1
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Wang H, Lu X, Zheng H, Wang W, Zhang G, Wang S, Lin P, Zhuang Y, Chen C, Chen Q, Qu J, Xu L. RNAsmc: A integrated tool for comparing RNA secondary structure and evaluating allosteric effects. Comput Struct Biotechnol J 2023; 21:965-973. [PMID: 36733704 PMCID: PMC9876829 DOI: 10.1016/j.csbj.2023.01.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 01/06/2023] [Accepted: 01/07/2023] [Indexed: 01/11/2023] Open
Abstract
RNA structure plays a crucial role in gene regulation, in RNA stability and the essential biological processes. RNA secondary structure (RSS) motifs are the basic building blocks for investigating the biological mechanisms of structure. Here, we present a strategy for structural motif-based dynamic alignment, namely, RNA secondary-structural motif-comparing (RNAsmc), to identify structural motifs and quantitatively evaluate their underlying molecular functions. RNAsmc also has strong robustness to sequence length, folding protocol and RNA structural profile by chemical probing. Notably, it is also applicable to quantify structural variation in special RNA editing events (SNVs or SNPs, fragment insertion or deletion, etc.). The findings indicate that RNAsmc can uncover the heterogeneity of RNA secondary structure and score for similarities among components, which provides an impetus to cluster RNA families and evaluate allosteric effects. We find that RNAsmc exhibits remarkable detection efficiency for experimentally-derived RiboSNitches. Finally, the pipeline was assembled into an R software package to serve as an automated toolkit to explore, align, and cluster RSS. It is freely available for download at https://CRAN.R-project.org/package=RNAsmc.
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Affiliation(s)
- Hong Wang
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
- State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
- Center of Optometry International Innovation of Wenzhou, Eye Valley, Wenzhou 325027, China
| | - Xiaoyan Lu
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Hewei Zheng
- Wekemo Tech Group Co., Ltd. Shenzhen 518000, China
| | - Wencan Wang
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
- State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
- Wenzhou Realdata Medical Research Co., Ltd, Wenzhou 325027, China
| | - Guosi Zhang
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
- State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Siyu Wang
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
- State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Peng Lin
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
- State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Youyuan Zhuang
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
- State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Chong Chen
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
- State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Qi Chen
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
- State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Jia Qu
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
- State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
- Center of Optometry International Innovation of Wenzhou, Eye Valley, Wenzhou 325027, China
- Corresponding authors at: National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
| | - Liangde Xu
- National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
- State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
- Center of Optometry International Innovation of Wenzhou, Eye Valley, Wenzhou 325027, China
- Corresponding authors at: National Engineering Research Center of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China
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2
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Retwitzer MD, Reinharz V, Churkin A, Ponty Y, Waldispühl J, Barash D. incaRNAfbinv 2.0: a webserver and software with motif control for fragment-based design of RNAs. Bioinformatics 2020; 36:2920-2922. [PMID: 31971575 DOI: 10.1093/bioinformatics/btaa039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2019] [Revised: 11/25/2019] [Accepted: 01/15/2020] [Indexed: 11/12/2022] Open
Abstract
SUMMARY RNA design has conceptually evolved from the inverse RNA folding problem. In the classical inverse RNA problem, the user inputs an RNA secondary structure and receives an output RNA sequence that folds into it. Although modern RNA design methods are based on the same principle, a finer control over the resulting sequences is sought. As an important example, a substantial number of non-coding RNA families show high preservation in specific regions, while being more flexible in others and this information should be utilized in the design. By using the additional information, RNA design tools can help solve problems of practical interest in the growing fields of synthetic biology and nanotechnology. incaRNAfbinv 2.0 utilizes a fragment-based approach, enabling a control of specific RNA secondary structure motifs. The new version allows significantly more control over the general RNA shape, and also allows to express specific restrictions over each motif separately, in addition to other advanced features. AVAILABILITY AND IMPLEMENTATION incaRNAfbinv 2.0 is available through a standalone package and a web-server at https://www.cs.bgu.ac.il/incaRNAfbinv. Source code, command-line and GUI wrappers can be found at https://github.com/matandro/RNAsfbinv. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Matan Drory Retwitzer
- Department of Computer Science, Ben Gurion University of the Negev, Beer Sheva 84105, Israel
| | - Vladimir Reinharz
- Department of Computer Science, Université du Québec à Montréal, Montreal, H2X 3Y7, Canada.,Institute for Basic Science, Daejeon 34126, South Korea
| | - Alexander Churkin
- Software Engineering Department, Sami Shamoon College of Engineering, Beer-Sheva 84100, Israel
| | - Yann Ponty
- Laboratoire d'Informatique de l'École Polytechnique (LIX CNRS UMR 7161), Ecole Polytechnique, Palaiseau 91120, France
| | - Jérôme Waldispühl
- School of Computer Science, McGill University Montréal H3A 0E9, Canada
| | - Danny Barash
- Department of Computer Science, Ben Gurion University of the Negev, Beer Sheva 84105, Israel
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3
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Yamagami R, Kayedkhordeh M, Mathews DH, Bevilacqua PC. Design of highly active double-pseudoknotted ribozymes: a combined computational and experimental study. Nucleic Acids Res 2019; 47:29-42. [PMID: 30462314 PMCID: PMC6326823 DOI: 10.1093/nar/gky1118] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2018] [Accepted: 10/24/2018] [Indexed: 01/02/2023] Open
Abstract
Design of RNA sequences that adopt functional folds establishes principles of RNA folding and applications in biotechnology. Inverse folding for RNAs, which allows computational design of sequences that adopt specific structures, can be utilized for unveiling RNA functions and developing genetic tools in synthetic biology. Although many algorithms for inverse RNA folding have been developed, the pseudoknot, which plays a key role in folding of ribozymes and riboswitches, is not addressed in most algorithms. For the few algorithms that attempt to predict pseudoknot-containing ribozymes, self-cleavage activity has not been tested. Herein, we design double-pseudoknot HDV ribozymes using an inverse RNA folding algorithm and test their kinetic mechanisms experimentally. More than 90% of the positively designed ribozymes possess self-cleaving activity, whereas more than 70% of negative control ribozymes, which are predicted to fold to the necessary structure but with low fidelity, do not possess it. Kinetic and mutation analyses reveal that these RNAs cleave site-specifically and with the same mechanism as the WT ribozyme. Most ribozymes react just 50- to 80-fold slower than the WT ribozyme, and this rate can be improved to near WT by modification of a junction. Thus, fast-cleaving functional ribozymes with multiple pseudoknots can be designed computationally.
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Affiliation(s)
- Ryota Yamagami
- Department of Chemistry, Pennsylvania State University, University Park, PA 16802, USA.,Center for RNA Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - Mohammad Kayedkhordeh
- Department of Biochemistry & Biophysics and Center for RNA Biology, University of Rochester Medical Center, Rochester, New York, NY 14642, USA
| | - David H Mathews
- Department of Biochemistry & Biophysics and Center for RNA Biology, University of Rochester Medical Center, Rochester, New York, NY 14642, USA.,Department of Biostatistics & Computational Biology, University of Rochester Medical Center, Rochester, New York, NY 14642, USA
| | - Philip C Bevilacqua
- Department of Chemistry, Pennsylvania State University, University Park, PA 16802, USA.,Center for RNA Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA.,Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA
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Jain S, Laederach A, Ramos SBV, Schlick T. A pipeline for computational design of novel RNA-like topologies. Nucleic Acids Res 2018; 46:7040-7051. [PMID: 30137633 PMCID: PMC6101589 DOI: 10.1093/nar/gky524] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2017] [Revised: 05/22/2018] [Accepted: 05/24/2018] [Indexed: 12/11/2022] Open
Abstract
Designing novel RNA topologies is a challenge, with important therapeutic and industrial applications. We describe a computational pipeline for design of novel RNA topologies based on our coarse-grained RNA-As-Graphs (RAG) framework. RAG represents RNA structures as tree graphs and describes RNA secondary (2D) structure topologies (currently up to 13 vertices, ≈260 nucleotides). We have previously identified novel graph topologies that are RNA-like among these. Here we describe a systematic design pipeline and illustrate design for six broad design problems using recently developed tools for graph-partitioning and fragment assembly (F-RAG). Following partitioning of the target graph, corresponding atomic fragments from our RAG-3D database are combined using F-RAG, and the candidate atomic models are scored using a knowledge-based potential developed for 3D structure prediction. The sequences of the top scoring models are screened further using available tools for 2D structure prediction. The results indicate that our modular approach based on RNA-like topologies rather than specific 2D structures allows for greater flexibility in the design process, and generates a large number of candidate sequences quickly. Experimental structure probing using SHAPE-MaP for two sequences agree with our predictions and suggest that our combined tools yield excellent candidates for further sequence and experimental screening.
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Affiliation(s)
- Swati Jain
- Department of Chemistry, New York University, 1001 Silver, 100 Washington Square East, New York, NY 10003, USA
| | - Alain Laederach
- Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Silvia B V Ramos
- Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Tamar Schlick
- Department of Chemistry, New York University, 1001 Silver, 100 Washington Square East, New York, NY 10003, USA
- Courant Institute of Mathematical Sciences, New York University, 251 Mercer Street, New York, NY 10012, USA
- NYU-ECNU Center for Computational Chemistry at New York University Shanghai, Room 340, Geography Building, North Zhongshan Road, 3663 Shanghai, China
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5
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Lotfi M, Zare-Mirakabad F, Montaseri S. RNA design using simulated SHAPE data. Genes Genet Syst 2018; 92:257-265. [PMID: 28757510 DOI: 10.1266/ggs.16-00067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
It has long been established that in addition to being involved in protein translation, RNA plays essential roles in numerous other cellular processes, including gene regulation and DNA replication. Such roles are known to be dictated by higher-order structures of RNA molecules. It is therefore of prime importance to find an RNA sequence that can fold to acquire a particular function that is desirable for use in pharmaceuticals and basic research. The challenge of finding an RNA sequence for a given structure is known as the RNA design problem. Although there are several algorithms to solve this problem, they mainly consider hard constraints, such as minimum free energy, to evaluate the predicted sequences. Recently, SHAPE data has emerged as a new soft constraint for RNA secondary structure prediction. To take advantage of this new experimental constraint, we report here a new method for accurate design of RNA sequences based on their secondary structures using SHAPE data as pseudo-free energy. We then compare our algorithm with four others: INFO-RNA, ERD, MODENA and RNAifold 2.0. Our algorithm precisely predicts 26 out of 29 new sequences for the structures extracted from the Rfam dataset, while the other four algorithms predict no more than 22 out of 29. The proposed algorithm is comparable to the above algorithms on RNA-SSD datasets, where they can predict up to 33 appropriate sequences for RNA secondary structures out of 34.
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Affiliation(s)
- Mohadeseh Lotfi
- Faculty of Mathematics and Computer Science, Amirkabir University of Technology
| | | | - Soheila Montaseri
- School of Mathematics, Statistics and Computer Science, College of Science, Enghelab Avenue, University of Tehran
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6
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Churkin A, Retwitzer MD, Reinharz V, Ponty Y, Waldispühl J, Barash D. Design of RNAs: comparing programs for inverse RNA folding. Brief Bioinform 2018; 19:350-358. [PMID: 28049135 PMCID: PMC6018860 DOI: 10.1093/bib/bbw120] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Computational programs for predicting RNA sequences with desired folding properties have been extensively developed and expanded in the past several years. Given a secondary structure, these programs aim to predict sequences that fold into a target minimum free energy secondary structure, while considering various constraints. This procedure is called inverse RNA folding. Inverse RNA folding has been traditionally used to design optimized RNAs with favorable properties, an application that is expected to grow considerably in the future in light of advances in the expanding new fields of synthetic biology and RNA nanostructures. Moreover, it was recently demonstrated that inverse RNA folding can successfully be used as a valuable preprocessing step in computational detection of novel noncoding RNAs. This review describes the most popular freeware programs that have been developed for such purposes, starting from RNAinverse that was devised when formulating the inverse RNA folding problem. The most recently published ones that consider RNA secondary structure as input are antaRNA, RNAiFold and incaRNAfbinv, each having different features that could be beneficial to specific biological problems in practice. The various programs also use distinct approaches, ranging from ant colony optimization to constraint programming, in addition to adaptive walk, simulated annealing and Boltzmann sampling. This review compares between the various programs and provides a simple description of the various possibilities that would benefit practitioners in selecting the most suitable program. It is geared for specific tasks requiring RNA design based on input secondary structure, with an outlook toward the future of RNA design programs.
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Affiliation(s)
- Alexander Churkin
- Shamoon College of Engineering and Physics Department at Ben-Gurion University, Beer-Sheva, Israel
| | | | - Vladimir Reinharz
- Department of Computer Science, Ben-Gurion University, Beer-Sheva, Israel
- School of Computer Science, McGill University, Montréal QC, Canada
| | - Yann Ponty
- Laboratoire d’informatique, École Polytechnique, Palaiseau, France
| | | | - Danny Barash
- Department of Computer Science, Ben-Gurion University, Beer-Sheva, Israel
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7
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Drory Retwitzer M, Reinharz V, Ponty Y, Waldispühl J, Barash D. incaRNAfbinv: a web server for the fragment-based design of RNA sequences. Nucleic Acids Res 2016; 44:W308-14. [PMID: 27185893 PMCID: PMC5741205 DOI: 10.1093/nar/gkw440] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2016] [Accepted: 05/06/2016] [Indexed: 01/02/2023] Open
Abstract
In recent years, new methods for computational RNA design have been developed and applied to various problems in synthetic biology and nanotechnology. Lately, there is considerable interest in incorporating essential biological information when solving the inverse RNA folding problem. Correspondingly, RNAfbinv aims at including biologically meaningful constraints and is the only program to-date that performs a fragment-based design of RNA sequences. In doing so it allows the design of sequences that do not necessarily exactly fold into the target, as long as the overall coarse-grained tree graph shape is preserved. Augmented by the weighted sampling algorithm of incaRNAtion, our web server called incaRNAfbinv implements the method devised in RNAfbinv and offers an interactive environment for the inverse folding of RNA using a fragment-based design approach. It takes as input: a target RNA secondary structure; optional sequence and motif constraints; optional target minimum free energy, neutrality and GC content. In addition to the design of synthetic regulatory sequences, it can be used as a pre-processing step for the detection of novel natural occurring RNAs. The two complementary methodologies RNAfbinv and incaRNAtion are merged together and fully implemented in our web server incaRNAfbinv, available at http://www.cs.bgu.ac.il/incaRNAfbinv.
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Affiliation(s)
| | - Vladimir Reinharz
- School of Computer Science & McGill Centre for Bioinformatics, McGill University, Montréal, QC H3A 0E9, Canada
| | - Yann Ponty
- Laboratoire d'Informatique (LIX)-CNRS UMR 7161, École Polytechnique, 91128 Palaiseau, France AMIB team/project, INRIA Saclay, Bâtiment Alan Turing, 91128 Palaiseau, France
| | - Jérôme Waldispühl
- School of Computer Science & McGill Centre for Bioinformatics, McGill University, Montréal, QC H3A 0E9, Canada
| | - Danny Barash
- Department of Computer Science, Ben-Gurion University, Beer-Sheva 84105, Israel
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Kleinkauf R, Houwaart T, Backofen R, Mann M. antaRNA--Multi-objective inverse folding of pseudoknot RNA using ant-colony optimization. BMC Bioinformatics 2015; 16:389. [PMID: 26581440 PMCID: PMC4652366 DOI: 10.1186/s12859-015-0815-6] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2015] [Accepted: 10/20/2015] [Indexed: 01/14/2023] Open
Abstract
Background Many functional RNA molecules fold into pseudoknot structures, which are often essential for the formation of an RNA’s 3D structure. Currently the design of RNA molecules, which fold into a specific structure (known as RNA inverse folding) within biotechnological applications, is lacking the feature of incorporating pseudoknot structures into the design. Hairpin-(H)- and kissing hairpin-(K)-type pseudoknots cover a wide range of biologically functional pseudoknots and can be represented on a secondary structure level. Results The RNA inverse folding program antaRNA, which takes secondary structure, target GC-content and sequence constraints as input, is extended to provide solutions for such H- and K-type pseudoknotted secondary structure constraint. We demonstrate the easy and flexible interchangeability of modules within the antaRNA framework by incorporating pKiss as structure prediction tool capable of predicting the mentioned pseudoknot types. The performance of the approach is demonstrated on a subset of the Pseudobase ++ dataset. Conclusions This new service is available via a standalone version and is also part of the Freiburg RNA Tools webservice. Furthermore, antaRNA is available in Galaxy and is part of the RNA-workbench Docker image.
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Affiliation(s)
- Robert Kleinkauf
- Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, Freiburg, 79110, Germany.
| | - Torsten Houwaart
- Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, Freiburg, 79110, Germany.
| | - Rolf Backofen
- Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, Freiburg, 79110, Germany. .,Center for Biological Signaling Studies (BIOSS), University of Freiburg, Freiburg, Germany. .,Center for Biological Systems Analysis (ZBSA), University of Freiburg, Freiburg, Germany. .,Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, Frederiksberg C, 1870, Denmark.
| | - Martin Mann
- Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, Freiburg, 79110, Germany.
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Drory Retwitzer M, Kifer I, Sengupta S, Yakhini Z, Barash D. An Efficient Minimum Free Energy Structure-Based Search Method for Riboswitch Identification Based on Inverse RNA Folding. PLoS One 2015; 10:e0134262. [PMID: 26230932 PMCID: PMC4521916 DOI: 10.1371/journal.pone.0134262] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2015] [Accepted: 07/07/2015] [Indexed: 11/22/2022] Open
Abstract
Riboswitches are RNA genetic control elements that were originally discovered in bacteria and provide a unique mechanism of gene regulation. They work without the participation of proteins and are believed to represent ancient regulatory systems in the evolutionary timescale. One of the biggest challenges in riboswitch research is to find additional eukaryotic riboswitches since more than 20 riboswitch classes have been found in prokaryotes but only one class has been found in eukaryotes. Moreover, this single known class of eukaryotic riboswitch, namely the TPP riboswitch class, has been found in bacteria, archaea, fungi and plants but not in animals. The few examples of eukaryotic riboswitches were identified using sequence-based bioinformatics search methods such as a combination of BLAST and pattern matching techniques that incorporate base-pairing considerations. None of these approaches perform energy minimization structure predictions. There is a clear motivation to develop new bioinformatics methods, aside of the ongoing advances in covariance models, that will sample the sequence search space more flexibly using structural guidance while retaining the computational efficiency of sequence-based methods. We present a new energy minimization approach that transforms structure-based search into a sequence-based search, thereby enabling the utilization of well established sequence-based search utilities such as BLAST and FASTA. The transformation to sequence space is obtained by using an extended inverse RNA folding problem solver with sequence and structure constraints, available within RNAfbinv. Examples in applying the new method are presented for the purine and preQ1 riboswitches. The method is described in detail along with its findings in prokaryotes. Potential uses in finding novel eukaryotic riboswitches and optimizing pre-designed synthetic riboswitches based on ligand simulations are discussed. The method components are freely available for use.
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Affiliation(s)
| | - Ilona Kifer
- Agilent Laboratories, Tel Aviv, Israel; Microsoft R&D Center, Herzliya, Israel
| | - Supratim Sengupta
- Department of Physical Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, 741246, India
| | - Zohar Yakhini
- Agilent Laboratories, Tel Aviv, Israel; Laboratory of Computational Biology, Computer Science Department, Israel Institute of Technology, Haifa, 32000, Israel
| | - Danny Barash
- Department of Computer Science, Ben-Gurion University, Beer-Sheva, 84105, Israel
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10
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Kleinkauf R, Mann M, Backofen R. antaRNA: ant colony-based RNA sequence design. Bioinformatics 2015; 31:3114-21. [PMID: 26023105 PMCID: PMC4576691 DOI: 10.1093/bioinformatics/btv319] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2015] [Accepted: 05/18/2015] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION RNA sequence design is studied at least as long as the classical folding problem. Although for the latter the functional fold of an RNA molecule is to be found ,: inverse folding tries to identify RNA sequences that fold into a function-specific target structure. In combination with RNA-based biotechnology and synthetic biology ,: reliable RNA sequence design becomes a crucial step to generate novel biochemical components. RESULTS In this article ,: the computational tool antaRNA is presented. It is capable of compiling RNA sequences for a given structure that comply in addition with an adjustable full range objective GC-content distribution ,: specific sequence constraints and additional fuzzy structure constraints. antaRNA applies ant colony optimization meta-heuristics and its superior performance is shown on a biological datasets. AVAILABILITY AND IMPLEMENTATION http://www.bioinf.uni-freiburg.de/Software/antaRNA CONTACT: backofen@informatik.uni-freiburg.de SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Robert Kleinkauf
- Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany
| | - Martin Mann
- Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany
| | - Rolf Backofen
- Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany, Center for Biological Signaling Studies (BIOSS), University of Freiburg, Germany, Center for Biological Systems Analysis (ZBSA), University of Freiburg, Germany and Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, DK-1870 Frederiksberg C, Denmark
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11
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Garcia-Martin JA, Dotu I, Clote P. RNAiFold 2.0: a web server and software to design custom and Rfam-based RNA molecules. Nucleic Acids Res 2015; 43:W513-21. [PMID: 26019176 PMCID: PMC4489274 DOI: 10.1093/nar/gkv460] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2015] [Accepted: 04/27/2015] [Indexed: 12/25/2022] Open
Abstract
Several algorithms for RNA inverse folding have been used to design synthetic riboswitches, ribozymes and thermoswitches, whose activity has been experimentally validated. The RNAiFold software is unique among approaches for inverse folding in that (exhaustive) constraint programming is used instead of heuristic methods. For that reason, RNAiFold can generate all sequences that fold into the target structure or determine that there is no solution. RNAiFold 2.0 is a complete overhaul of RNAiFold 1.0, rewritten from the now defunct COMET language to C++. The new code properly extends the capabilities of its predecessor by providing a user-friendly pipeline to design synthetic constructs having the functionality of given Rfam families. In addition, the new software supports amino acid constraints, even for proteins translated in different reading frames from overlapping coding sequences; moreover, structure compatibility/incompatibility constraints have been expanded. With these features, RNAiFold 2.0 allows the user to design single RNA molecules as well as hybridization complexes of two RNA molecules. Availability: the web server, source code and linux binaries are publicly accessible at http://bioinformatics.bc.edu/clotelab/RNAiFold2.0.
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Affiliation(s)
| | - Ivan Dotu
- Research Programme on Biomedical Informatics (GRIB), Department of Experimental and Health Sciences, Universitat Pompeu Fabra, IMIM (Hospital del Mar Medical Research Institute); C/Dr. Aiguader 88, Barcelona E-08003, Spain
| | - Peter Clote
- Biology Department, Boston College, 140 Commonwealth Avenue, Chestnut Hill, MA 02467, USA
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12
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Churkin A, Weinbrand L, Barash D. Free energy minimization to predict RNA secondary structures and computational RNA design. Methods Mol Biol 2015; 1269:3-16. [PMID: 25577369 DOI: 10.1007/978-1-4939-2291-8_1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Determining the RNA secondary structure from sequence data by computational predictions is a long-standing problem. Its solution has been approached in two distinctive ways. If a multiple sequence alignment of a collection of homologous sequences is available, the comparative method uses phylogeny to determine conserved base pairs that are more likely to form as a result of billions of years of evolution than by chance. In the case of single sequences, recursive algorithms that compute free energy structures by using empirically derived energy parameters have been developed. This latter approach of RNA folding prediction by energy minimization is widely used to predict RNA secondary structure from sequence. For a significant number of RNA molecules, the secondary structure of the RNA molecule is indicative of its function and its computational prediction by minimizing its free energy is important for its functional analysis. A general method for free energy minimization to predict RNA secondary structures is dynamic programming, although other optimization methods have been developed as well along with empirically derived energy parameters. In this chapter, we introduce and illustrate by examples the approach of free energy minimization to predict RNA secondary structures.
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Affiliation(s)
- Alexander Churkin
- Department of Computer Science, Ben-Gurion University, 653, Beer-Sheva, 84105, Israel
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