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De novo 3D models of SARS-CoV-2 RNA elements from consensus experimental secondary structures.
Nucleic Acids Res. 2021 04 06; 49(6):3092-3108.NA

Abstract

The rapid spread of COVID-19 is motivating development of antivirals targeting conserved SARS-CoV-2 molecular machinery. The SARS-CoV-2 genome includes conserved RNA elements that offer potential small-molecule drug targets, but most of their 3D structures have not been experimentally characterized. Here, we provide a compilation of chemical mapping data from our and other labs, secondary structure models, and 3D model ensembles based on Rosetta's FARFAR2 algorithm for SARS-CoV-2 RNA regions including the individual stems SL1-8 in the extended 5' UTR; the reverse complement of the 5' UTR SL1-4; the frameshift stimulating element (FSE); and the extended pseudoknot, hypervariable region, and s2m of the 3' UTR. For eleven of these elements (the stems in SL1-8, reverse complement of SL1-4, FSE, s2m and 3' UTR pseudoknot), modeling convergence supports the accuracy of predicted low energy states; subsequent cryo-EM characterization of the FSE confirms modeling accuracy. To aid efforts to discover small molecule RNA binders guided by computational models, we provide a second set of similarly prepared models for RNA riboswitches that bind small molecules. Both datasets ('FARFAR2-SARS-CoV-2', https://github.com/DasLab/FARFAR2-SARS-CoV-2; and 'FARFAR2-Apo-Riboswitch', at https://github.com/DasLab/FARFAR2-Apo-Riboswitch') include up to 400 models for each RNA element, which may facilitate drug discovery approaches targeting dynamic ensembles of RNA molecules.

Authors+Show Affiliations

Biophysics Program, Stanford University, Stanford, CA 94305, USA.Department of Biochemistry, Stanford University School of Medicine, Stanford CA 94305, USA.Department of Biochemistry, Stanford University School of Medicine, Stanford CA 94305, USA.Biophysics Program, Stanford University, Stanford, CA 94305, USA.Department of Biochemistry, Stanford University School of Medicine, Stanford CA 94305, USA.Department of Biochemistry, Stanford University School of Medicine, Stanford CA 94305, USA.Eterna Massive Open Laboratory.Information Sciences Institute, University of Southern California, Marina Del Rey, CA 90292, USA.Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI 53706 USA.Biophysics Program, Stanford University, Stanford, CA 94305, USA. Department of Biochemistry, Stanford University School of Medicine, Stanford CA 94305, USA. Department of Physics, Stanford University, Stanford, CA 94305, USA.

Pub Type(s)

Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

Language

eng

PubMed ID

33693814

Citation

Rangan, Ramya, et al. "De Novo 3D Models of SARS-CoV-2 RNA Elements From Consensus Experimental Secondary Structures." Nucleic Acids Research, vol. 49, no. 6, 2021, pp. 3092-3108.
Rangan R, Watkins AM, Chacon J, et al. De novo 3D models of SARS-CoV-2 RNA elements from consensus experimental secondary structures. Nucleic Acids Res. 2021;49(6):3092-3108.
Rangan, R., Watkins, A. M., Chacon, J., Kretsch, R., Kladwang, W., Zheludev, I. N., Townley, J., Rynge, M., Thain, G., & Das, R. (2021). De novo 3D models of SARS-CoV-2 RNA elements from consensus experimental secondary structures. Nucleic Acids Research, 49(6), 3092-3108. https://doi.org/10.1093/nar/gkab119
Rangan R, et al. De Novo 3D Models of SARS-CoV-2 RNA Elements From Consensus Experimental Secondary Structures. Nucleic Acids Res. 2021 04 6;49(6):3092-3108. PubMed PMID: 33693814.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - De novo 3D models of SARS-CoV-2 RNA elements from consensus experimental secondary structures. AU - Rangan,Ramya, AU - Watkins,Andrew M, AU - Chacon,Jose, AU - Kretsch,Rachael, AU - Kladwang,Wipapat, AU - Zheludev,Ivan N, AU - Townley,Jill, AU - Rynge,Mats, AU - Thain,Gregory, AU - Das,Rhiju, PY - 2021/02/16/accepted PY - 2021/02/08/revised PY - 2020/12/16/received PY - 2021/3/12/pubmed PY - 2021/4/14/medline PY - 2021/3/11/entrez SP - 3092 EP - 3108 JF - Nucleic acids research JO - Nucleic Acids Res VL - 49 IS - 6 N2 - The rapid spread of COVID-19 is motivating development of antivirals targeting conserved SARS-CoV-2 molecular machinery. The SARS-CoV-2 genome includes conserved RNA elements that offer potential small-molecule drug targets, but most of their 3D structures have not been experimentally characterized. Here, we provide a compilation of chemical mapping data from our and other labs, secondary structure models, and 3D model ensembles based on Rosetta's FARFAR2 algorithm for SARS-CoV-2 RNA regions including the individual stems SL1-8 in the extended 5' UTR; the reverse complement of the 5' UTR SL1-4; the frameshift stimulating element (FSE); and the extended pseudoknot, hypervariable region, and s2m of the 3' UTR. For eleven of these elements (the stems in SL1-8, reverse complement of SL1-4, FSE, s2m and 3' UTR pseudoknot), modeling convergence supports the accuracy of predicted low energy states; subsequent cryo-EM characterization of the FSE confirms modeling accuracy. To aid efforts to discover small molecule RNA binders guided by computational models, we provide a second set of similarly prepared models for RNA riboswitches that bind small molecules. Both datasets ('FARFAR2-SARS-CoV-2', https://github.com/DasLab/FARFAR2-SARS-CoV-2; and 'FARFAR2-Apo-Riboswitch', at https://github.com/DasLab/FARFAR2-Apo-Riboswitch') include up to 400 models for each RNA element, which may facilitate drug discovery approaches targeting dynamic ensembles of RNA molecules. SN - 1362-4962 UR - https://www.unboundmedicine.com/medline/citation/33693814/De_novo_3D_models_of_SARS_CoV_2_RNA_elements_from_consensus_experimental_secondary_structures_ L2 - https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkab119 DB - PRIME DP - Unbound Medicine ER -