Secondary Structure Model Research Articles

Identification and characterization of RNA binding sites for (p)ppGpp using RNA-DRaCALA.

Ligand-binding RNAs (RNA aptamers) are widespread in the three domains of life, serving as sensors of metabolites and other small molecules. When aptamers are embedded within RNA transcripts as components of riboswitches, they can regulate gene expression upon binding their ligands. Previous methods for biochemical validation of computationally predicted aptamers are not well-suited for rapid screening of large numbers of RNA aptamers. Therefore, we utilized DRaCALA (Differential Radial Capillary Action of Ligand Assay), a technique designed originally to study protein-ligand interactions, to examine RNA-ligand binding, permitting rapid screening of dozens of RNA aptamer candidates concurrently. Using this method, which we call RNA-DRaCALA, we screened 30 ykkC family subtype 2a RNA aptamers that were computationally predicted to bind (p)ppGpp. Most of the aptamers bound both ppGpp and pppGpp, but some strongly favored only ppGpp or pppGpp, and some bound neither. Expansion of the number of biochemically verified sites allowed construction of more accurate secondary structure models and prediction of key features in the aptamers that distinguish a ppGpp from a pppGpp binding site. To demonstrate that the method works with other ligands, we also used RNA DRaCALA to analyze aptamer binding by thiamine pyrophosphate.

한국판 문제적 음란물 소비 척도(PPCS-K)의 타당화 연구

The purpose of this study is to translate and validate the Problematic Pornography Consumption Scale(PPCS; Bőthe et al., 2017). We analyzed 336 Korean adults. We conducted Confirmatory Factor Analysis to test that the original scale factor structure was applied equally to Korean adults. As a result of the analysis, it was confirmed that it was the same hierarchical secondary structure model as the results of the validation study of the PPCS. Subsequently, the reliability, Concurrent validity, convergent validity of the Korean version of the Problematic Pornography Consumption Scale were verified, and all of them showed appropriate levels of results. We conduct Latent Profile Analysis(LPA) to classify latent groups according to the level of problematic pornography consumption. As a result, it was confirmed that it was appropriate to classify the entire sample into three groups. ROC analysis was conducted to identify the high-risk group, and optimal cut-off point for identifying the high-risk group was confirmed as 67 points. Through the results of this study, it was confirmed that the Korean version of the Problematic Pornography Consumption Scale is reliable and valid scale to measure the problematic pornography consumption level of Korean adults. Finally, implications and limitations of this study and suggestions for future research were discussed.

LazySampling and LinearSampling: fast stochastic sampling of RNA secondary structure with applications to SARS-CoV-2.

Many RNAs fold into multiple structures at equilibrium, and there is a need to sample these structures according to their probabilities in the ensemble. The conventional sampling algorithm suffers from two limitations: (i) the sampling phase is slow due to many repeated calculations; and (ii) the end-to-end runtime scales cubically with the sequence length. These issues make it difficult to be applied to long RNAs, such as the full genomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To address these problems, we devise a new sampling algorithm, LazySampling, which eliminates redundant work via on-demand caching. Based on LazySampling, we further derive LinearSampling, an end-to-end linear time sampling algorithm. Benchmarking on nine diverse RNA families, the sampled structures from LinearSampling correlate better with the well-established secondary structures than Vienna RNAsubopt and RNAplfold. More importantly, LinearSampling is orders of magnitude faster than standard tools, being 428× faster (72 s versus 8.6 h) than RNAsubopt on the full genome of SARS-CoV-2 (29 903 nt). The resulting sample landscape correlates well with the experimentally guided secondary structure models, and is closer to the alternative conformations revealed by experimentally driven analysis. Finally, LinearSampling finds 23 regions of 15nt with high accessibilities in the SARS-CoV-2 genome, which are potential targets for COVID-19 diagnostics and therapeutics.

Rational Design of RN15m4 Cathelin Domain-Based Peptides from Siamese Crocodile Cathelicidin Improves Antimicrobial Activity.

Antimicrobial peptides are becoming a new generation of antibiotics due to their therapeutic potential and ability to decrease drug-resistant bacteria development. Cathelicidins are known as effective peptides of vertebrate immunity that play crucial roles in the defensive strategy against pathogens. To improve its potency, the RN15 antibacterial peptide derived from the cathelin domain of Crocodylus siamensis cathelicidin has been modified and its antimicrobial properties investigated. Peptides were derived by template-based and physicochemical designation. The RN15 derivative peptides were predicted through their structure modeling, antimicrobial potency, and peptide-membrane calculation. The antimicrobial and cytotoxic activities of candidate peptides were investigated. Simultaneous consideration of physicochemical characteristics, secondary structure modeling, and the result of antimicrobial peptide tools prediction indicated that RN15m4 peptide was a candidate derivative antimicrobial peptide. The RN15m4 peptide expresses antimicrobial activity against most Gram-positive and Gram-negative bacteria and fungi with a lower minimum inhibition concentration (MIC) than the parent peptide. Besides, the time-killing assay shows that the designed peptide performed its ability to quickly kill bacteria better than the original peptide. Scanning electron microscopy (SEM) displayed the destruction of the bacterial cell membrane caused by the RN15m4 peptide. In addition, the RN15m4 peptide exhibits low hemolytic activity and low cytotoxic activity as good as the template peptide. The RN15m4 peptide performs a range of antimicrobial activities with low cell toxicity. Our study has illustrated the combination approach to peptide design for potent antibiotic peptide discovery.

Characterization of intron 7 to exon 8 of heat shock protein 90-aa1 (hsp90aa1) gene in dominant brown layer chicken using some bioinformatic tools


 HSP90AA1, an isoform of HSP90 has been characterized to indicate it plays important roles in basic cellular events. It is activated in chicken in response to heat stress. This study was aimed at the computational analysis of the biochemical cum structural features and an evolutionary relationship study on the HSP90AA1 gene in Dominant brown layers (DBL) and some selected avian species using bioinformatics tools. ProtParam for physicochemical properties. Scanprosite for post-translational modification sites, Netphos-3.1 for phosphorylation sites, BDM-PUB program for Ubiquitination sites, PDBSUM for Secondary structure and homology modelling with SWISS-model. The findings revealed that intron 7 and exon 8 of HSP90AA1 protein in DBL had a molecular weight of 24681.19Da and an instability index of 27.60, contains N-myristoylation, Protein-kinase-C-phosphorylation and Tyrosine-kinase-phosphorylation site-2 post-translational modification sites, 4-serine and 2-threonine phosphorylation sites and 12-ubiquitination sites. The evolutionary relationship study found Japanese quail to be in a sister branch close to DBL and chicken. Motifs detected in the avian species revealed the gene to be highly conserved. The secondary structure consisted of 16-helices, 3-sheets and 14-strands. The homology modelling was 87.25% sequence identity with human MC-HSP90-alpha. The study elucidates the components and characteristics of HSP90AA1 in DBL in response to heat stress.

Complex and simple translational readthrough signals in pea enation mosaic virus 1 and potato leafroll virus, respectively.

Different essential viral proteins are translated via programmed stop codon readthrough. Pea enation mosaic virus 1 (PEMV1) and potato leafroll virus (PLRV) are related positive-sense RNA plant viruses in the family Solemoviridae, and are type members of the Enamovirus and Polerovirus genera, respectively. Both use translational readthrough to express a C-terminally extended minor capsid protein (CP), termed CP-readthrough domain (CP-RTD), from a viral subgenomic mRNA that is transcribed during infections. Limited incorporation of CP-RTD subunits into virus particles is essential for aphid transmission, however the functional readthrough structures that mediate CP-RTD translation have not yet been defined. Through RNA solution structure probing, RNA secondary structure modeling, site-directed mutagenesis, and functional in vitro and in vivo analyses, we have investigated in detail the readthrough elements and complex structure involved in expression of CP-RTD in PEMV1, and assessed and deduced a comparatively simpler readthrough structure for PLRV. Collectively, this study has (i) generated the first higher-order RNA structural models for readthrough elements in an enamovirus and a polerovirus, (ii) revealed a stark contrast in the complexity of readthrough structures in these two related viruses, (iii) provided compelling experimental evidence for the strict requirement for long-distance RNA-RNA interactions in generating the active readthrough signals, (iv) uncovered what could be considered the most complex readthrough structure reported to date, that for PEMV1, and (v) proposed plausible assembly pathways for the formation of the elaborate PEMV1 and simple PLRV readthrough structures. These findings notably advance our understanding of this essential mode of gene expression in these agriculturally important plant viruses.

Rotavirus RNA chaperone mediates global transcriptome-wide increase in RNA backbone flexibility.

Due to genome segmentation, rotaviruses must co-package eleven distinct genomic RNAs. The packaging is mediated by virus-encoded RNA chaperones, such as the rotavirus NSP2 protein. While the activities of distinct RNA chaperones are well studied on smaller RNAs, little is known about their global effect on the entire viral transcriptome. Here, we used Selective 2′-hydroxyl Acylation Analyzed by Primer Extension and Mutational Profiling (SHAPE-MaP) to examine the secondary structure of the rotavirus transcriptome in the presence of increasing amounts of NSP2. SHAPE-MaP data reveals that despite the well-documented helix-unwinding activity of NSP2 in vitro, its incubation with cognate rotavirus transcripts does not induce a significant change in the SHAPE reactivities. However, a quantitative analysis of mutation rates measured by mutational profiling reveals a global 5-fold rate increase in the presence of NSP2. We demonstrate that the normalization procedure used in deriving SHAPE reactivities from mutation rates can mask an important global effect of an RNA chaperone. Analysis of the mutation rates reveals a larger effect on stems rather than loops. Together, these data provide the first experimentally derived secondary structure model of the rotavirus transcriptome and reveal that NSP2 acts by globally increasing RNA backbone flexibility in a concentration-dependent manner.

Structures, Functions and Therapeutic Potential of Cyclotides

Plants usually produce a large number of secondary metabolite molecules, including antimicrobial peptides that typically interact with membranes of pathogens and kill these. Cysteine is more abundant in plant antimicrobial peptides than other sources. These phytopeptides can be classified into 5–8 distinct groups, based on the length, secondary structure type, number and model of disulphide bridges, and others. Among the different groups of phytopeptides, cyclotides are end-to-end cyclic with a disulphide bridge in the knot fashion. Cyclotide peptides are primarily known for its anti-nematode, anti-mollusk, and anti-trematode action. This review aims to provide detailed insights on cyclotides, from their origin, and structural and functional characterization, to their therapeutic potential, biotechnological application, and future prospective.

Residual Structural Equation Models

The residual variables in a structural equation model can be used to create a secondary structural model which we call the residual structural equation model (RSEM). We describe the maximum-likelihood, weighted least squares and Bayesian estimations for RSEM. The methodology is illustrated with several examples and simulation studies. We discuss the implementation of RSEM in the Mplus software package and provide scripts for the simulation studies. The RSEM framework is utilized to estimate and simplify popular models such as the random intercept cross-lagged panel model (RI-CLPM) and the latent curve model with structured residuals (LCM-SR). We discuss in details RSEM models with categorical observed variables as well as categorical latent variables in the context of mixture modeling.

Wide-Line NMR Melting Diagrams, Their Thermodynamic Interpretation, and Secondary Structure Predictions for A30P and E46K α-Synuclein.

Parkinson’s disease is thought to be caused by aggregation of the intrinsically disordered protein, α-synuclein. Two amyloidogenic variants, A30P, and E46K familial mutants were investigated by wide-line 1H NMR spectrometry as a completion of our earlier work on wild-type and A53T α-synuclein (BokorM. et al. WT and A53T α-synuclein systems: melting diagram and its new interpretation. Int. J. Mol. Sci.2020, 21, 3997.). A monolayer of mobile water molecules hydrates A30P α-synuclein at the lowest potential barriers (temperatures), while E46K α-synuclein has here third as much mobile hydration, insufficient for functionality. According to wide-line 1H NMR results and secondary structure predictions, E46K α-synuclein is more compact than the A30P variant and they are more compact than the wild type (WT) and A53T variants. Linear hydration vs potential barrier sections of A30P α-synuclein shows one and E46K shows two slopes. The different slopes of the latter between potential barriers Ea,1 and Ea,2 reflect a change in water–protein interactions. The 31–32% homogeneous potential barrier distribution of the protein–water bonds refers to a non-negligible amount of secondary structures in all four α-synuclein variants. The secondary structures detected by wide-line 1H NMR are solvent-exposed α-helices, which are predicted by secondary structure models. β-sheets are only minor components of the protein structures as three- and eight-state predicted secondary structures are dominated by α-helices and coils.

Structure‐function relationships for the lncRNA SChLAP1 in aggressive prostate cancer

Advances in deep sequencing technologies have facilitated the identification and annotation of thousands of long noncoding RNAs (lncRNAs) across the transcriptome. LncRNAs are documented to play critical housekeeping roles within the cell and are implicated in a wide variety of diseases, including cancer. While studies into lncRNA function in cancer abound, there are limited examples to date of detailed lncRNA structural analyses to enable understanding of structure‐function relationships. Understanding structure‐function relationships would increase our insight into the noncoding transcriptome and yield potential avenues for targeting lncRNAs implicated in disease. The lncRNA Second Chromosome Locus Associated with Prostate 1 (SChLAP1) has been identified in multiple clinical studies as a predictive biomarker and molecular driver of aggressive prostate cancer. While several protein interactors have been identified for SChLAP1 to date, structural insight into SChLAP1:protein recognition has not yet been explored. We believe that structural analysis of SChLAP1 will assist in designing specific therapeutic strategies to inhibit SChLAP1:protein interactions implicated in prostate cancer. To this end, we performed Selective 2′‐Hydroxyl Acylation analyzed by Primer Extension with Mutational Profiling (SHAPE‐MaP) and dimethyl sulfate (DMS)‐MaP in vitroand in cellulo. This approach yielded the first secondary structure model of SChLAP1, which revealed a complex architecture with a wide variety of secondary structures throughout the length of the transcript. Analyzing our in‐cell probing data with the ΔSHAPE algorithm, we identified protein binding regions within SChLAP1 and mapped them to non‐human primate‐conserved exons within the transcript. Finally, we identified a smaller, highly structured fragment of SChLAP1 that houses multiple putative protein binding sites implicated in prostate cancer. We believe that this region of SChLAP1 is amenable to therapeutic targeting and may be used as a smaller construct for in vitrodevelopment of SChLAP1‐targeting therapeutics. We also believe this fragment may be amenable to 3D biophysical analyses, such as X‐ray crystallography or cryo‐EM, to further enhance structural understanding of SChLAP1:protein complexation. Ongoing work is focused on determining the sufficiency of this fragment for protein recognition and characterizing potential magnesium‐dependent tertiary structures. We believe this work will facilitate the development of specific therapeutic strategies for SChLAP1 and contribute to the growing need of characterizing structure‐function relationships within lncRNAs.

Using Unassigned NMR Chemical Shifts to Model RNA Secondary Structure.

NMR-derived chemical shifts are sensitive probes of RNA structure. However, the need to assign NMR spectra hampers their utility as a direct source of structural information. In this report, we describe a simple method that uses unassigned 2D NMR spectra to model the secondary structure of RNAs. As in the case of assigned chemical shifts, we could use unassigned chemical shift data to reweight conformational libraries such that the highest weighted structure closely resembles their reference NMR structure. Furthermore, the application of our approach to the 3'- and 5'-UTR of the SARS-CoV-2 genome yields structures that are, for the most part, consistent with the secondary structure models derived from chemical probing data. Therefore, we expect the framework we describe here will be useful as a general strategy for rapidly generating preliminary structural RNA models directly from unassigned 2D NMR spectra. As we demonstrated for the 337-nt and 472-nt UTRs of SARS-CoV-2, our approach could be especially valuable for modeling the secondary structures of large RNA.

Cotranscriptional RNA strand exchange underlies the gene regulation mechanism in a purine-sensing transcriptional riboswitch.

RNA folds cotranscriptionally to traverse out-of-equilibrium intermediate structures that are important for RNA function in the context of gene regulation. To investigate this process, here we study the structure and function of the Bacillus subtilis yxjA purine riboswitch, a transcriptional riboswitch that downregulates a nucleoside transporter in response to binding guanine. Although the aptamer and expression platform domain sequences of the yxjA riboswitch do not completely overlap, we hypothesized that a strand exchange process triggers its structural switching in response to ligand binding. In vivo fluorescence assays, structural chemical probing data and experimentally informed secondary structure modeling suggest the presence of a nascent intermediate central helix. The formation of this central helix in the absence of ligand appears to compete with both the aptamer's P1 helix and the expression platform's transcriptional terminator. All-atom molecular dynamics simulations support the hypothesis that ligand binding stabilizes the aptamer P1 helix against central helix strand invasion, thus allowing the terminator to form. These results present a potential model mechanism to explain how ligand binding can induce downstream conformational changes by influencing local strand displacement processes of intermediate folds that could be at play in multiple riboswitch classes.

Structural modeling of human AKAP3 protein and in silico analysis of single nucleotide polymorphisms associated with sperm motility

AKAP3 is a member of the A-kinase anchoring proteins and it is a constituent of the sperm fibrous sheath. AKAP3 is needed for the formation of sperm flagellum structure, sperm motility, and male fertility. This study aims to model the AKAP3 tertiary structure and identify the probable impact of four mutations characterized in infertile men on the AKAP3 structure. The T464S, I500T, E525K, and I661T substitutions were analyzed using in silico methods. The secondary structure and three-dimensional model of AKAP3 were determined using PSI-BLAST based secondary structure prediction and Robetta servers. The TM-score was used to quantitatively measure the structural similarities between native and mutated models. All of the desired substitutions were classified as benign. I-Mutant results showed all of the substitutions decreased AKAP3 stability; however, the I500T and I661T were more effective. Superposition and secondary structure comparisons between native and mutants showed no dramatic deviations. Our study provided an appropriate model for AKAP3. Destabilization of AKAP3 caused by these substitutions did not appear to induce structural disturbances. As AKAP3 is involved in male infertility, providing more structural insights and the impact of mutations that cause protein functional diversity could elucidate the etiology of male fertility problems at molecular level.

Putative ITS2 secondary structure model and multi‐gene phylogenies of tetrahymenids (Ciliophora, Hymenostomatia) parasitizing planarians and crayfish worms

AbstractTetrahymena comprises over 80 free‐living as well as facultative or obligate histophagous species parasitizing especially invertebrates and fishes. Because of the comparatively high morphological conservativeness of tetrahymenids, their identification is primarily based on the gene coding for cytochrome c oxidase subunit I (COI). In addition to this mitochondrial barcoding marker, we tested here also the species discriminatory power of the highly variable nuclear ITS region, using the secondary structure of the ITS2 molecules and the compensatory base change (CBC) analysis. ITS2 secondary structures were proposed for 25 distinct ribotypes of 13 taxa, including three Tetrahymena species parasitizing planarians and crayfish worms, with the free‐energy minimization approach and the homology modelling. Although the majority of Tetrahymena species pairs can be reliably separated by one to six hemi‐CBCs localized especially in the third and fourth helix of the ITS2 molecules, some ITS region sequences might transcend species boundaries. In other words, intraspecies and interspecies p‐distances of ITS region sequences might overlap. This fact weakens the discriminatory power and the usage of the ITS region in the molecular taxonomy of Tetrahymena. On the other hand, there was always a distinct barcoding gap at about 4% sequence divergence in the case of the COI gene. Despite the slightly lower delimitation power of the ITS region, this molecular marker helped to recognize multiple previous misidentifications that were subsequently verified by comparing COI sequences.

Secondary Structure of Subgenomic RNA M of SARS-CoV-2.

SARS-CoV-2 belongs to the Coronavirinae family. Like other coronaviruses, SARS-CoV-2 is enveloped and possesses a positive-sense, single-stranded RNA genome of ~30 kb. Genomic RNA is used as the template for replication and transcription. During these processes, positive-sense genomic RNA (gRNA) and subgenomic RNAs (sgRNAs) are created. Several studies presented the importance of the genomic RNA secondary structure in SARS-CoV-2 replication. However, the structure of sgRNAs has remained largely unsolved so far. In this study, we probed the sgRNA M model of SARS-CoV-2 in vitro. The presented model molecule includes 5′UTR and a coding sequence of gene M. This is the first experimentally informed secondary structure model of sgRNA M, which presents features likely to be important in sgRNA M function. The knowledge of sgRNA M structure provides insights to better understand virus biology and could be used for designing new therapeutics.

Is skipping the definition of primary and secondary models possible? Prediction of Escherichia coli O157 growth by machine learning

To predict bacterial population behavior in food, statistical models with specific function form have been applied in the field of predictive microbiology. Modelers need to consider the linear or non-linear relationship between the response and explanatory variables in the statistical modeling approach. In the present study, we focused on machine learning methods to skip definition of primary and secondary structure model. Support vector regression, extremely randomized trees regression, and Gaussian process regression were used to predict population growth of Escherichia coli O157 at 15 and 25 °C without defining the primary and secondary models. Furthermore, the support vector regression model was applied to predict small population of bacteria cells with probability theory. The model performance of the machine learning models were nearly equal to that of the current statistical models. Machine learning models have a potential for predicting bacterial population behavior.

Trans-Activator Binding Site Context in RCNMV Modulates Subgenomic mRNA Transcription.

Many positive-sense RNA viruses transcribe subgenomic (sg) mRNAs during infections that template the translation of a subset of viral proteins. Red clover necrotic mosaic virus (RCNMV) expresses its capsid protein through the transcription of a sg mRNA from RNA1 genome segment. This transcription event is activated by an RNA structure formed by base pairing between a trans-activator (TA) in RNA2 and a trans-activator binding site (TABS) in RNA1. In this study, the impact of the structural context of the TABS in RNA1 on the TA–TABS interaction and sg mRNA transcription was investigated using in vitro and in vivo approaches. The results (i) generated RNA secondary structure models for the TA and TABS, (ii) revealed that the TABS is partially base paired with proximal upstream sequences, which limits TA access, (iii) demonstrated that the aforementioned intra-RNA1 base pairing involving the TABS modulates the TA–TABS interaction in vitro and sg mRNA levels during infections, and (iv) revealed that the TABS in RNA1 can be modified to mediate sg mRNA transcription in a TA-independent manner. These findings advance our understanding of transcriptional regulation in RCNMV and provide novel insights into the origin of the TA–TABS interaction.

Phylogeography and Diversity Among Populations of the Toxigenic Benthic Dinoflagellate Prorocentrum From Coastal Reef Systems in Mexico

The marine dinoflagellate genus Prorocentrum Ehrenberg comprises many species occupying primarily benthic or epiphytic habitats, particularly in tropical and sub-tropical waters. Despite concerted efforts to establish phylogenetic associations, there remain unresolved issues in defining morphospecies and membership in species complexes. The study described herein addressed the inter- and infraspecific relationships of members of the Prorocentrum lima and Prorocentrum hoffmannianum species complexes (PLSC and PHSC, respectively) by applying multivariate approaches in morphotaxonomy, molecular phylogenetics and chemodiversity to establish affinities among multiple clonal isolates. Morphotaxonomic analysis showed consistency with classical morphospecies descriptors, and high variability in cell size and dimensions, but did not challenge current species complex concepts. Phylogenetic analysis of ITS/5.8S rDNA sequences from isolates from the Gulf of California, Caribbean Sea, and Gulf of Mexico coasts compared with archived global GenBank sequences served to define five consistent clades with separation of the PLSC and PHSC. Secondary structure modeling of ITS2 rRNA variation based on compensatory base changes (CBC) was effective in resolving details of the respective species complexes and even indicated putative incipient or cryptic speciation due to potential hybridization barriers. This study represents the largest (n = 67 isolates) chemodiversity analysis of polyketide-derived toxins associated with diarrheic shellfish poisoning (DSP) from a benthic dinoflagellate genus. Relative composition of some analogs (OA, OA-D8, DTX1, DTX1a, and DTX1a-D8), including two new undescribed isomers, distinguished P. lima from P. hoffmannianum sensu lato, but without clear associations with substrate type or geographical origin. Although all P. lima and most (one exception) P. hoffmannianum were toxigenic, the total cell toxin content could not be linked at the species level. This research demonstrates that clonal chemodiversity in toxin composition cannot yet be effectively applied to define ecological niches or species interactions within local assemblages. Phylogenetic analysis of the ITS/5.8 rDNA, particularly when combined with secondary structure modeling, rather than only a comparison of LSU rDNA sequences, is a more powerful approach to identify cryptic speciation and to resolve species complexes within benthic dinoflagellate groups.

Prediction of RNA secondary structure including pseudoknots for long sequences.

RNA structural elements called pseudoknots are involved in various biological phenomena including ribosomal frameshifts. Because it is infeasible to construct an efficiently computable secondary structure model including pseudoknots, secondary structure prediction methods considering pseudoknots are not yet widely available. We developed IPknot, which uses heuristics to speed up computations, but it has remained difficult to apply it to long sequences, such as messenger RNA and viral RNA, because it requires cubic computational time with respect to sequence length and has threshold parameters that need to be manually adjusted. Here, we propose an improvement of IPknot that enables calculation in linear time by employing the LinearPartition model and automatically selects the optimal threshold parameters based on the pseudo-expected accuracy. In addition, IPknot showed favorable prediction accuracy across a wide range of conditions in our exhaustive benchmarking, not only for single sequences but also for multiple alignments.