LocalSTAR3D: a local stack-based RNA 3D structural alignment tool

Chen, Xiaoli; Khan, Nabila Shahnaz; Zhang, Shaojie

doi:10.1093/nar/gkaa453

Cited by 7 publications

(19 citation statements)

References 49 publications

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“…It can also detect modules and tertiary structure patterns, including pseudoknots and kink-turns. The recent extension, DSSR-PyMOL [ 68 ], allows drawing cartoon-block schemes of the 3D structure and responds to the need for simplified visualization of quadruplexes. Input data formats: PDB, mmCIF and PDB ID.…”

Section: Methodsmentioning

confidence: 99%

How bioinformatics resources work with G4 RNAs

Miskiewicz

Sarzyñska

Szachniuk

2020

Briefings in Bioinformatics

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Quadruplexes (G4s) are of interest, which increases with the number of identified G4 structures and knowledge about their biomedical potential. These unique motifs form in many organisms, including humans, where their appearance correlates with various diseases. Scientists store and analyze quadruplexes using recently developed bioinformatic tools—many of them focused on DNA structures. With an expanding collection of G4 RNAs, we check how existing tools deal with them. We review all available bioinformatics resources dedicated to quadruplexes and examine their usefulness in G4 RNA analysis. We distinguish the following subsets of resources: databases, tools to predict putative quadruplex sequences, tools to predict secondary structure with quadruplexes and tools to analyze and visualize quadruplex structures. We share the results obtained from processing specially created RNA datasets with these tools. Contact:mszachniuk@cs.put.poznan.plSupplementary information: Supplementary data are available at Briefings in Bioinformatics online.

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Section: Methodsmentioning

confidence: 99%

How bioinformatics resources work with G4 RNAs

Miskiewicz

Sarzyñska

Szachniuk

2020

Briefings in Bioinformatics

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“…There are numerous computational approaches currently available in the form of webservers, databases, or downloadable executables (Table 1) [6][7][8][9][10][11][12][13][14][15]17,[19][20][21][22][23][24][25][26][28][29][30][31][33][34][35][36]. The variety of methods, inputs, and outputs that are offered by the currently available programs (Table 1) create a rather complementary RNA base motif analysis ecosystem [6][7][8][9][10][11][12][13][14][15]17,[19][20][21][22][23][24][25][26][28][29]…”

Section: Comparison Of Computational Approaches In Annotating Rna Base Motifsmentioning

confidence: 99%

“…The variety of methods, inputs, and outputs that are offered by the currently available programs (Table 1) create a rather complementary RNA base motif analysis ecosystem [6][7][8][9][10][11][12][13][14][15]17,[19][20][21][22][23][24][25][26][28][29][30][31][33][34][35][36]. Many of those approaches, such as NASSAM, COGNAC, MC-Annotate, R3D align, RNA-Bricks, RNAMotifsScanX, and LocalStar3D (Table 1) [9,18,22,26,28,30,35], employ graph theoretical algorithms. However, due to the different objectives of each program, the graph representations used also differ.…”

Section: Comparison Of Computational Approaches In Annotating Rna Base Motifsmentioning

confidence: 99%

“…However, due to the different objectives of each program, the graph representations used also differ. The programs R3D align and LocalStar3D adopt graph-based alignments, where the nodes are the local base alignments and the edges connect the alignments [18,35]. RNA-Bricks adopts a reduced graph representation using 3D motifs such as loops, stems, or single strand terminals as the nodes and the nucleotide pairs, intra-molecular interactions, or crystallographic contacts as edges [28].…”

Section: Comparison Of Computational Approaches In Annotating Rna Base Motifsmentioning

confidence: 99%

“…Motif analysis on ribosomal structures that are of low resolution could benefit from the method employed by CompAnnotate [32]. For tertiary structure analyses that require a wider range of motif annotations, users can opt for WebFR3D, RNA Frabase 2.0, and NASSAM [9,18,22,26,28,30,35]. The primary focus of this paper will be on a suite of graph theoretical algorithms with web browser interfaces because such accessibility could allow for a wider user base.…”

Section: Comparison Of Computational Approaches In Annotating Rna Base Motifsmentioning

confidence: 99%

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Graph Theoretical Methods and Workflows for Searching and Annotation of RNA Tertiary Base Motifs and Substructures

Emrizal

Hamdani

Firdaus-Raih

2021

IJMS

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The increasing number and complexity of structures containing RNA chains in the Protein Data Bank (PDB) have led to the need for automated structure annotation methods to replace or complement expert visual curation. This is especially true when searching for tertiary base motifs and substructures. Such base arrangements and motifs have diverse roles that range from contributions to structural stability to more direct involvement in the molecule’s functions, such as the sites for ligand binding and catalytic activity. We review the utility of computational approaches in annotating RNA tertiary base motifs in a dataset of PDB structures, particularly the use of graph theoretical algorithms that can search for such base motifs and annotate them or find and annotate clusters of hydrogen-bond-connected bases. We also demonstrate how such graph theoretical algorithms can be integrated into a workflow that allows for functional analysis and comparisons of base arrangements and sub-structures, such as those involved in ligand binding. The capacity to carry out such automatic curations has led to the discovery of novel motifs and can give new context to known motifs as well as enable the rapid compilation of RNA 3D motifs into a database.

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CircularSTAR3D: a stack-based RNA 3D structural alignment tool for circular matching

Chen

Zhang

2023

Nucleic Acids Research

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The functions of non-coding RNAs usually depend on their 3D structures. Therefore, comparing RNA 3D structures is critical in analyzing their functions. We noticed an interesting phenomenon that two non-coding RNAs may share similar substructures when rotating their sequence order. To the best of our knowledge, no existing RNA 3D structural alignment tools can detect this type of matching. In this article, we defined the RNA 3D structure circular matching problem and developed a software tool named CircularSTAR3D to solve this problem. CircularSTAR3D first uses the conserved stacks (consecutive base pairs with similar 3D structures) in the input RNAs to identify the circular matched internal loops and multiloops. Then it performs a local extension iteratively to obtain the whole circular matched substructures. The computational experiments conducted on a non-redundant RNA structure dataset show that circular matching is ubiquitous. Furthermore, we demonstrated the utility of CircularSTAR3D by detecting the conserved substructures missed by regular alignment tools, including structural motifs and conserved structures between riboswitches and ribozymes from different classes. We anticipate CircularSTAR3D to be a valuable supplement to the existing RNA 3D structural analysis techniques.

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LocalSTAR3D: a local stack-based RNA 3D structural alignment tool

Cited by 7 publications

References 49 publications

How bioinformatics resources work with G4 RNAs

How bioinformatics resources work with G4 RNAs

Graph Theoretical Methods and Workflows for Searching and Annotation of RNA Tertiary Base Motifs and Substructures

CircularSTAR3D: a stack-based RNA 3D structural alignment tool for circular matching

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