters multiple opportunities to form non-native yet energetically favorable pairings of nucleotide sequences. Given this forbidding free-energy landscape, mechanisms have evolved that contribute to a directed and efficient folding process, including catalytic proteins and error-detecting chaperones. Among structural RNA molecules we make a distinction between “bound” molecules, which are active as part of ribonucleoprotein (RNP) complexes, and “unbound,” with physiological functions performed without necessarily being bound in RNP complexes. We hypothesized that unbound molecules, lacking the partnering structure of a protein, would be more vulnerable than bound molecules to kinetic traps that compete with native stem structures. We defined an “ambiguity index”—a normalized function of the primary and secondary structure of an individual molecule that measures the number of kinetic traps available to nucleotide sequences that are paired in the native structure, presuming that unbound molecules would have lower indexes. The ambiguity index depends on the purported secondary structure, and was computed under both the comparative (“gold standard”) and an equilibrium-based prediction which approximates the minimum free energy (MFE) structure. Arguing that kinetically accessible metastable structures might be more biologically relevant than thermodynamic equilibrium structures, we also hypothesized that MFE-derived ambiguities would be less effective in separating bound and unbound molecules. Results We have introduced an intuitive and easily computed function of primary and secondary structures that measures the availability of complementary sequences that could disrupt the formation of native stems on a given molecule—an ambiguity index. Using comparative secondary structures, the ambiguity index is systematically smaller among unbound than bound molecules, as expected. Furthermore, the effect is lost when the presumably more accurate comparative structure is replaced instead by the MFE structure. Conclusions A statistical analysis of the relationship between the primary and secondary structures of non-coding RNA molecules suggests that stem-disrupting kinetic traps are substantially less prevalent in molecules not participating in RNP complexes. In that this distinction is apparent under the comparative but not the MFE secondary structure, the results highlight a possible deficiency in structure predictions when based upon assumptions of thermodynamic equilibrium.

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Widespread selection for extremely high and low levels of secondary structure in coding sequences across all domains of life

Open Biology ◽

10.1098/rsob.190020 ◽

2019 ◽

Vol 9 (5) ◽

pp. 190020 ◽

Cited By ~ 3

Author(s):

Daniel Gebert ◽

Julia Jehn ◽

David Rosenkranz

Keyword(s):

Secondary Structure ◽

Gc Content ◽

Secondary Structures ◽

Coding Sequences ◽

Rna Secondary Structures ◽

Synonymous Mutations ◽

Codon Composition ◽

Domains Of Life ◽

Low Levels ◽

Selection For

Codon composition, GC content and local RNA secondary structures can have a profound effect on gene expression, and mutations affecting these parameters, even though they do not alter the protein sequence, are not neutral in terms of selection. Although evidence exists that, in some cases, selection favours more stable RNA secondary structures, we currently lack a concrete idea of how many genes are affected within a species, and whether this is a universal phenomenon in nature. We searched for signs of structural selection in a global manner, analysing a set of 1 million coding sequences from 73 species representing all domains of life, as well as viruses, by means of our newly developed software PACKEIS. We show that codon composition and amino acid identity are main determinants of RNA secondary structure. In addition, we show that the arrangement of synonymous codons within coding sequences is non-random, yielding extremely high, but also extremely low, RNA structuredness significantly more often than expected by chance. Taken together, we demonstrate that selection for high and low levels of secondary structure is a widespread phenomenon. Our results provide another line of evidence that synonymous mutations are less neutral than commonly thought, which is of importance for many evolutionary models.

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Secondary Structural Elements within the 3′ Untranslated Region of Mouse Hepatitis Virus Strain JHM Genomic RNA

Journal of Virology ◽

10.1128/jvi.75.24.12105-12113.2001 ◽

2001 ◽

Vol 75 (24) ◽

pp. 12105-12113 ◽

Cited By ~ 35

Author(s):

Qi Liu ◽

Reed F. Johnson ◽

Julian L. Leibowitz

Keyword(s):

Secondary Structure ◽

Protein Binding ◽

Hepatitis Virus ◽

Mouse Hepatitis Virus ◽

Rna Replication ◽

Secondary Structures ◽

Host Protein ◽

Wild Type ◽

Base Pairing ◽

Stem Loop

ABSTRACT Previously, we characterized two host protein binding elements located within the 3′-terminal 166 nucleotides of the mouse hepatitis virus (MHV) genome and assessed their functions in defective-interfering (DI) RNA replication. To determine the role of RNA secondary structures within these two host protein binding elements in viral replication, we explored the secondary structure of the 3′-terminal 166 nucleotides of the MHV strain JHM genome using limited RNase digestion assays. Our data indicate that multiple stem-loop and hairpin-loop structures exist within this region. Mutant and wild-type DIssEs were employed to test the function of secondary structure elements in DI RNA replication. Three stem structures were chosen as targets for the introduction of transversion mutations designed to destroy base pairing structures. Mutations predicted to destroy the base pairing of nucleotides 142 to 136 with nucleotides 68 to 74 exhibited a deleterious effect on DIssE replication. Destruction of base pairing between positions 96 to 99 and 116 to 113 also decreased DI RNA replication. Mutations interfering with the pairing of nucleotides 67 to 63 with nucleotides 52 to 56 had only minor effects on DIssE replication. The introduction of second complementary mutations which restored the predicted base pairing of positions 142 to 136 with 68 to 74 and nucleotides 96 to 99 with 116 to 113 largely ameliorated defects in replication ability, restoring DI RNA replication to levels comparable to that of wild-type DIssE RNA, suggesting that these secondary structures are important for efficient MHV replication. We also identified a conserved 23-nucleotide stem-loop structure involving nucleotides 142 to 132 and nucleotides 68 to 79. The upstream side of this conserved stem-loop is contained within a host protein binding element (nucleotides 166 to 129).

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