A Particle Swarm Optimizer for Finding Minimum Free Energy RNA Secondary Structures

2007 ◽  
Author(s):  
Michael Geis ◽  
Martin Middendorf
Keyword(s):  
Free Energy ◽  
Particle Swarm ◽  
Secondary Structures ◽  
Minimum Free Energy ◽  
Particle Swarm Optimizer ◽  
Rna Secondary Structures

PSRna: Prediction of small RNA secondary structures based on reverse complementary folding method

2016 ◽  
Vol 14 (04) ◽  
pp. 1643001 ◽  
Author(s):  
Jin Li ◽  
Chengzhen Xu ◽  
Lei Wang ◽  
Hong Liang ◽  
Weixing Feng ◽  
...  
Keyword(s):  
Free Energy ◽  
Secondary Structure ◽  
Small Rna ◽  
Small Rnas ◽  
Dynamic Programming Algorithm ◽  
Real Data ◽  
Secondary Structures ◽  
Minimum Free Energy ◽  
Programming Algorithm ◽  
Rna Secondary Structures

Prediction of RNA secondary structures is an important problem in computational biology and bioinformatics, since RNA secondary structures are fundamental for functional analysis of RNA molecules. However, small RNA secondary structures are scarce and few algorithms have been specifically designed for predicting the secondary structures of small RNAs. Here we propose an algorithm named “PSRna” for predicting small-RNA secondary structures using reverse complementary folding and characteristic hairpin loops of small RNAs. Unlike traditional algorithms that usually generate multi-branch loops and 5[Formula: see text] end self-folding, PSRna first estimated the maximum number of base pairs of RNA secondary structures based on the dynamic programming algorithm and a path matrix is constructed at the same time. Second, the backtracking paths are extracted from the path matrix based on backtracking algorithm, and each backtracking path represents a secondary structure. To improve accuracy, the predicted RNA secondary structures are filtered based on their free energy, where only the secondary structure with the minimum free energy was identified as the candidate secondary structure. Our experiments on real data show that the proposed algorithm is superior to two popular methods, RNAfold and RNAstructure, in terms of sensitivity, specificity and Matthews correlation coefficient (MCC).

scholarly journals Base-pair ambiguity and the kinetics of RNA folding

2019 ◽  
Vol 20 (1) ◽  
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.

scholarly journals Base-pair Ambiguity and the Kinetics of RNA Folding

2019 ◽  
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.

scholarly journals Mathematical and Biological Modelling of RNA Secondary Structure and Its Effects on Gene Expression

2006 ◽  
Vol 7 (1) ◽  
pp. 37-43 ◽  
Author(s):  
T. A. Hughes ◽  
J. N. McElwaine
Keyword(s):  
Gene Expression ◽  
Free Energy ◽  
Secondary Structure ◽  
Structure Prediction ◽  
Secondary Structure Prediction ◽  
Secondary Structures ◽  
Minimum Free Energy ◽  
Messenger Rnas ◽  
Rna Sequences ◽  
Translational Machinery

Secondary structures within the 5′ untranslated regions of messenger RNAs can have profound effects on the efficiency of translation of their messages and thereby on gene expression. Consequently they can act as important regulatory motifs in both physiological and pathological settings. Current approaches to predicting the secondary structure of these RNA sequences find the structure with the global-minimum free energy. However, since RNA folds progressively from the 5′ end when synthesised or released from the translational machinery, this may not be the most probable structure. We discuss secondary structure prediction based on local-minimisation of free energy with thermodynamic fluctuations as nucleotides are added to the 3′ end and show that these can result in different secondary structures. We also discuss approaches for studying the extent of the translational inhibition specified by structures within the 5′ untranslated region.

scholarly journals A meta-analysis of gRNA library screens enables an improved understanding of the impact of gRNA folding and structural stability on CRISPR-Cas9 activity.

2021 ◽  
Author(s):  
Eirik A Moreb ◽  
Michael D Lynch
Keyword(s):  
Free Energy ◽  
Structural Stability ◽  
Meta Analysis ◽  
Secondary Structures ◽  
Minimum Free Energy ◽  
Guide Rna ◽  
Prediction Algorithms ◽  
The Impact

CRISPR systems are known to be inhibited by unwanted secondary structures that form within the guide RNA (gRNA). The minimum free energy of predicted secondary structures has been used in prediction algorithms. However, the types of structures as well as the degree to which a predicted structure can inhibit Cas9/gRNA activity is not well characterized. Here we perform a meta-analysis of published CRISPR-Cas9 datasets to better understand the role of secondary structures in inhibiting gRNA activity. We identify two inhibitory structures and provide estimated free energy cutoffs at which they become impactful. Further, we identify the prevalence of these structures in existing datasets. The cutoffs provided help to explain conflicting impacts of free energy values in different datasets as well as providing a guideline for future gRNA designs.

Sign in / Sign up

Export Citation Format

Share Document