The assessment of molecular dynamics results of three-dimensional RNA aptamer structure prediction
Aptamers are single-stranded DNA or RNA that bind to specific targets such as proteins, thus having similar characteristics to antibodies. It can be synthesized at a lower cost, with no batch-to-batch variations, and is easier to modify chemically than antibodies, thus potentially being used as ther...
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Published in | PloS one Vol. 18; no. 7; p. e0288684 |
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Main Authors | , , , , , , , , |
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Language | English |
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27.07.2023
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Abstract | Aptamers are single-stranded DNA or RNA that bind to specific targets such as proteins, thus having similar characteristics to antibodies. It can be synthesized at a lower cost, with no batch-to-batch variations, and is easier to modify chemically than antibodies, thus potentially being used as therapeutic and biosensing agents. The current method for RNA aptamer identification in vitro uses the SELEX method, which is considered inefficient due to its complex process. Computational models of aptamers have been used to predict and study the molecular interaction of modified aptamers to improve affinity. In this study, we generated three-dimensional models of five RNA aptamers from their sequence using mFold, RNAComposer web server, and molecular dynamics simulation. The model structures were then evaluated and compared with the experimentally determined structures. This study showed that the combination of mFold, RNAComposer, and molecular dynamics simulation could generate 14-16, 28, or 29 nucleotides length of 3D RNA aptamer with similar geometry and topology to the experimentally determined structures. The non-canonical basepair structure of the aptamer loop was formed through the MD simulation, which also improved the three-dimensional RNA aptamers model. Clustering analysis was recommended to choose the more representative model. |
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AbstractList | Aptamers are single-stranded DNA or RNA that bind to specific targets such as proteins, thus having similar characteristics to antibodies. It can be synthesized at a lower cost, with no batch-to-batch variations, and is easier to modify chemically than antibodies, thus potentially being used as therapeutic and biosensing agents. The current method for RNA aptamer identification in vitro uses the SELEX method, which is considered inefficient due to its complex process. Computational models of aptamers have been used to predict and study the molecular interaction of modified aptamers to improve affinity. In this study, we generated three-dimensional models of five RNA aptamers from their sequence using mFold, RNAComposer web server, and molecular dynamics simulation. The model structures were then evaluated and compared with the experimentally determined structures. This study showed that the combination of mFold, RNAComposer, and molecular dynamics simulation could generate 14-16, 28, or 29 nucleotides length of 3D RNA aptamer with similar geometry and topology to the experimentally determined structures. The non-canonical basepair structure of the aptamer loop was formed through the MD simulation, which also improved the three-dimensional RNA aptamers model. Clustering analysis was recommended to choose the more representative model. Aptamers are single-stranded DNA or RNA that bind to specific targets such as proteins, thus having similar characteristics to antibodies. It can be synthesized at a lower cost, with no batch-to-batch variations, and is easier to modify chemically than antibodies, thus potentially being used as therapeutic and biosensing agents. The current method for RNA aptamer identification in vitro uses the SELEX method, which is considered inefficient due to its complex process. Computational models of aptamers have been used to predict and study the molecular interaction of modified aptamers to improve affinity. In this study, we generated three-dimensional models of five RNA aptamers from their sequence using mFold, RNAComposer web server, and molecular dynamics simulation. The model structures were then evaluated and compared with the experimentally determined structures. This study showed that the combination of mFold, RNAComposer, and molecular dynamics simulation could generate 14-16, 28, or 29 nucleotides length of 3D RNA aptamer with similar geometry and topology to the experimentally determined structures. The non-canonical basepair structure of the aptamer loop was formed through the MD simulation, which also improved the three-dimensional RNA aptamers model. Clustering analysis was recommended to choose the more representative model.Aptamers are single-stranded DNA or RNA that bind to specific targets such as proteins, thus having similar characteristics to antibodies. It can be synthesized at a lower cost, with no batch-to-batch variations, and is easier to modify chemically than antibodies, thus potentially being used as therapeutic and biosensing agents. The current method for RNA aptamer identification in vitro uses the SELEX method, which is considered inefficient due to its complex process. Computational models of aptamers have been used to predict and study the molecular interaction of modified aptamers to improve affinity. In this study, we generated three-dimensional models of five RNA aptamers from their sequence using mFold, RNAComposer web server, and molecular dynamics simulation. The model structures were then evaluated and compared with the experimentally determined structures. This study showed that the combination of mFold, RNAComposer, and molecular dynamics simulation could generate 14-16, 28, or 29 nucleotides length of 3D RNA aptamer with similar geometry and topology to the experimentally determined structures. The non-canonical basepair structure of the aptamer loop was formed through the MD simulation, which also improved the three-dimensional RNA aptamers model. Clustering analysis was recommended to choose the more representative model. |
Audience | Academic |
Author | Satriawan, Ardianto Aditama, Reza Bethasari, Maulidwina Anshori, Isa Ropii, Bejo Shalannanda, Wervyan Setianingsih, Casi Koesoema, Allya Paramita Akbar, Mohammad Rizki |
AuthorAffiliation | 6 Biochemistry Research Group, Faculty of Mathematics and Natural Sciences, Bandung Institute of Technology, Bandung, West Java, Indonesia 2 Department of Pharmacy, Universitas Muhammadiyah Bandung, Bandung, West Java, Indonesia 4 Department of Computer Engineering, School of Electrical Engineering, Telkom University, Bandung Regency, West Java, Indonesia 5 Department of Cardiology and Vascular Medicine, Faculty of Medicine, Universitas Padjadjaran and Dr. Hasan Sadikin General Hospital, Bandung, West Java, Indonesia 1 School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, West Java, Indonesia Wake Forest University, UNITED STATES 3 Research Center for Nanosciences and Nanotechnology (RCNN), Bandung Institute of Technology, Bandung, West Java, Indonesia |
AuthorAffiliation_xml | – name: Wake Forest University, UNITED STATES – name: 3 Research Center for Nanosciences and Nanotechnology (RCNN), Bandung Institute of Technology, Bandung, West Java, Indonesia – name: 1 School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, West Java, Indonesia – name: 5 Department of Cardiology and Vascular Medicine, Faculty of Medicine, Universitas Padjadjaran and Dr. Hasan Sadikin General Hospital, Bandung, West Java, Indonesia – name: 2 Department of Pharmacy, Universitas Muhammadiyah Bandung, Bandung, West Java, Indonesia – name: 4 Department of Computer Engineering, School of Electrical Engineering, Telkom University, Bandung Regency, West Java, Indonesia – name: 6 Biochemistry Research Group, Faculty of Mathematics and Natural Sciences, Bandung Institute of Technology, Bandung, West Java, Indonesia |
Author_xml | – sequence: 1 givenname: Bejo orcidid: 0000-0001-7985-900X surname: Ropii fullname: Ropii, Bejo – sequence: 2 givenname: Maulidwina surname: Bethasari fullname: Bethasari, Maulidwina – sequence: 3 givenname: Isa surname: Anshori fullname: Anshori, Isa – sequence: 4 givenname: Allya Paramita surname: Koesoema fullname: Koesoema, Allya Paramita – sequence: 5 givenname: Wervyan orcidid: 0000-0002-4342-9718 surname: Shalannanda fullname: Shalannanda, Wervyan – sequence: 6 givenname: Ardianto surname: Satriawan fullname: Satriawan, Ardianto – sequence: 7 givenname: Casi surname: Setianingsih fullname: Setianingsih, Casi – sequence: 8 givenname: Mohammad Rizki surname: Akbar fullname: Akbar, Mohammad Rizki – sequence: 9 givenname: Reza orcidid: 0009-0006-1797-1059 surname: Aditama fullname: Aditama, Reza |
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CitedBy_id | crossref_primary_10_1016_j_heliyon_2024_e34183 crossref_primary_10_1186_s12896_024_00891_0 crossref_primary_10_3390_ijms242216318 crossref_primary_10_1016_j_microc_2024_109968 crossref_primary_10_1016_j_talanta_2025_127948 |
Cites_doi | 10.1093/nar/gki222 10.3390/ijms20102511 10.1021/ja060952q 10.1261/rna.1919010 10.1261/rna.031054.111 10.1016/j.jsb.2015.07.003 10.1093/nar/gku743 10.1093/nar/gks339 10.1126/science.2200121 10.1021/acsami.0c05750 10.1093/nar/gku330 10.1093/nar/gkp408 10.1002/jcc.23354 10.1021/bi982515x 10.3390/ijms18112442 10.1021/jp808357m 10.1002/prca.201200042 10.1038/346818a0 10.1261/rna.113106 10.1093/nar/gkm1141 10.1093/nar/gky314 10.1021/jp910226e |
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Snippet | Aptamers are single-stranded DNA or RNA that bind to specific targets such as proteins, thus having similar characteristics to antibodies. It can be... |
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SubjectTerms | Analysis Antibodies Aptamers Biology and life sciences Biosensors Cluster analysis Clustering DNA Dynamic structural analysis In vitro methods and tests Ligands Mathematical models Modelling Molecular dynamics Molecular interactions Monoclonal antibodies Nucleotide sequence Nucleotides Pharmacology Physical Sciences Proteins Research and Analysis Methods Ribonucleic acid RNA Servers Simulation Single-stranded DNA Sodium Three dimensional models Topology |
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Title | The assessment of molecular dynamics results of three-dimensional RNA aptamer structure prediction |
URI | https://www.ncbi.nlm.nih.gov/pubmed/37498889 https://www.proquest.com/docview/2842935328 https://www.proquest.com/docview/2844097185 https://pubmed.ncbi.nlm.nih.gov/PMC10373999 http://dx.doi.org/10.1371/journal.pone.0288684 |
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