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Lee S, Yan S, Dey A, Laederach A, Schlick T. A Cascade of Conformational Switches in SARS-CoV-2 Frameshifting: Coregulation by Upstream and Downstream Elements. Biochemistry 2025; 64:953-966. [PMID: 39907285 PMCID: PMC11840926 DOI: 10.1021/acs.biochem.4c00641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2024] [Revised: 01/13/2025] [Accepted: 01/17/2025] [Indexed: 02/06/2025]
Abstract
Targeting ribosomal frameshifting has emerged as a potential therapeutic intervention strategy against COVID-19. In this process, a -1 shift in the ribosomal reading frame encodes alternative viral proteins. Any interference with this process profoundly affects viral replication and propagation. For SARS-CoV-2, two RNA sites associated with ribosomal frameshifting are positioned on the 5' and 3' of the frameshifting residues. Although much attention has been focused on the 3' frameshift element (FSE), the 5' stem-loop (attenuator hairpin, AH) can play a role. Yet the relationship between the two regions is unknown. In addition, multiple folds of the FSE and FSE-containing RNA regions have been discovered. To gain more insight into these RNA folds in the larger sequence context that includes AH, we apply our graph-theory-based modeling tools to represent RNA secondary structures, "RAG" (RNA-As-Graphs), to generate conformational landscapes that suggest length-dependent conformational distributions. We show that the AH region can coexist as a stem-loop with main and alternative 3-stem pseudoknots of the FSE (dual graphs 3_6 and 3_3 in our notation) but that an alternative stem 1 (AS1) can disrupt the FSE pseudoknots and trigger other folds. A critical length for AS1 of 10-bp regulates key folding transitions. Together with designed mutants and available experimental data, we present a sequential view of length-dependent folds during frameshifting and suggest their mechanistic roles. These structural and mutational insights into both ends of the FSE advance our understanding of the SARS-CoV-2 frameshifting mechanism by suggesting how alternative folds play a role in frameshifting and defining potential therapeutic intervention techniques that target specific folds.
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Affiliation(s)
- Samuel Lee
- Department
of Chemistry, New York University, New York, New York 10003, United States
| | - Shuting Yan
- Department
of Chemistry, New York University, New York, New York 10003, United States
| | - Abhishek Dey
- Department
of Biotechnology, National Institute of
Pharmaceutical Education and Research-Raebareli (NIPER-R), Lucknow, Uttar Pradesh 226002, India
| | - Alain Laederach
- Department
of Biology, University of North Carolina
at Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Tamar Schlick
- Department
of Chemistry, New York University, New York, New York 10003, United States
- Courant
Institute of Mathematical Sciences, New
York University, New York, New York 10012, United States
- NYU-ECNU
Center for Computational Chemistry, NYU
Shanghai, Shanghai 200062, PR China
- NYU Simons
Center for Computational Physical Chemistry, New York University, New York, New York 10003, United States
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2
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Bu F, Adam Y, Adamiak RW, Antczak M, de Aquino BRH, Badepally NG, Batey RT, Baulin EF, Boinski P, Boniecki MJ, Bujnicki JM, Carpenter KA, Chacon J, Chen SJ, Chiu W, Cordero P, Das NK, Das R, Dawson WK, DiMaio F, Ding F, Dock-Bregeon AC, Dokholyan NV, Dror RO, Dunin-Horkawicz S, Eismann S, Ennifar E, Esmaeeli R, Farsani MA, Ferré-D'Amaré AR, Geniesse C, Ghanim GE, Guzman HV, Hood IV, Huang L, Jain DS, Jaryani F, Jin L, Joshi A, Karelina M, Kieft JS, Kladwang W, Kmiecik S, Koirala D, Kollmann M, Kretsch RC, Kurciński M, Li J, Li S, Magnus M, Masquida B, Moafinejad SN, Mondal A, Mukherjee S, Nguyen THD, Nikolaev G, Nithin C, Nye G, Pandaranadar Jeyeram IPN, Perez A, Pham P, Piccirilli JA, Pilla SP, Pluta R, Poblete S, Ponce-Salvatierra A, Popenda M, Popenda L, Pucci F, Rangan R, Ray A, Ren A, Sarzynska J, Sha CM, Stefaniak F, Su Z, Suddala KC, Szachniuk M, Townshend R, Trachman RJ, Wang J, Wang W, Watkins A, Wirecki TK, Xiao Y, Xiong P, Xiong Y, Yang J, Yesselman JD, Zhang J, Zhang Y, Zhang Z, Zhou Y, Zok T, Zhang D, Zhang S, Żyła A, Westhof E, Miao Z. RNA-Puzzles Round V: blind predictions of 23 RNA structures. Nat Methods 2025; 22:399-411. [PMID: 39623050 PMCID: PMC11810798 DOI: 10.1038/s41592-024-02543-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 10/29/2024] [Indexed: 01/16/2025]
Abstract
RNA-Puzzles is a collective endeavor dedicated to the advancement and improvement of RNA three-dimensional structure prediction. With agreement from structural biologists, RNA structures are predicted by modeling groups before publication of the experimental structures. We report a large-scale set of predictions by 18 groups for 23 RNA-Puzzles: 4 RNA elements, 2 Aptamers, 4 Viral elements, 5 Ribozymes and 8 Riboswitches. We describe automatic assessment protocols for comparisons between prediction and experiment. Our analyses reveal some critical steps to be overcome to achieve good accuracy in modeling RNA structures: identification of helix-forming pairs and of non-Watson-Crick modules, correct coaxial stacking between helices and avoidance of entanglements. Three of the top four modeling groups in this round also ranked among the top four in the CASP15 contest.
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Grants
- T32 GM066706 NIGMS NIH HHS
- NSFC T2225007 National Natural Science Foundation of China (National Science Foundation of China)
- R35 GM134919 NIGMS NIH HHS
- R35GM145409 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- R35 GM145409 NIGMS NIH HHS
- 32270707 National Natural Science Foundation of China (National Science Foundation of China)
- R35 GM122579 NIGMS NIH HHS
- R35 GM134864 NIGMS NIH HHS
- T32 grant GM066706 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- P20GM121342 Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
- R21 CA219847 NCI NIH HHS
- 32171191 National Natural Science Foundation of China (National Science Foundation of China)
- P20 GM121342 NIGMS NIH HHS
- R35 GM152029 NIGMS NIH HHS
- R01 GM073850 NIGMS NIH HHS
- F32 GM112294 NIGMS NIH HHS
- ZIA DK075136 Intramural NIH HHS
- Z.M. is supported by Major Projects of Guangzhou National Laboratory, (Grant No. GZNL2023A01006, GZNL2024A01002, SRPG22-003, SRPG22-006, SRPG22-007, HWYQ23-003, YW-YFYJ0102), the National Key R&D Programs of China (2023YFF1204700, 2023YFF1204701, 2021YFF1200900, 2021YFF1200903). This work is part of the ITI 2021-2028 program and supported by IdEx Unistra (ANR-10-IDEX-0002 to E.W.), SFRI-STRAT’US project (ANR-20-SFRI-0012) and EUR IMCBio (IMCBio ANR-17-EURE-0023 to E.W.) under the framework of the French Investments for the Future Program.
- E.W. acknowledges also support from Wenzhou Institute, University of Chinese Academy of Sciences (WIUCASQD2024002).
- E.F.B. was additionally supported by European Molecular Biology Organization (EMBO) fellowship (ALTF 525-2022).
- Boniecki’s research was supported by the Polish National Science Center Poland (NCN) (grant 2016/23/B/ST6/03433 to Michal J. Boniecki). Predictions were performed using computational resources of the Interdisciplinary Centre for Mathematical and Computational Modelling of the University of Warsaw (ICM) (grant G66-9).
- J.M.B. is supported by the National Science Centre in Poland (NCN grants: 2017/26/A/NZ1/01083 to J.M.B., 2021/43/D/NZ1/03360 to S.M., 2020/39/B/NZ2/03127 to F.S., 2020/39/D/NZ2/02837 to T.K.W.). J.M.B. acknowledge Poland high-performance computing Infrastructure PLGrid (HPC Centers: ACK Cyfronet AGH, PCSS, CI TASK, WCSS) for providing computer facilities and support within the computational grant PLG/2023/016080.
- S.J.C. is supported by the National Institutes of Health under Grant R35-GM134919.
- R.D. is supported by Stanford Bio-X (to R.D., R.O.D., R.C.K., and S.E.); Stanford Gerald J. Lieberman Fellowship (to R.R.); the National Institutes of Health (R21 CA219847 and R35 GM122579 to R.D.), the Howard Hughes Medical Institute (HHMI, to R.D.); Consejo Nacional de Ciencia y Tecnología CONACyT Fellowship 312765 (P.C.); the Ruth L. Kirschstein National Research Service Award Postdoctoral Fellowships GM112294 (to J.D.Y.); National Science Foundation Graduate Research Fellowships (R.J.L.T. and R.R.); the National Library of Medicine T15 Training Grant (NLM T15007033 to K.A.C.); the U.S. Department of Energy, Office of Science Graduate Student Research program (R.J.L.T.).
- The National Institutes of Health grants 1R35 GM134864 and the Passan Foundation.
- R.O.D. is supported by the U.S. Department of Energy, Office of Science, Scientific Discovery through Advanced Computing (SciDAC) program (R.O.D.); Intel (R.O.D.).
- A.F.D. is supported, in part, by the intramural program of the National Heart, Lung and Blood Institute, National Institutes of Health, USA.
- Guangdong Science and Technology Department (2022A1515010328, 2023B1212060013, 2020B1212030004), Fundamental Research Funds for the Central Universities, Sun Yat-sen University (23ptpy41).
- D.K. is supported by the NSF CAREER award MCB-2236996, and start-up, SURFF, and START awards from the University of Maryland Baltimore County to D.K.
- BM is supported by the Interdisciplinary Thematic Institute IMCBio, as part of the ITI 2021-2028 program at the University of Strasbourg, CNRS and Inserm, by IdEx Unistra (ANR-10-IDEX-0002), and EUR (IMCBio ANR-17-EUR-0023), under the framework of the French Investments Program for the Future.
- T.H.D.N. is supported by UKRI-Medical Research Council grant MC_UP_1201/19.
- C.N. and M.K. acknowledge funding from the National Science Centre, Poland [OPUS 2019/33/B/NZ2/02100]; S.P.P. acknowledges funding from the National Science Centre, Poland [OPUS 2020/39/B/NZ2/01301]; S.K. acknowledges funding from the National Science Centre, Poland [Sheng 2021/40/Q/NZ2/00078]; C.N. acknowledge Polish high-performance computing infrastructure PLGrid (HPC Centers: PCSS, ACK Cyfronet AGH, CI TASK, WCSS) for providing computer facilities and support within the computational grants PLG/2022/016043, PLG/2022/015327 and PLG/2020/013424.
- AP is supported by an NSF-CAREER award CHE-2235785
- A.R. is supported by grants from the Natural Science Foundation of China (32325029, 32022039, 91940302, and 91640104), the National Key Research and Development Project of China (2021YFC2300300 and 2023YFC2604300).
- Marta Szachniuk are supported by the National Science Centre, Poland (2019/35/B/ST6/03074 to M.S.), the statutory funds of IBCH PAS and Poznan University of Technology.
- J.W. is supported by the Penn State College of Medicine’s Artificial Intelligence and Biomedical Informatics Program.
- J.Z. is supported by the Intramural Research Program of the NIH, the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) (ZIADK075136 to J.Z.), and an NIH Deputy Director for Intramural Research (DDIR) Challenge Award to J.Z.
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Affiliation(s)
- Fan Bu
- GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macao Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, China
- School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Yagoub Adam
- Inter-institutional Graduate Program on Bioinformatics, Department of Computer Science and Mathematics, FFCLRP, University of São Paulo, Ribeirão Preto, Brazil
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Nigeria
| | - Ryszard W Adamiak
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
- Institute of Computing Science, Poznan University of Technology, Poznan, Poland
| | - Maciej Antczak
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
- Institute of Computing Science, Poznan University of Technology, Poznan, Poland
| | - Belisa Rebeca H de Aquino
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Nagendar Goud Badepally
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Robert T Batey
- Department of Biochemistry, University of Colorado at Boulder, Boulder, CO, USA
| | - Eugene F Baulin
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Pawel Boinski
- Institute of Computing Science, Poznan University of Technology, Poznan, Poland
| | - Michal J Boniecki
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Janusz M Bujnicki
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Kristy A Carpenter
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Jose Chacon
- Department of Biochemistry, Stanford University, Stanford, CA, USA
- Department of Cell and Developmental Biology, University of California San Diego, San Diego, CA, USA
| | - Shi-Jie Chen
- Department of Physics, Department of Biochemistry and Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA
| | - Wah Chiu
- Department of Bioengineering and James H. Clark Center, Stanford University, Stanford, CA, USA
| | - Pablo Cordero
- Department of Biochemistry, Stanford University, Stanford, CA, USA
- Stripe, South San Francisco, CA, USA
| | - Naba Krishna Das
- Department of Chemistry and Biochemistry, University of Maryland Baltimore County, Baltimore, MD, USA
| | - Rhiju Das
- Department of Biochemistry, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
- Biophysics program, Stanford University, Stanford, CA, USA
| | - Wayne K Dawson
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Frank DiMaio
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Feng Ding
- Department of Physics and Astronomy, Clemson University, Clemson, SC, USA
| | - Anne-Catherine Dock-Bregeon
- Laboratory of Integrative Biology of Marine Models (LBI2M), Sorbonne University-CNRS UMR8227, Roscoff, France
| | - Nikolay V Dokholyan
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
| | - Ron O Dror
- Department of Computer Science, Stanford University, Stanford, CA, USA
- Department of Structural Biology, Stanford University, Stanford, CA, USA
- Department of Molecular and Cellular Physiology, Stanford University, Stanford, CA, USA
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
| | - Stanisław Dunin-Horkawicz
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Stephan Eismann
- Department of Applied Physics, Stanford University, Stanford, CA, USA
- Atomic AI, South San Francisco, CA, USA
| | - Eric Ennifar
- Architecture et Réactivité de l'ARN, Institut de Biologie Moléculaire et Cellulaire du CNRS, Université de Strasbourg, Strasbourg, France
| | - Reza Esmaeeli
- Department of Chemistry and Quantum Theory Project, University of Florida, Gainesville, FL, USA
| | - Masoud Amiri Farsani
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Adrian R Ferré-D'Amaré
- Laboratory of Nucleic Acids, National Heart, Lung and Blood Institute, Bethesda, MD, USA
| | - Caleb Geniesse
- Department of Biochemistry, Stanford University, Stanford, CA, USA
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - George E Ghanim
- Medical Research Council Laboratory of Molecular Biology, Cambridge, UK
| | - Horacio V Guzman
- Instituto de Ciencia de Materials de Barcelona, ICMAB-CSIC, Bellaterra E-08193, Spain & Departamento de Física Teórica de la Materia Condensada, Universidad Autónoma de Madrid, Madrid, Spain
| | - Iris V Hood
- Laboratory of Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA
| | - Lin Huang
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University Guangzhou, Guangdong, China
| | - Dharm Skandh Jain
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Farhang Jaryani
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Lei Jin
- Department of Physics, Department of Biochemistry and Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA
| | - Astha Joshi
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Masha Karelina
- Biophysics program, Stanford University, Stanford, CA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Jeffrey S Kieft
- Department of Biochemistry and Molecular Genetics, University of Colorado Denver School of Medicine, Aurora, CO, USA
- New York Structural Biology Center, New York, NY, USA
| | - Wipapat Kladwang
- Department of Biochemistry, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
| | - Sebastian Kmiecik
- Laboratory of Computational Biology, Biological and Chemical Research Center, Faculty of Chemistry, University of Warsaw, Warsaw, Poland
| | - Deepak Koirala
- Department of Chemistry and Biochemistry, University of Maryland Baltimore County, Baltimore, MD, USA
| | - Markus Kollmann
- Department of Computer Science, Heinrich Heine University of Düsseldorf, Düsseldorf, Germany
| | | | - Mateusz Kurciński
- Laboratory of Computational Biology, Biological and Chemical Research Center, Faculty of Chemistry, University of Warsaw, Warsaw, Poland
| | - Jun Li
- Department of Physics, Department of Biochemistry and Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA
| | - Shuang Li
- Laboratory of Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA
| | - Marcin Magnus
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA
| | - BenoÎt Masquida
- UMR 7156, CNRS - Université de Strasbourg, IPCB, Strasbourg, France
| | - S Naeim Moafinejad
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Arup Mondal
- Department of Chemistry and Quantum Theory Project, University of Florida, Gainesville, FL, USA
| | - Sunandan Mukherjee
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | | | - Grigory Nikolaev
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Chandran Nithin
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
- Laboratory of Computational Biology, Biological and Chemical Research Center, Faculty of Chemistry, University of Warsaw, Warsaw, Poland
| | - Grace Nye
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
| | - Iswarya P N Pandaranadar Jeyeram
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Alberto Perez
- Department of Chemistry and Quantum Theory Project, University of Florida, Gainesville, FL, USA
| | - Phillip Pham
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
| | - Joseph A Piccirilli
- Department of Biochemistry and Molecular Biology, The University of Chicago, Chicago, IL, USA
- Department of Chemistry, The University of Chicago, Chicago, IL, USA
| | - Smita Priyadarshini Pilla
- Laboratory of Computational Biology, Biological and Chemical Research Center, University of Warsaw, Warsaw, Poland
| | - Radosław Pluta
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Simón Poblete
- Facultad de Ingeniería, Arquitectura y Diseño, Universidad San Sebastián, Santiago, Chile
- Centro BASAL Ciencia & Vida, Universidad San Sebastián, Santiago, Chile
| | - Almudena Ponce-Salvatierra
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Mariusz Popenda
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
| | - Lukasz Popenda
- NanoBioMedical Centre, Adam Mickiewicz University, Poznan, Poland
| | - Fabrizio Pucci
- Computational Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, Belgium
| | - Ramya Rangan
- Biophysics program, Stanford University, Stanford, CA, USA
- Atomic AI, South San Francisco, CA, USA
| | - Angana Ray
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Aiming Ren
- Life Sciences Institute, Zhejiang University, Hangzhou, China
| | - Joanna Sarzynska
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
| | - Congzhou Mike Sha
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
| | - Filip Stefaniak
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Zhaoming Su
- The State Key Laboratory of Biotherapy, West China Hospital, Chengdu, China
| | - Krishna C Suddala
- Laboratory of Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA
| | - Marta Szachniuk
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
- Institute of Computing Science, Poznan University of Technology, Poznan, Poland
| | - Raphael Townshend
- Department of Computer Science, Stanford University, Stanford, CA, USA
- Atomic AI, South San Francisco, CA, USA
| | - Robert J Trachman
- Laboratory of Nucleic Acids, National Heart, Lung and Blood Institute, Bethesda, MD, USA
| | - Jian Wang
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
| | - Wenkai Wang
- MOE Frontiers Science Center for Nonlinear Expectations, Research Center for Mathematics and Interdisciplinary Sciences, Shandong University, Qingdao, China
| | - Andrew Watkins
- Department of Biochemistry, Stanford University, Stanford, CA, USA
- Prescient Design, Genentech Research and Early Development, South San Francisco, CA, USA
| | - Tomasz K Wirecki
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Yi Xiao
- School of Physics and Key Laboratory of Molecular Biophysics of the Ministry of Education, Huazhong University of Science and Technology, Wuhan, China
| | - Peng Xiong
- School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Department of Biomedical Engineering, Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, China
| | - Yiduo Xiong
- School of Physics and Key Laboratory of Molecular Biophysics of the Ministry of Education, Huazhong University of Science and Technology, Wuhan, China
| | - Jianyi Yang
- MOE Frontiers Science Center for Nonlinear Expectations, Research Center for Mathematics and Interdisciplinary Sciences, Shandong University, Qingdao, China
| | - Joseph David Yesselman
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
- Department of Chemistry, University of Nebraska, Lincoln, NE, USA
| | - Jinwei Zhang
- Laboratory of Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA
| | - Yi Zhang
- School of Physics and Key Laboratory of Molecular Biophysics of the Ministry of Education, Huazhong University of Science and Technology, Wuhan, China
| | - Zhenzhen Zhang
- Department of Physics and Astronomy, Clemson University, Clemson, SC, USA
| | - Yuanzhe Zhou
- Department of Physics, Department of Biochemistry and Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA
| | - Tomasz Zok
- Institute of Computing Science, Poznan University of Technology, Poznan, Poland
| | - Dong Zhang
- Department of Physics, Department of Biochemistry and Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA
| | - Sicheng Zhang
- Department of Physics, Department of Biochemistry and Institute for Data Science and Informatics, University of Missouri, Columbia, MO, USA
| | - Adriana Żyła
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Eric Westhof
- Architecture et Réactivité de l'ARN, Institut de Biologie Moléculaire et Cellulaire du CNRS, Université de Strasbourg, Strasbourg, France.
- Engineering Research Center of Clinical Functional Materials and Diagnosis & Treatment Devices of Zhejiang Province, Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, China.
| | - Zhichao Miao
- GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macao Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, China.
- Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Clinical Research Center for Anesthesiology and Perioperative Medicine, Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
- European Bioinformatics Institute, European Molecular Biology Laboratory, Wellcome Genome Campus, Cambridge, UK.
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3
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Huang X, Du Z. Elaborated pseudoknots that stimulate -1 programmed ribosomal frameshifting or stop codon readthrough in RNA viruses. J Biomol Struct Dyn 2025; 43:1566-1578. [PMID: 38095458 PMCID: PMC11176267 DOI: 10.1080/07391102.2023.2292296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 11/25/2023] [Indexed: 05/08/2024]
Abstract
Pseudoknots assume various functions including stimulation of -1 programmed ribosomal frameshifting (PRF) or stop codon readthrough (SCR) in RNA viruses. These pseudoknots vary greatly in sizes and structural complexities. Recent biochemical and structural studies confirm the three-stemmed pseudoknots as the -1 PRF stimulators in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and related coronaviruses. We reexamined previously reported -1 PRF or SCR stimulating pseudoknots, especially those containing a relatively long connecting loop between the two pseudoknot-forming stems, for their ability to form elaborated structures. Many potential elaborated pseudoknots were identified that contain one or more of the following extra structural elements: stem-loop, embedded pseudoknot, kissing hairpins, and additional loop-loop interactions. The elaborated pseudoknots are found in several different virus families that utilize either the -1 PRF or SCR recoding mechanisms. Model-building studies were performed to not only establish the structural feasibility of the elaborated pseudoknots but also reveal potential additional structural features that cannot be readily inferred from the predicted secondary structures. Some of the structures, such as embedded double pseudoknots and compact loop-loop pseudoknots mediated by the previously established common pseudoknot motif-1 (CPK-1), represent the first of its kind in the literatures. By advancing discovery of new functional RNA structures, we significantly expand the repertoire of known elaborated pseudoknots that could potentially play a role in -1 PRF and SCR regulation. These results contribute to a better understanding of RNA structures in general, facilitating the design of engineering RNA molecules with certain desired functions.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Xiaolan Huang
- School of Computing, Southern Illinois University at Carbondale, IL 62901, USA
| | - Zhihua Du
- School of Chemical and Biomolecular Sciences, Southern Illinois University at Carbondale, IL 62901, USA
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4
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Ceylan B, Adam J, Toews S, Kaiser F, Dörr J, Scheppa D, Tants JN, Smart A, Schoth J, Philipp S, Stirnal E, Ferner J, Richter C, Sreeramulu S, Caliskan N, Schlundt A, Weigand JE, Göbel M, Wacker A, Schwalbe H. Optimization of Structure-Guided Development of Chemical Probes for the Pseudoknot RNA of the Frameshift Element in SARS-CoV-2. Angew Chem Int Ed Engl 2025:e202417961. [PMID: 39887818 DOI: 10.1002/anie.202417961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2024] [Revised: 12/12/2024] [Accepted: 01/28/2025] [Indexed: 02/01/2025]
Abstract
Targeting the RNA genome of SARS-CoV-2 is a viable option for antiviral drug development. We explored three ligand binding sites of the core pseudoknot RNA of the SARS-CoV-2 frameshift element. We iteratively optimized ligands, based on improved affinities, targeting these binding sites and report on structural and dynamic properties of the three identified binding sites. Available experimental 3D structures of the pseudoknot element were compared to SAXS and NMR data to validate its dominant folding state in solution. In order to experimentally map in silico predicted binding sites, NMR assignments of the majority of nucleobases were achieved by segmental labeling of the pseudoknot RNA and isotope-filtered NMR experiments at 1.2 GHz, demonstrating the value of NMR spectroscopy to supplement modelling and docking data. Optimized ligands with enhanced affinity were shown to specifically inhibit frameshifting without affecting 0-frame translation in cell-free translation assays, establishing the frameshift element as target for drug-like ligands of low molecular weight.
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Affiliation(s)
- Betül Ceylan
- Institute for Organic Chemistry and Chemical Biology, Goethe University Frankfurt, Max-von-Laue-Straße 7, 60438, Frankfurt am Main, Germany
- Center of Biomolecular Magnetic Resonance (BMRZ), Goethe University Frankfurt, Max-von-Laue-Straße 9, 60438, Frankfurt am Main, Germany
| | - Jennifer Adam
- Institute for Organic Chemistry and Chemical Biology, Goethe University Frankfurt, Max-von-Laue-Straße 7, 60438, Frankfurt am Main, Germany
- Center of Biomolecular Magnetic Resonance (BMRZ), Goethe University Frankfurt, Max-von-Laue-Straße 9, 60438, Frankfurt am Main, Germany
| | - Sabrina Toews
- Institute for Organic Chemistry and Chemical Biology, Goethe University Frankfurt, Max-von-Laue-Straße 7, 60438, Frankfurt am Main, Germany
- Center of Biomolecular Magnetic Resonance (BMRZ), Goethe University Frankfurt, Max-von-Laue-Straße 9, 60438, Frankfurt am Main, Germany
| | - Frank Kaiser
- Institute for Organic Chemistry and Chemical Biology, Goethe University Frankfurt, Max-von-Laue-Straße 7, 60438, Frankfurt am Main, Germany
- Center of Biomolecular Magnetic Resonance (BMRZ), Goethe University Frankfurt, Max-von-Laue-Straße 9, 60438, Frankfurt am Main, Germany
| | - Jonas Dörr
- Institute for Organic Chemistry and Chemical Biology, Goethe University Frankfurt, Max-von-Laue-Straße 7, 60438, Frankfurt am Main, Germany
| | - Daniel Scheppa
- Institute for Organic Chemistry and Chemical Biology, Goethe University Frankfurt, Max-von-Laue-Straße 7, 60438, Frankfurt am Main, Germany
| | - Jan-Niklas Tants
- Center of Biomolecular Magnetic Resonance (BMRZ), Goethe University Frankfurt, Max-von-Laue-Straße 9, 60438, Frankfurt am Main, Germany
- Institute for Molecular Biosciences, Goethe University Frankfurt, Max-von-Laue-Straße 9, 60438, Frankfurt am Main, Germany
| | - Alexandria Smart
- Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research (HIRI-HZI), Josef-Schneider-Straße 2/D15, 97080, Würzburg, Germany
- Regensburg Center for Biochemistry (RCB), University of Regensburg, Universitätsstraße 31, 93053, Regensburg
| | - Julian Schoth
- Institute of Pharmaceutical Chemistry, University of Marburg, 35032, Marburg, Germany
| | - Susanne Philipp
- Institute of Pharmaceutical Chemistry, University of Marburg, 35032, Marburg, Germany
| | - Elke Stirnal
- Institute for Organic Chemistry and Chemical Biology, Goethe University Frankfurt, Max-von-Laue-Straße 7, 60438, Frankfurt am Main, Germany
- Center of Biomolecular Magnetic Resonance (BMRZ), Goethe University Frankfurt, Max-von-Laue-Straße 9, 60438, Frankfurt am Main, Germany
| | - Jan Ferner
- Institute for Organic Chemistry and Chemical Biology, Goethe University Frankfurt, Max-von-Laue-Straße 7, 60438, Frankfurt am Main, Germany
- Center of Biomolecular Magnetic Resonance (BMRZ), Goethe University Frankfurt, Max-von-Laue-Straße 9, 60438, Frankfurt am Main, Germany
| | - Christian Richter
- Institute for Organic Chemistry and Chemical Biology, Goethe University Frankfurt, Max-von-Laue-Straße 7, 60438, Frankfurt am Main, Germany
- Center of Biomolecular Magnetic Resonance (BMRZ), Goethe University Frankfurt, Max-von-Laue-Straße 9, 60438, Frankfurt am Main, Germany
| | - Sridhar Sreeramulu
- Institute for Organic Chemistry and Chemical Biology, Goethe University Frankfurt, Max-von-Laue-Straße 7, 60438, Frankfurt am Main, Germany
- Center of Biomolecular Magnetic Resonance (BMRZ), Goethe University Frankfurt, Max-von-Laue-Straße 9, 60438, Frankfurt am Main, Germany
| | - Neva Caliskan
- Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research (HIRI-HZI), Josef-Schneider-Straße 2/D15, 97080, Würzburg, Germany
- Regensburg Center for Biochemistry (RCB), University of Regensburg, Universitätsstraße 31, 93053, Regensburg
| | - Andreas Schlundt
- Center of Biomolecular Magnetic Resonance (BMRZ), Goethe University Frankfurt, Max-von-Laue-Straße 9, 60438, Frankfurt am Main, Germany
- Institute for Molecular Biosciences, Goethe University Frankfurt, Max-von-Laue-Straße 9, 60438, Frankfurt am Main, Germany
- Institute of Biochemistry, University of Greifswald, 17489, Greifswald, Germany
| | - Julia E Weigand
- Institute of Pharmaceutical Chemistry, University of Marburg, 35032, Marburg, Germany
| | - Michael Göbel
- Institute for Organic Chemistry and Chemical Biology, Goethe University Frankfurt, Max-von-Laue-Straße 7, 60438, Frankfurt am Main, Germany
| | - Anna Wacker
- Institute for Organic Chemistry and Chemical Biology, Goethe University Frankfurt, Max-von-Laue-Straße 7, 60438, Frankfurt am Main, Germany
- Center of Biomolecular Magnetic Resonance (BMRZ), Goethe University Frankfurt, Max-von-Laue-Straße 9, 60438, Frankfurt am Main, Germany
| | - Harald Schwalbe
- Institute for Organic Chemistry and Chemical Biology, Goethe University Frankfurt, Max-von-Laue-Straße 7, 60438, Frankfurt am Main, Germany
- Center of Biomolecular Magnetic Resonance (BMRZ), Goethe University Frankfurt, Max-von-Laue-Straße 9, 60438, Frankfurt am Main, Germany
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5
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Yan S, Schlick T. Heterogeneous and multiple conformational transition pathways between pseudoknots of the SARS-CoV-2 frameshift element. Proc Natl Acad Sci U S A 2025; 122:e2417479122. [PMID: 39854230 PMCID: PMC11789066 DOI: 10.1073/pnas.2417479122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2024] [Accepted: 11/25/2024] [Indexed: 01/26/2025] Open
Abstract
Frameshifting is an essential mechanism employed by many viruses including coronaviruses to produce viral proteins from a compact RNA genome. It is facilitated by specific RNA folds in the frameshift element (FSE), which has emerged as an important therapeutic target. For SARS-CoV-2, a specific 3-stem pseudoknot has been identified to stimulate frameshifting. However, prior studies and our RNA-As-Graphs analysis coupled to chemical reactivity experiments revealed other folds, including a different pseudoknot. Although structural plasticity has been proposed to play a key role in frameshifting, paths between different FSE RNA folds have not been yet identified. Here, we capture atomic-level transition pathways between two key FSE pseudoknots by transition path sampling coupled to Markov State Modeling and our BOLAS free energy method. We reveal multiple transition paths within a heterogeneous, multihub conformational landscape. A shared folding mechanism involves RNA stem unpairing followed by a 5'-chain end release. Significantly, this pseudoknot transition critically tunes the tension through the RNA spacer region and places the viral RNA in the narrow ribosomal channel. Our work further explains the role of the alternative pseudoknot in ribosomal pausing and clarifies why the experimentally captured pseudoknot is preferred for frameshifting. Our capturing of this large-scale transition of RNA secondary and tertiary structure highlights the complex pathways of biomolecules and the inherent multifarious aspects that viruses developed to ensure virulence and survival. This enhanced understanding of viral frameshifting also provides insights to target key transitions for therapeutic applications. Our methods are generally applicable to other large-scale biomolecular transitions.
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Affiliation(s)
- Shuting Yan
- Department of Chemistry, New York University, New York, NY10003
| | - Tamar Schlick
- Department of Chemistry, New York University, New York, NY10003
- Department of Mathematics and Computer Science, Courant Institute of Mathematical Sciences, New York University, New York, NY10012
- New York University - East China Normal University Center for Computational Chemistry, NYU Shanghai, Shanghai200062, People’s Republic of China
- Simons Center for Computational Physical Chemistry, New York University, New York, NY10003
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6
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Gray M, Trinity L, Stege U, Ponty Y, Will S, Jabbari H. CParty: hierarchically constrained partition function of RNA pseudoknots. Bioinformatics 2024; 41:btae748. [PMID: 39700413 PMCID: PMC11709253 DOI: 10.1093/bioinformatics/btae748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2024] [Revised: 11/28/2024] [Accepted: 12/17/2024] [Indexed: 12/21/2024] Open
Abstract
MOTIVATION Biologically relevant RNA secondary structures are routinely predicted by efficient dynamic programming algorithms that minimize their free energy. Starting from such algorithms, one can devise partition function algorithms, which enable stochastic perspectives on RNA structure ensembles. As the most prominent example, McCaskill's partition function algorithm is derived from pseudoknot-free energy minimization. While this algorithm became hugely successful for the analysis of pseudoknot-free RNA structure ensembles, as of yet there exists only one pseudoknotted partition function implementation, which covers only simple pseudoknots and comes with a borderline-prohibitive complexity of O(n5) in the RNA length n. RESULTS Here, we develop a partition function algorithm corresponding to the hierarchical pseudoknot prediction of HFold, which performs exact optimization in a realistic pseudoknot energy model. In consequence, our algorithm CParty carries over HFold's advantages over classical pseudoknot prediction in characterizing the Boltzmann ensemble at equilibrium. Given an RNA sequence S and a pseudoknot-free structure G, CParty computes the partition function over all possibly pseudoknotted density-2 structures G∪G' of S that extend the fixed G by a disjoint pseudoknot-free structure G'. Thus, CParty follows the common hypothesis of hierarchical pseudoknot formation, where pseudoknots form as tertiary contacts only after a first pseudoknot-free "core" G and we call the computed partition function hierarchically constrained (by G). Like HFold, the dynamic programming algorithm CParty is very efficient, achieving the low complexity of the pseudoknot-free algorithm, i.e. cubic time and quadratic space. Finally, by computing pseudoknotted ensemble energies, we unveil kinetics features of a therapeutic target in SARS-CoV-2. AVAILABILITY AND IMPLEMENTATION CParty is available at https://github.com/HosnaJabbari/CParty.
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Affiliation(s)
- Mateo Gray
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta T6G 1H9, Canada
| | - Luke Trinity
- Department of Computer Science, University of Victoria, Victoria, British Columbia V8P 5C2, Canada
| | - Ulrike Stege
- Department of Computer Science, University of Victoria, Victoria, British Columbia V8P 5C2, Canada
| | - Yann Ponty
- Institut Polytechnique de Paris, 91120 Palaiseau, Paris, France
| | - Sebastian Will
- Institut Polytechnique de Paris, 91120 Palaiseau, Paris, France
| | - Hosna Jabbari
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta T6G 1H9, Canada
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7
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Iannuzzelli JA, Bonn R, Hong AS, Anitha AS, Jenkins JL, Wedekind JE, Fasan R. Cyclic peptides targeting the SARS-CoV-2 programmed ribosomal frameshifting RNA from a multiplexed phage display library. Chem Sci 2024; 15:19520-19533. [PMID: 39568906 PMCID: PMC11575553 DOI: 10.1039/d4sc04026k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2024] [Accepted: 10/03/2024] [Indexed: 11/22/2024] Open
Abstract
RNA provides the genetic blueprint for many pathogenic viruses, including SARS-CoV-2. The propensity of RNA to fold into specific tertiary structures enables the biomolecular recognition of cavities and crevices suited for the binding of drug-like molecules. Despite increasing interest in RNA as a target for chemical biology and therapeutic applications, the development of molecules that recognize RNA with high affinity and specificity represents a significant challenge. Here, we report a strategy for the discovery and selection of RNA-targeted macrocyclic peptides derived from combinatorial libraries of peptide macrocycles displayed by bacteriophages. Specifically, a platform for phage display of macrocyclic organo-peptide hybrids (MOrPH-PhD) was combined with a diverse set of non-canonical amino acid-based cyclization modules to produce large libraries of 107 structurally diverse, genetically encoded peptide macrocycles. These libraries were panned against the -1 programmed ribosomal frameshifting stimulatory sequence (FSS) RNA pseudoknot of SARS-CoV-2, which revealed specific macrocyclic peptide sequences that bind this essential motif with high affinity and selectivity. Peptide binding localizes to the FSS dimerization loop based on chemical modification analysis and binding assays and the cyclic peptides show specificity toward the target RNA over unrelated RNA pseudoknots. This work introduces a novel system for the generation and high-throughput screening of topologically diverse cyclopeptide scaffolds (multiplexed MOrPH-PhD), and it provides a blueprint for the exploration and evolution of genetically encoded macrocyclic peptides that target specific RNAs.
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Affiliation(s)
| | - Rachel Bonn
- Department of Biochemistry and Biophysics, University of Rochester School of Medicine and Dentistry Rochester NY 14642 USA
- Center for RNA Biology, University of Rochester School of Medicine and Dentistry Rochester NY 14642 USA
| | - Andrew S Hong
- Department of Chemistry, University of Rochester Rochester NY 14627 USA
| | - Abhijith Saseendran Anitha
- Department of Chemistry, University of Rochester Rochester NY 14627 USA
- Department of Chemistry & Biochemistry, The University of Texas at Dallas Richardson TX 75080 USA
| | - Jermaine L Jenkins
- Department of Biochemistry and Biophysics, University of Rochester School of Medicine and Dentistry Rochester NY 14642 USA
- Center for RNA Biology, University of Rochester School of Medicine and Dentistry Rochester NY 14642 USA
| | - Joseph E Wedekind
- Department of Biochemistry and Biophysics, University of Rochester School of Medicine and Dentistry Rochester NY 14642 USA
- Center for RNA Biology, University of Rochester School of Medicine and Dentistry Rochester NY 14642 USA
| | - Rudi Fasan
- Department of Chemistry, University of Rochester Rochester NY 14627 USA
- Department of Chemistry & Biochemistry, The University of Texas at Dallas Richardson TX 75080 USA
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8
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Mertinkus K, Oxenfarth A, Richter C, Wacker A, Mata CP, Carazo JM, Schlundt A, Schwalbe H. Dissecting the Conformational Heterogeneity of Stem-Loop Substructures of the Fifth Element in the 5'-Untranslated Region of SARS-CoV-2. J Am Chem Soc 2024; 146:30139-30154. [PMID: 39442924 PMCID: PMC11544613 DOI: 10.1021/jacs.4c08406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2024] [Revised: 09/19/2024] [Accepted: 09/20/2024] [Indexed: 10/25/2024]
Abstract
Throughout the family of coronaviruses, structured RNA elements within the 5' region of the genome are highly conserved. The fifth stem-loop element from SARS-CoV-2 (5_SL5) represents an example of an RNA structural element, repeatedly occurring in coronaviruses. It contains a conserved, repetitive fold within its substructures SL5a and SL5b. We herein report the detailed characterization of the structure and dynamics of elements SL5a and SL5b that are located immediately upstream of the SARS-CoV-2 ORF1a/b start codon. Exploiting the unique ability of solution NMR methods, we show that the structures of both apical loops are modulated by structural differences in the remote parts located in their stem regions. We further integrated our high-resolution models of SL5a/b into the context of full-length 5_SL5 structures by combining different structural biology methods. Finally, we evaluated the impact of the two most common VoC mutations within 5_SL5 with respect to individual base-pair stability.
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Affiliation(s)
- Klara
R. Mertinkus
- Institute
for Organic Chemistry and Chemical Biology, Goethe University Frankfurt Am Main, Frankfurt/Main, Hessen 60438, Germany
- Center
for Biomolecular Magnetic Resonance (BMRZ), Goethe University Frankfurt Am Main, Frankfurt/Main, Hessen 60438, Germany
| | - Andreas Oxenfarth
- Institute
for Organic Chemistry and Chemical Biology, Goethe University Frankfurt Am Main, Frankfurt/Main, Hessen 60438, Germany
- Center
for Biomolecular Magnetic Resonance (BMRZ), Goethe University Frankfurt Am Main, Frankfurt/Main, Hessen 60438, Germany
| | - Christian Richter
- Center
for Biomolecular Magnetic Resonance (BMRZ), Goethe University Frankfurt Am Main, Frankfurt/Main, Hessen 60438, Germany
| | - Anna Wacker
- Institute
for Organic Chemistry and Chemical Biology, Goethe University Frankfurt Am Main, Frankfurt/Main, Hessen 60438, Germany
- Center
for Biomolecular Magnetic Resonance (BMRZ), Goethe University Frankfurt Am Main, Frankfurt/Main, Hessen 60438, Germany
| | - Carlos P. Mata
- Biocomputing
Unit, Department of Macromolecular Structures, National Centre for Biotechnology (CSIC), Darwin 3, Madrid 28049, Spain
| | - Jose Maria Carazo
- Biocomputing
Unit, Department of Macromolecular Structures, National Centre for Biotechnology (CSIC), Darwin 3, Madrid 28049, Spain
| | - Andreas Schlundt
- Center
for Biomolecular Magnetic Resonance (BMRZ), Goethe University Frankfurt Am Main, Frankfurt/Main, Hessen 60438, Germany
- Institute
of Biochemistry, University of Greifswald, Greifswald 17489, Germany
| | - Harald Schwalbe
- Institute
for Organic Chemistry and Chemical Biology, Goethe University Frankfurt Am Main, Frankfurt/Main, Hessen 60438, Germany
- Center
for Biomolecular Magnetic Resonance (BMRZ), Goethe University Frankfurt Am Main, Frankfurt/Main, Hessen 60438, Germany
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9
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Hernández-Marín M, Cantero-Camacho Á, Mena I, López-Núñez S, García-Sastre A, Gallego J. Sarbecovirus programmed ribosome frameshift RNA element folding studied by NMR spectroscopy and comparative analyses. Nucleic Acids Res 2024; 52:11960-11972. [PMID: 39149904 PMCID: PMC11514460 DOI: 10.1093/nar/gkae704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Revised: 07/24/2024] [Accepted: 08/05/2024] [Indexed: 08/17/2024] Open
Abstract
The programmed ribosomal frameshift (PRF) region is found in the RNA genome of all coronaviruses and shifts the ribosome reading frame through formation of a three-stem pseudoknot structure, allowing the translation of essential viral proteins. Using NMR spectroscopy, comparative sequence analyses and functional assays we show that, in the absence of the ribosome, a 123-nucleotide sequence encompassing the PRF element of SARS-CoV-2 adopts a well-defined two-stem loop structure that is conserved in all SARS-like coronaviruses. In this conformation, the attenuator hairpin and slippery site nucleotides are exposed in the first stem-loop and two pseudoknot stems are present in the second stem-loop, separated by an 8-nucleotide bulge. Formation of the third pseudoknot stem depends on pairing between bulge nucleotides and base-paired nucleotides of the upstream stem-loop, as shown by a PRF construct where residues of the upstream stem were removed, which formed the pseudoknot structure and had increased frameshifting activity in a dual-luciferase assay. The base-pair switch driving PRF pseudoknot folding was found to be conserved in several human non-SARS coronaviruses. The collective results suggest that the frameshifting pseudoknot structure of these viruses only forms transiently in the presence of the translating ribosome. These findings clarify the frameshifting mechanism in coronaviruses and can have a beneficial impact on antiviral drug discovery.
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Affiliation(s)
- María Hernández-Marín
- Centro de Investigación Traslacional San Alberto Magno, Universidad Católica de Valencia, 46001 Valencia, Spain
- Escuela de Doctorado, Universidad Católica de Valencia, 46001 Valencia, Spain
| | - Ángel Cantero-Camacho
- Centro de Investigación Traslacional San Alberto Magno, Universidad Católica de Valencia, 46001 Valencia, Spain
| | - Ignacio Mena
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, NY, USA
| | - Sergio López-Núñez
- Centro de Investigación Traslacional San Alberto Magno, Universidad Católica de Valencia, 46001 Valencia, Spain
- Escuela de Doctorado, Universidad Católica de Valencia, 46001 Valencia, Spain
| | - Adolfo García-Sastre
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, NY, USA
- Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, NY, USA
- Department of Medicine, Icahn School of Medicine at Mount Sinai, NY, USA
- Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, NY, USA
- The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, NY, USA
| | - José Gallego
- Centro de Investigación Traslacional San Alberto Magno, Universidad Católica de Valencia, 46001 Valencia, Spain
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10
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Dey A, Yan S, Schlick T, Laederach A. Abolished frameshifting for predicted structure-stabilizing SARS-CoV-2 mutants: implications to alternative conformations and their statistical structural analyses. RNA (NEW YORK, N.Y.) 2024; 30:1437-1450. [PMID: 39084880 PMCID: PMC11482603 DOI: 10.1261/rna.080035.124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Accepted: 07/21/2024] [Indexed: 08/02/2024]
Abstract
The SARS-CoV-2 frameshifting element (FSE) has been intensely studied and explored as a therapeutic target for coronavirus diseases, including COVID-19. Besides the intriguing virology, this small RNA is known to adopt many length-dependent conformations, as verified by multiple experimental and computational approaches. However, the role these alternative conformations play in the frameshifting mechanism and how to quantify this structural abundance has been an ongoing challenge. Here, we show by DMS and dual-luciferase functional assays that previously predicted FSE mutants (using the RAG graph theory approach) suppress structural transitions and abolish frameshifting. Furthermore, correlated mutation analysis of DMS data by three programs (DREEM, DRACO, and DANCE-MaP) reveals important differences in their estimation of specific RNA conformations, suggesting caution in the interpretation of such complex conformational landscapes. Overall, the abolished frameshifting in three different mutants confirms that all alternative conformations play a role in the pathways of ribosomal transition.
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Affiliation(s)
- Abhishek Dey
- Department of Biotechnology, National Institute of Pharmaceutical Education and Research (NIPER-R)-Raebareli, Lucknow 226002, India
| | - Shuting Yan
- Department of Chemistry, New York University, New York, New York 10003, USA
| | - Tamar Schlick
- Department of Chemistry, New York University, New York, New York 10003, USA
- Courant Institute of Mathematical Sciences, New York University, New York, New York 10012, USA
- NYU-ECNU Center for Computational Chemistry, NYU Shanghai, Shanghai 200062, P.R. China
- NYU Simons Center for Computational Physical Chemistry, New York University, New York, New York 10003, USA
| | - Alain Laederach
- Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
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11
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Mathez G, Brancale A, Cagno V. Novel Inhibitors of SARS-CoV-2 RNA Identified through Virtual Screening. J Chem Inf Model 2024; 64:6190-6196. [PMID: 39037082 PMCID: PMC11323243 DOI: 10.1021/acs.jcim.4c00758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Revised: 07/08/2024] [Accepted: 07/10/2024] [Indexed: 07/23/2024]
Abstract
We currently lack antivirals for most human viruses. In a quest for new molecules, focusing on viral RNA, instead of viral proteins, can represent a promising strategy. In this study, new inhibitors were identified starting from a published crystal structure of the tertiary SARS-CoV-2 RNA involved in the -1 programmed ribosomal frameshift. The pseudoknot structure was refined, and a virtual screening was performed using the repository of binders to the nucleic acid library, taking into consideration RNA flexibility. Hit compounds were validated against the wild-type virus and with a dual-luciferase assay measuring the frameshift efficiency. Several active molecules were identified. Our study reveals new inhibitors of SARS-CoV-2 but also highlights the feasibility of targeting RNA starting from virtual screening, a strategy that could be broadly applied to drug development.
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Affiliation(s)
- Gregory Mathez
- Institute
of Microbiology, University Hospital of
Lausanne, University of Lausanne, 1011 Lausanne, Switzerland
- Department
of Organic Chemistry, University of Chemistry
and Technology Prague, 16628 Prague 6, Czech Republic
| | - Andrea Brancale
- Department
of Organic Chemistry, University of Chemistry
and Technology Prague, 16628 Prague 6, Czech Republic
| | - Valeria Cagno
- Institute
of Microbiology, University Hospital of
Lausanne, University of Lausanne, 1011 Lausanne, Switzerland
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12
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Allan MF, Aruda J, Plung JS, Grote SL, des Taillades YJM, de Lajarte AA, Bathe M, Rouskin S. Discovery and Quantification of Long-Range RNA Base Pairs in Coronavirus Genomes with SEARCH-MaP and SEISMIC-RNA. RESEARCH SQUARE 2024:rs.3.rs-4814547. [PMID: 39149495 PMCID: PMC11326378 DOI: 10.21203/rs.3.rs-4814547/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
RNA molecules perform a diversity of essential functions for which their linear sequences must fold into higher-order structures. Techniques including crystallography and cryogenic electron microscopy have revealed 3D structures of ribosomal, transfer, and other well-structured RNAs; while chemical probing with sequencing facilitates secondary structure modeling of any RNAs of interest, even within cells. Ongoing efforts continue increasing the accuracy, resolution, and ability to distinguish coexisting alternative structures. However, no method can discover and quantify alternative structures with base pairs spanning arbitrarily long distances - an obstacle for studying viral, messenger, and long noncoding RNAs, which may form long-range base pairs. Here, we introduce the method of Structure Ensemble Ablation by Reverse Complement Hybridization with Mutational Profiling (SEARCH-MaP) and software for Structure Ensemble Inference by Sequencing, Mutation Identification, and Clustering of RNA (SEISMIC-RNA). We use SEARCH-MaP and SEISMIC-RNA to discover that the frameshift stimulating element of SARS coronavirus 2 base-pairs with another element 1 kilobase downstream in nearly half of RNA molecules, and that this structure competes with a pseudoknot that stimulates ribosomal frameshifting. Moreover, we identify long-range base pairs involving the frameshift stimulating element in other coronaviruses including SARS coronavirus 1 and transmissible gastroenteritis virus, and model the full genomic secondary structure of the latter. These findings suggest that long-range base pairs are common in coronaviruses and may regulate ribosomal frameshifting, which is essential for viral RNA synthesis. We anticipate that SEARCH-MaP will enable solving many RNA structure ensembles that have eluded characterization, thereby enhancing our general understanding of RNA structures and their functions. SEISMIC-RNA, software for analyzing mutational profiling data at any scale, could power future studies on RNA structure and is available on GitHub and the Python Package Index.
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Affiliation(s)
- Matthew F. Allan
- Department of Microbiology, Harvard Medical School, Boston, Massachusetts, USA 02115
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA 02139
- Computational and Systems Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA 02139
| | - Justin Aruda
- Department of Microbiology, Harvard Medical School, Boston, Massachusetts, USA 02115
- Harvard Program in Biological and Biomedical Sciences, Division of Medical Sciences, Harvard Medical School, Boston, MA, USA 02115
| | - Jesse S. Plung
- Department of Microbiology, Harvard Medical School, Boston, Massachusetts, USA 02115
- Harvard Program in Virology, Division of Medical Sciences, Harvard Medical School, Boston, MA, USA 02115
| | - Scott L. Grote
- Department of Microbiology, Harvard Medical School, Boston, Massachusetts, USA 02115
| | | | - Albéric A. de Lajarte
- Department of Microbiology, Harvard Medical School, Boston, Massachusetts, USA 02115
| | - Mark Bathe
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA 02139
| | - Silvi Rouskin
- Department of Microbiology, Harvard Medical School, Boston, Massachusetts, USA 02115
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13
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Allan MF, Aruda J, Plung JS, Grote SL, Martin des Taillades YJ, de Lajarte AA, Bathe M, Rouskin S. Discovery and Quantification of Long-Range RNA Base Pairs in Coronavirus Genomes with SEARCH-MaP and SEISMIC-RNA. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.29.591762. [PMID: 38746332 PMCID: PMC11092567 DOI: 10.1101/2024.04.29.591762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
RNA molecules perform a diversity of essential functions for which their linear sequences must fold into higher-order structures. Techniques including crystallography and cryogenic electron microscopy have revealed 3D structures of ribosomal, transfer, and other well-structured RNAs; while chemical probing with sequencing facilitates secondary structure modeling of any RNAs of interest, even within cells. Ongoing efforts continue increasing the accuracy, resolution, and ability to distinguish coexisting alternative structures. However, no method can discover and quantify alternative structures with base pairs spanning arbitrarily long distances - an obstacle for studying viral, messenger, and long noncoding RNAs, which may form long-range base pairs. Here, we introduce the method of Structure Ensemble Ablation by Reverse Complement Hybridization with Mutational Profiling (SEARCH-MaP) and software for Structure Ensemble Inference by Sequencing, Mutation Identification, and Clustering of RNA (SEISMIC-RNA). We use SEARCH-MaP and SEISMIC-RNA to discover that the frameshift stimulating element of SARS coronavirus 2 base-pairs with another element 1 kilobase downstream in nearly half of RNA molecules, and that this structure competes with a pseudoknot that stimulates ribosomal frameshifting. Moreover, we identify long-range base pairs involving the frameshift stimulating element in other coronaviruses including SARS coronavirus 1 and transmissible gastroenteritis virus, and model the full genomic secondary structure of the latter. These findings suggest that long-range base pairs are common in coronaviruses and may regulate ribosomal frameshifting, which is essential for viral RNA synthesis. We anticipate that SEARCH-MaP will enable solving many RNA structure ensembles that have eluded characterization, thereby enhancing our general understanding of RNA structures and their functions. SEISMIC-RNA, software for analyzing mutational profiling data at any scale, could power future studies on RNA structure and is available on GitHub and the Python Package Index.
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14
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Huang X, Du Z. Possible involvement of three-stemmed pseudoknots in regulating translational initiation in human mRNAs. PLoS One 2024; 19:e0307541. [PMID: 39038036 PMCID: PMC11262651 DOI: 10.1371/journal.pone.0307541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Accepted: 07/08/2024] [Indexed: 07/24/2024] Open
Abstract
RNA pseudoknots play a crucial role in various cellular functions. Established pseudoknots show significant variation in both size and structural complexity. Specifically, three-stemmed pseudoknots are characterized by an additional stem-loop embedded in their structure. Recent findings highlight these pseudoknots as bacterial riboswitches and potent stimulators for programmed ribosomal frameshifting in RNA viruses like SARS-CoV2. To investigate the possible presence of functional three-stemmed pseudoknots in human mRNAs, we employed in-house developed computational methods to detect such structures within a dataset comprising 21,780 full-length human mRNA sequences. Numerous three-stemmed pseudoknots were identified. A selected set of 14 potential instances are presented, in which the start codon of the mRNA is found in close proximity either upstream, downstream, or within the identified three-stemmed pseudoknot. These pseudoknots likely play a role in translational initiation regulation. The probability of their existence gains support from their ranking as the most stable pseudoknot identified in the entire mRNA sequence, structural conservation across homologous mRNAs, stereochemical feasibility as demonstrated by structural modeling, and classification as members of the CPK-1 pseudoknot family, which includes many well-established pseudoknots. Furthermore, in four of the mRNAs, two or three closely spaced or tandem three-stemmed pseudoknots were identified. These findings suggest the frequent occurrence of three-stemmed pseudoknots in human mRNAs. A stepwise co-transcriptional folding mechanism is proposed for the formation of a three-stemmed pseudoknot structure. Our results not only provide fresh insights into the structures and functions of pseudoknots but also unveil the potential to target pseudoknots for treating human diseases.
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Affiliation(s)
- Xiaolan Huang
- School of Computing, Southern Illinois University at Carbondale, IL, United States of America
| | - Zhihua Du
- School of Chemical and Biomolecular Sciences, Southern Illinois University at Carbondale, IL, United States of America
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15
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Peterson JM, Becker ST, O'Leary CA, Juneja P, Yang Y, Moss WN. Structure of the SARS-CoV-2 Frameshift Stimulatory Element with an Upstream Multibranch Loop. Biochemistry 2024; 63:1287-1296. [PMID: 38727003 DOI: 10.1021/acs.biochem.3c00716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) frameshift stimulatory element (FSE) is necessary for programmed -1 ribosomal frameshifting (-1 PRF) and optimized viral efficacy. The FSE has an abundance of context-dependent alternate conformations, but two of the structures most crucial to -1 PRF are an attenuator hairpin and a three-stem H-type pseudoknot structure. A crystal structure of the pseudoknot alone features three RNA stems in a helically stacked linear structure, whereas a 6.9 Å cryo-EM structure including the upstream heptameric slippery site resulted in a bend between two stems. Our previous research alluded to an extended upstream multibranch loop that includes both the attenuator hairpin and the slippery site-a conformation not previously modeled. We aim to provide further context to the SARS-CoV-2 FSE via computational and medium resolution cryo-EM approaches, by presenting a 6.1 Å cryo-EM structure featuring a linear pseudoknot structure and a dynamic upstream multibranch loop.
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Affiliation(s)
- Jake M Peterson
- Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa 50011, United States
| | - Scott T Becker
- Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa 50011, United States
| | - Collin A O'Leary
- Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa 50011, United States
| | - Puneet Juneja
- Cryo-EM Facility, Iowa State University, Ames, Iowa 50011, United States
| | - Yang Yang
- Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa 50011, United States
| | - Walter N Moss
- Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa 50011, United States
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16
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Dey A, Yan S, Schlick T, Laederach A. Abolished frameshifting for predicted structure-stabilizing SARS-CoV-2 mutants: Implications to alternative conformations and their statistical structural analyses. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.28.586935. [PMID: 38585719 PMCID: PMC10996636 DOI: 10.1101/2024.03.28.586935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
The SARS-CoV-2 frameshifting element (FSE) has been intensely studied and explored as a therapeutic target for coronavirus diseases including COVID-19. Besides the intriguing virology, this small RNA is known to adopt many length-dependent conformations, as verified by multiple experimental and computational approaches. However, the role these alternative conformations play in the frameshifting mechanism and how to quantify this structural abundance has been an ongoing challenge. Here, we show by DMS and dual-luciferase functional assays that previously predicted FSE mutants (using the RAG graph theory approach) suppress structural transitions and abolish frameshifting. Furthermore, correlated mutation analysis of DMS data by three programs (DREEM, DRACO, and DANCE-MaP) reveals important differences in their estimation of specific RNA conformations, suggesting caution in the interpretation of such complex conformational landscapes. Overall, the abolished frameshifting in three different mutants confirms that all alternative conformations play a role in the pathways of ribosomal transition.
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17
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Kretsch RC, Xu L, Zheludev IN, Zhou X, Huang R, Nye G, Li S, Zhang K, Chiu W, Das R. Tertiary folds of the SL5 RNA from the 5' proximal region of SARS-CoV-2 and related coronaviruses. Proc Natl Acad Sci U S A 2024; 121:e2320493121. [PMID: 38427602 PMCID: PMC10927501 DOI: 10.1073/pnas.2320493121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2023] [Accepted: 01/05/2024] [Indexed: 03/03/2024] Open
Abstract
Coronavirus genomes sequester their start codons within stem-loop 5 (SL5), a structured, 5' genomic RNA element. In most alpha- and betacoronaviruses, the secondary structure of SL5 is predicted to contain a four-way junction of helical stems, some of which are capped with UUYYGU hexaloops. Here, using cryogenic electron microscopy (cryo-EM) and computational modeling with biochemically determined secondary structures, we present three-dimensional structures of SL5 from six coronaviruses. The SL5 domain of betacoronavirus severe-acute-respiratory-syndrome-related coronavirus 2 (SARS-CoV-2), resolved at 4.7 Å resolution, exhibits a T-shaped structure, with its UUYYGU hexaloops at opposing ends of a coaxial stack, the T's "arms." Further analysis of SL5 domains from SARS-CoV-1 and MERS (7.1 and 6.4 to 6.9 Å resolution, respectively) indicate that the junction geometry and inter-hexaloop distances are conserved features across these human-infecting betacoronaviruses. The MERS SL5 domain displays an additional tertiary interaction, which is also observed in the non-human-infecting betacoronavirus BtCoV-HKU5 (5.9 to 8.0 Å resolution). SL5s from human-infecting alphacoronaviruses, HCoV-229E and HCoV-NL63 (6.5 and 8.4 to 9.0 Å resolution, respectively), exhibit the same coaxial stacks, including the UUYYGU-capped arms, but with a phylogenetically distinct crossing angle, an X-shape. As such, all SL5 domains studied herein fold into stable tertiary structures with cross-genus similarities and notable differences, with implications for potential protein-binding modes and therapeutic targets.
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Affiliation(s)
| | - Lily Xu
- Department of Microbiology and Immunology, Stanford University, Stanford, CA 94305
| | - Ivan N. Zheludev
- Department of Biochemistry, Stanford University, Stanford, CA94305
| | - Xueting Zhou
- Department of Bioengineering, James H. Clark Center, Stanford University, Stanford, CA94305
| | - Rui Huang
- Department of Biochemistry, Stanford University, Stanford, CA94305
| | - Grace Nye
- Department of Biochemistry, Stanford University, Stanford, CA94305
| | - Shanshan Li
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei230027, China
| | - Kaiming Zhang
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei230027, China
| | - Wah Chiu
- Biophysics Program, Stanford University, Stanford, CA94305
- Department of Bioengineering, James H. Clark Center, Stanford University, Stanford, CA94305
- CryoEM and Bioimaging Division, Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, Stanford University, Menlo Park, CA94025
| | - Rhiju Das
- Biophysics Program, Stanford University, Stanford, CA94305
- Department of Biochemistry, Stanford University, Stanford, CA94305
- HHMI, Stanford University, Stanford, CA94305
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18
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Karousis ED, Schubert K, Ban N. Coronavirus takeover of host cell translation and intracellular antiviral response: a molecular perspective. EMBO J 2024; 43:151-167. [PMID: 38200146 PMCID: PMC10897431 DOI: 10.1038/s44318-023-00019-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 11/01/2023] [Accepted: 11/24/2023] [Indexed: 01/12/2024] Open
Abstract
Coronaviruses are a group of related RNA viruses that cause respiratory diseases in humans and animals. Understanding the mechanisms of translation regulation during coronaviral infections is critical for developing antiviral therapies and preventing viral spread. Translation of the viral single-stranded RNA genome in the host cell cytoplasm is an essential step in the life cycle of coronaviruses, which affects the cellular mRNA translation landscape in many ways. Here we discuss various viral strategies of translation control, including how members of the Betacoronavirus genus shut down host cell translation and suppress host innate immune functions, as well as the role of the viral non-structural protein 1 (Nsp1) in the process. We also outline the fate of viral RNA, considering stress response mechanisms triggered in infected cells, and describe how unique viral RNA features contribute to programmed ribosomal -1 frameshifting, RNA editing, and translation shutdown evasion.
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Affiliation(s)
- Evangelos D Karousis
- Multidisciplinary Center for Infectious Diseases, University of Bern, Bern, Switzerland
- Department of Chemistry and Biochemistry, University of Bern, Bern, Switzerland
| | - Katharina Schubert
- Department of Biology, Institute of Molecular Biology and Biophysics, ETH Zurich, Zurich, Switzerland
| | - Nenad Ban
- Department of Biology, Institute of Molecular Biology and Biophysics, ETH Zurich, Zurich, Switzerland.
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19
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Huang SH, Chen SC, Wu TY, Chen CY, Yu CH. Programmable modulation of ribosomal frameshifting by mRNA targeting CRISPR-Cas12a system. iScience 2023; 26:108492. [PMID: 38125012 PMCID: PMC10730746 DOI: 10.1016/j.isci.2023.108492] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 09/13/2023] [Accepted: 11/16/2023] [Indexed: 12/23/2023] Open
Abstract
Minus 1 programmed ribosomal frameshifting (-1 PRF) is a conserved translational regulation event essential for critical biological processes, including the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication. Efficient trans-modulation of the structured RNA element crucial to -1 PRF will endow the therapeutic application. Here, we demonstrate that CRISPR RNA can stimulate efficient -1 PRF. Assembled CRISPR-Cas12a, but not CRISPR-Cas9, complex further enhances -1 PRF efficiency through its higher capacity to stall translating ribosomes. We additionally perform CRISPR-Cas12a targeting to impair the SARS-CoV-2 frameshifting pseudoknot structure via a focused screening. We demonstrate that targeting CRISPR-Cas12a results in more than 70% suppression of -1 PRF in vitro and about 50% suppression in mammalian cells. Our results show the expanded function of the CRISPR-Cas12 system in modulating -1 PRF efficiency through stalling ribosomes and deforming frameshifting stimulatory signals, which could serve as a new strategy for future coronavirus pandemics.
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Affiliation(s)
- Shih-Hong Huang
- Department of Biochemistry and Molecular Biology, College of Medicine, National Cheng Kung University, Tainan, Taiwan
- Institute of Basic Medical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Shih-Cheng Chen
- Department of Biochemistry and Molecular Biology, College of Medicine, National Cheng Kung University, Tainan, Taiwan
- National Institute of Cancer Research, National Health Research Institutes, Tainan, Taiwan
| | | | - Cheng-Yao Chen
- YD BioLabs, Inc., Hsinchu, Taiwan
- School of Medical Laboratory Science and Biotechnology, Taipei Medical University, Taipei, Taiwan
| | - Chien-Hung Yu
- Department of Biochemistry and Molecular Biology, College of Medicine, National Cheng Kung University, Tainan, Taiwan
- Institute of Basic Medical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan
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20
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Kretsch RC, Xu L, Zheludev IN, Zhou X, Huang R, Nye G, Li S, Zhang K, Chiu W, Das R. Tertiary folds of the SL5 RNA from the 5' proximal region of SARS-CoV-2 and related coronaviruses. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.22.567964. [PMID: 38076883 PMCID: PMC10705266 DOI: 10.1101/2023.11.22.567964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
Coronavirus genomes sequester their start codons within stem-loop 5 (SL5), a structured, 5' genomic RNA element. In most alpha- and betacoronaviruses, the secondary structure of SL5 is predicted to contain a four-way junction of helical stems, some of which are capped with UUYYGU hexaloops. Here, using cryogenic electron microscopy (cryo-EM) and computational modeling with biochemically-determined secondary structures, we present three-dimensional structures of SL5 from six coronaviruses. The SL5 domain of betacoronavirus SARS-CoV-2, resolved at 4.7 Å resolution, exhibits a T-shaped structure, with its UUYYGU hexaloops at opposing ends of a coaxial stack, the T's "arms." Further analysis of SL5 domains from SARS-CoV-1 and MERS (7.1 and 6.4-6.9 Å resolution, respectively) indicate that the junction geometry and inter-hexaloop distances are conserved features across the studied human-infecting betacoronaviruses. The MERS SL5 domain displays an additional tertiary interaction, which is also observed in the non-human-infecting betacoronavirus BtCoV-HKU5 (5.9-8.0 Å resolution). SL5s from human-infecting alphacoronaviruses, HCoV-229E and HCoV-NL63 (6.5 and 8.4-9.0 Å resolution, respectively), exhibit the same coaxial stacks, including the UUYYGU-capped arms, but with a phylogenetically distinct crossing angle, an X-shape. As such, all SL5 domains studied herein fold into stable tertiary structures with cross-genus similarities, with implications for potential protein-binding modes and therapeutic targets.
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Affiliation(s)
| | - Lily Xu
- Department of Microbiology and Immunology, Stanford University, Stanford, CA, USA
| | - Ivan N. Zheludev
- Department of Biochemistry, Stanford University, Stanford, CA, USA
| | - Xueting Zhou
- Department of Bioengineering, James H. Clark Center, Stanford University, Stanford, CA, USA
| | - Rui Huang
- Department of Biochemistry, Stanford University, Stanford, CA, USA
| | - Grace Nye
- Department of Biochemistry, Stanford University, Stanford, CA, USA
| | - Shanshan Li
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230027, China
| | - Kaiming Zhang
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230027, China
| | - Wah Chiu
- Biophysics Program, Stanford University, Stanford, CA, USA
- Department of Bioengineering, James H. Clark Center, Stanford University, Stanford, CA, USA
- CryoEM and Bioimaging Division, Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, Stanford University, Menlo Park, CA, USA
| | - Rhiju Das
- Biophysics Program, Stanford University, Stanford, CA, USA
- Department of Biochemistry, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford, CA, USA
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21
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Mainan A, Roy S. Dynamic Counterion Condensation Model Decodes Functional Dynamics of RNA Pseudoknot in SARS-CoV-2: Control of Ion-Mediated Pierced Lasso Topology. J Phys Chem Lett 2023; 14:10402-10411. [PMID: 37955626 DOI: 10.1021/acs.jpclett.3c02755] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2023]
Abstract
The programmed frameshifting stimulatory element, a promising drug target for COVID-19 treatment, involves a RNA pseudoknot (PK) structure. This RNA PK facilitates frameshifting, enabling RNA viruses to translate multiple proteins from a single mRNA, which is a key strategy for their rapid evolution. Overcoming the challenges of capturing large-scale structural changes of RNA under the influence of a dynamic counterion environment (K+ and Mg2+), the study extended the applications of a newly developed dynamic counterion condensation (DCC) model. DCC simulations reveal potential folding pathways of this RNA PK, supported by the experimental findings obtained using optical tweezers. The study elucidates the pivotal role of Mg2+ ions in crafting a lasso-like RNA topology, a novel RNA motif that governs dynamic transitions between the ring-opened and ring-closed states of the RNA. The pierced lasso component guided by Mg2+-mediated interactions orchestrates inward and outward motion fine-tuning tension on the slippery segment, a critical factor for optimizing frameshifting efficiency.
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Affiliation(s)
- Avijit Mainan
- Department of Chemical Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, West Bengal 741246, India
| | - Susmita Roy
- Department of Chemical Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, West Bengal 741246, India
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22
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Knizhnik E, Chumakov S, Svetlova J, Pavlova I, Khodarovich Y, Brylev V, Severov V, Alieva R, Kozlovskaya L, Andreev D, Aralov A, Varizhuk A. Unwinding the SARS-CoV-2 Ribosomal Frameshifting Pseudoknot with LNA and G-Clamp-Modified Phosphorothioate Oligonucleotides Inhibits Viral Replication. Biomolecules 2023; 13:1660. [PMID: 38002341 PMCID: PMC10668963 DOI: 10.3390/biom13111660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 11/10/2023] [Accepted: 11/15/2023] [Indexed: 11/26/2023] Open
Abstract
Ribosomal frameshifting (RFS) at the slippery site of SARS-CoV-2 RNA is essential for the biosynthesis of the viral replication machinery. It requires the formation of a pseudoknot (PK) structure near the slippery site and can be inhibited by PK-disrupting oligonucleotide-based antivirals. We obtained and compared three types of such antiviral candidates, namely locked nucleic acids (LNA), LNA-DNA gapmers, and G-clamp-containing phosphorothioates (CPSs) complementary to PK stems. Using optical and electrophoretic methods, we showed that stem 2-targeting oligonucleotide analogs induced PK unfolding at nanomolar concentrations, and this effect was particularly pronounced in the case of LNA. For the leading PK-unfolding LNA and CPS oligonucleotide analogs, we also demonstrated dose-dependent RSF inhibition in dual luciferase assays (DLAs). Finally, we showed that the leading oligonucleotide analogs reduced SARS-CoV-2 replication at subtoxic concentrations in the nanomolar range in two human cell lines. Our findings highlight the promise of PK targeting, illustrate the advantages and limitations of various types of DNA modifications and may promote the future development of oligonucleotide-based antivirals.
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Affiliation(s)
- Ekaterina Knizhnik
- Lopukhin Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, 119435 Moscow, Russia; (E.K.); (J.S.); (I.P.); (V.S.)
- Department of Biological and Medical Physics, Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia
| | - Stepan Chumakov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 117997 Moscow, Russia; (S.C.); (Y.K.); (V.B.); (D.A.)
| | - Julia Svetlova
- Lopukhin Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, 119435 Moscow, Russia; (E.K.); (J.S.); (I.P.); (V.S.)
| | - Iulia Pavlova
- Lopukhin Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, 119435 Moscow, Russia; (E.K.); (J.S.); (I.P.); (V.S.)
- Department of Biological and Medical Physics, Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia
| | - Yuri Khodarovich
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 117997 Moscow, Russia; (S.C.); (Y.K.); (V.B.); (D.A.)
- Research and Educational Resource Center for Cellular Technologies of The Peoples’ Friendship University of Russia, 117198 Moscow, Russia
| | - Vladimir Brylev
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 117997 Moscow, Russia; (S.C.); (Y.K.); (V.B.); (D.A.)
| | - Vjacheslav Severov
- Lopukhin Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, 119435 Moscow, Russia; (E.K.); (J.S.); (I.P.); (V.S.)
| | - Rugiya Alieva
- Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, 119992 Moscow, Russia;
- Raman Spectroscopy Laboratory, Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia
| | - Liubov Kozlovskaya
- Chumakov Scientific Center for Research and Development of Immune-and-Biological Products, Russian Academy of Sciences (Institute of Poliomyelitis), 108819 Moscow, Russia;
| | - Dmitry Andreev
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 117997 Moscow, Russia; (S.C.); (Y.K.); (V.B.); (D.A.)
- Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, 119992 Moscow, Russia;
| | - Andrey Aralov
- Lopukhin Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, 119435 Moscow, Russia; (E.K.); (J.S.); (I.P.); (V.S.)
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 117997 Moscow, Russia; (S.C.); (Y.K.); (V.B.); (D.A.)
| | - Anna Varizhuk
- Lopukhin Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, 119435 Moscow, Russia; (E.K.); (J.S.); (I.P.); (V.S.)
- Department of Biological and Medical Physics, Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia
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23
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He W, San Emeterio J, Woodside MT, Kirmizialtin S, Pollack L. Atomistic structure of the SARS-CoV-2 pseudoknot in solution from SAXS-driven molecular dynamics. Nucleic Acids Res 2023; 51:11332-11344. [PMID: 37819014 PMCID: PMC10639041 DOI: 10.1093/nar/gkad809] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 08/31/2023] [Accepted: 09/21/2023] [Indexed: 10/13/2023] Open
Abstract
SARS-CoV-2 depends on -1 programmed ribosomal frameshifting (-1 PRF) to express proteins essential for its replication. The RNA pseudoknot stimulating -1 PRF is thus an attractive drug target. However, the structural models of this pseudoknot obtained from cryo-EM and crystallography differ in some important features, leaving the pseudoknot structure unclear. We measured the solution structure of the pseudoknot using small-angle X-ray scattering (SAXS). The measured profile did not agree with profiles computed from the previously solved structures. Beginning with each of these solved structures, we used the SAXS data to direct all atom molecular dynamics (MD) simulations to improve the agreement in profiles. In all cases, this refinement resulted in a bent conformation that more closely resembled the cryo-EM structures than the crystal structure. Applying the same approach to a point mutant abolishing -1 PRF revealed a notably more bent structure with reoriented helices. This work clarifies the dynamic structures of the SARS-CoV-2 pseudoknot in solution.
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Affiliation(s)
- Weiwei He
- Chemistry Program, Science Division, New York University, Abu Dhabi, United Arab Emirates
- Department of Chemistry, New York University, USA
| | | | - Michael T Woodside
- Department of Physics, Li Ka Shing Institute of Virology, and Centre for Prions and Protein Folding Diseases, University of Alberta, Canada
| | - Serdal Kirmizialtin
- Chemistry Program, Science Division, New York University, Abu Dhabi, United Arab Emirates
- Department of Chemistry, New York University, USA
| | - Lois Pollack
- School of Applied and Engineering Physics, Cornell University, USA
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24
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Vögele J, Hymon D, Martins J, Ferner J, Jonker HA, Hargrove A, Weigand J, Wacker A, Schwalbe H, Wöhnert J, Duchardt-Ferner E. High-resolution structure of stem-loop 4 from the 5'-UTR of SARS-CoV-2 solved by solution state NMR. Nucleic Acids Res 2023; 51:11318-11331. [PMID: 37791874 PMCID: PMC10639051 DOI: 10.1093/nar/gkad762] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 07/19/2023] [Accepted: 09/09/2023] [Indexed: 10/05/2023] Open
Abstract
We present the high-resolution structure of stem-loop 4 of the 5'-untranslated region (5_SL4) of the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) genome solved by solution state nuclear magnetic resonance spectroscopy. 5_SL4 adopts an extended rod-like structure with a single flexible looped-out nucleotide and two mixed tandem mismatches, each composed of a G•U wobble base pair and a pyrimidine•pyrimidine mismatch, which are incorporated into the stem-loop structure. Both the tandem mismatches and the looped-out residue destabilize the stem-loop structure locally. Their distribution along the 5_SL4 stem-loop suggests a role of these non-canonical elements in retaining functionally important structural plasticity in particular with regard to the accessibility of the start codon of an upstream open reading frame located in the RNA's apical loop. The apical loop-although mostly flexible-harbors residual structural features suggesting an additional role in molecular recognition processes. 5_SL4 is highly conserved among the different variants of SARS-CoV-2 and can be targeted by small molecule ligands, which it binds with intermediate affinity in the vicinity of the non-canonical elements within the stem-loop structure.
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Affiliation(s)
- Jennifer Vögele
- Institute for Molecular Biosciences, Goethe-University Frankfurt, Max-von-Laue-Strasse 9, 60438 Frankfurt/M., Germany
- Center for Biomolecular Magnetic Resonance (BMRZ), Goethe-University Frankfurt, Max-von-Laue-Strasse 7, 60438 Frankfurt/M., Germany
| | - Daniel Hymon
- Center for Biomolecular Magnetic Resonance (BMRZ), Goethe-University Frankfurt, Max-von-Laue-Strasse 7, 60438 Frankfurt/M., Germany
- Institute for Organic Chemistry and Chemical Biology, Goethe-University Frankfurt, Max-von-Laue-Strasse 7, 60438 Frankfurt/M., Germany
| | - Jason Martins
- Center for Biomolecular Magnetic Resonance (BMRZ), Goethe-University Frankfurt, Max-von-Laue-Strasse 7, 60438 Frankfurt/M., Germany
- Institute for Organic Chemistry and Chemical Biology, Goethe-University Frankfurt, Max-von-Laue-Strasse 7, 60438 Frankfurt/M., Germany
| | - Jan Ferner
- Center for Biomolecular Magnetic Resonance (BMRZ), Goethe-University Frankfurt, Max-von-Laue-Strasse 7, 60438 Frankfurt/M., Germany
- Institute for Organic Chemistry and Chemical Biology, Goethe-University Frankfurt, Max-von-Laue-Strasse 7, 60438 Frankfurt/M., Germany
| | - Hendrik R A Jonker
- Center for Biomolecular Magnetic Resonance (BMRZ), Goethe-University Frankfurt, Max-von-Laue-Strasse 7, 60438 Frankfurt/M., Germany
- Institute for Organic Chemistry and Chemical Biology, Goethe-University Frankfurt, Max-von-Laue-Strasse 7, 60438 Frankfurt/M., Germany
| | | | - Julia E Weigand
- Philipps-University Marburg, Department of Pharmacy, Institute of Pharmaceutical Chemistry, Marbacher Weg 6, 35037 Marburg, Germany
| | - Anna Wacker
- Center for Biomolecular Magnetic Resonance (BMRZ), Goethe-University Frankfurt, Max-von-Laue-Strasse 7, 60438 Frankfurt/M., Germany
- Institute for Organic Chemistry and Chemical Biology, Goethe-University Frankfurt, Max-von-Laue-Strasse 7, 60438 Frankfurt/M., Germany
| | - Harald Schwalbe
- Center for Biomolecular Magnetic Resonance (BMRZ), Goethe-University Frankfurt, Max-von-Laue-Strasse 7, 60438 Frankfurt/M., Germany
- Institute for Organic Chemistry and Chemical Biology, Goethe-University Frankfurt, Max-von-Laue-Strasse 7, 60438 Frankfurt/M., Germany
| | - Jens Wöhnert
- Institute for Molecular Biosciences, Goethe-University Frankfurt, Max-von-Laue-Strasse 9, 60438 Frankfurt/M., Germany
- Center for Biomolecular Magnetic Resonance (BMRZ), Goethe-University Frankfurt, Max-von-Laue-Strasse 7, 60438 Frankfurt/M., Germany
| | - Elke Duchardt-Ferner
- Institute for Molecular Biosciences, Goethe-University Frankfurt, Max-von-Laue-Strasse 9, 60438 Frankfurt/M., Germany
- Center for Biomolecular Magnetic Resonance (BMRZ), Goethe-University Frankfurt, Max-von-Laue-Strasse 7, 60438 Frankfurt/M., Germany
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25
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Abstract
Protein synthesis by the ribosome is the final stage of biological information transfer and represents an irreversible commitment to gene expression. Accurate translation of messenger RNA is therefore essential to all life, and spontaneous errors by the translational machinery are highly infrequent (∼1/100,000 codons). Programmed -1 ribosomal frameshifting (-1PRF) is a mechanism in which the elongating ribosome is induced at high frequency to slip backward by one nucleotide at a defined position and to continue translation in the new reading frame. This is exploited as a translational regulation strategy by hundreds of RNA viruses, which rely on -1PRF during genome translation to control the stoichiometry of viral proteins. While early investigations of -1PRF focused on virological and biochemical aspects, the application of X-ray crystallography and cryo-electron microscopy (cryo-EM), and the advent of deep sequencing and single-molecule approaches have revealed unexpected structural diversity and mechanistic complexity. Molecular players from several model systems have now been characterized in detail, both in isolation and, more recently, in the context of the elongating ribosome. Here we provide a summary of recent advances and discuss to what extent a general model for -1PRF remains a useful way of thinking.
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Affiliation(s)
- Chris H Hill
- York Structural Biology Laboratory, York Biomedical Research Institute, Department of Biology, University of York, York, United Kingdom;
| | - Ian Brierley
- Department of Pathology, University of Cambridge, Cambridge, United Kingdom;
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26
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Zhang Q, Yang L, Wang K, Guo L, Ning H, Wang S, Gong Y. Terahertz waves regulate the mechanical unfolding of tau pre-mRNA hairpins. iScience 2023; 26:107572. [PMID: 37664616 PMCID: PMC10470126 DOI: 10.1016/j.isci.2023.107572] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 07/14/2023] [Accepted: 08/05/2023] [Indexed: 09/05/2023] Open
Abstract
Intermolecular interactions, including hydrogen bonds, dominate the pairing and unpairing of nucleic acid chains in the transfer process of genetic information. The energy of THz waves just matches with the weak interactions, so THz waves may interact with biomolecules. Here, the dynamic effects of THz electromagnetic (EM) waves on the mechanical unfolding process of RNA hairpins (WT-30nt and its mutants, rHP, SARS-CoV-2, and SRV-1 SF206) are investigated using steered molecular dynamics (SMD) simulations. The results show that THz waves can either promote the unfolding of the double helix of the RNA hairpin during the initial unfolding phase (4-21.8 THz) or significantly enhance (23.8 and 25.5 THz) or weaken (37.4 and 41.2 THz) its structural stability during unfolding. Our findings have important implications for applying THz waves to regulate dynamic deconvolution processes, such as gene replication, transcription, and translation.
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Affiliation(s)
- Qin Zhang
- School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China
| | - Lixia Yang
- School of Physics, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China
| | - Kaicheng Wang
- School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China
| | - Lianghao Guo
- School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China
| | - Hui Ning
- School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China
| | - Shaomeng Wang
- School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China
| | - Yubin Gong
- School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China
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27
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Kulkarni M, Thangappan J, Deb I, Wu S. Comparative analysis of RNA secondary structure accuracy on predicted RNA 3D models. PLoS One 2023; 18:e0290907. [PMID: 37656749 PMCID: PMC10473517 DOI: 10.1371/journal.pone.0290907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 08/18/2023] [Indexed: 09/03/2023] Open
Abstract
RNA structure is conformationally dynamic, and accurate all-atom tertiary (3D) structure modeling of RNA remains challenging with the prevailing tools. Secondary structure (2D) information is the standard prerequisite for most RNA 3D modeling. Despite several 2D and 3D structure prediction tools proposed in recent years, one of the challenges is to choose the best combination for accurate RNA 3D structure prediction. Here, we benchmarked seven small RNA PDB structures (40 to 90 nucleotides) with different topologies to understand the effects of different 2D structure predictions on the accuracy of 3D modeling. The current study explores the blind challenge of 2D to 3D conversions and highlights the performances of de novo RNA 3D modeling from their predicted 2D structure constraints. Our results show that conformational sampling-based methods such as SimRNA and IsRNA1 depend less on 2D accuracy, whereas motif-based methods account for 2D evidence. Our observations illustrate the disparities in available 3D and 2D prediction methods and may further offer insights into developing topology-specific or family-specific RNA structure prediction pipelines.
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Affiliation(s)
- Mandar Kulkarni
- R&D Center, PharmCADD Co. Ltd., Dong-gu, Busan, Republic of Korea
| | | | - Indrajit Deb
- R&D Center, PharmCADD Co. Ltd., Dong-gu, Busan, Republic of Korea
| | - Sangwook Wu
- R&D Center, PharmCADD Co. Ltd., Dong-gu, Busan, Republic of Korea
- Department of Physics, Pukyong National University, Busan, Republic of Korea
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28
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Deng J, Fang X, Huang L, Li S, Xu L, Ye K, Zhang J, Zhang K, Zhang QC. RNA structure determination: From 2D to 3D. FUNDAMENTAL RESEARCH 2023; 3:727-737. [PMID: 38933295 PMCID: PMC11197651 DOI: 10.1016/j.fmre.2023.06.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 06/04/2023] [Accepted: 06/05/2023] [Indexed: 06/28/2024] Open
Abstract
RNA molecules serve a wide range of functions that are closely linked to their structures. The basic structural units of RNA consist of single- and double-stranded regions. In order to carry out advanced functions such as catalysis and ligand binding, certain types of RNAs can adopt higher-order structures. The analysis of RNA structures has progressed alongside advancements in structural biology techniques, but it comes with its own set of challenges and corresponding solutions. In this review, we will discuss recent advances in RNA structure analysis techniques, including structural probing methods, X-ray crystallography, nuclear magnetic resonance, cryo-electron microscopy, and small-angle X-ray scattering. Often, a combination of multiple techniques is employed for the integrated analysis of RNA structures. We also survey important RNA structures that have been recently determined using various techniques.
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Affiliation(s)
- Jie Deng
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Xianyang Fang
- Beijing Frontier Research Center for Biological Structure, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing 100084, China
- Key Laboratory of RNA Biology, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Lin Huang
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Shanshan Li
- MOE Key Laboratory for Cellular Dynamics and Center for Advanced Interdisciplinary Science and Biomedicine of IHM, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230027, China
| | - Lilei Xu
- Beijing Frontier Research Center for Biological Structure, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Keqiong Ye
- Key Laboratory of RNA Biology, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jinsong Zhang
- MOE Key Laboratory of Bioinformatics, Beijing Advanced Innovation Center for Structural Biology & Frontier Research Center for Biological Structure, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing 100084, China
- Tsinghua-Peking Center for Life Sciences, Beijing 100084, China
| | - Kaiming Zhang
- MOE Key Laboratory for Cellular Dynamics and Center for Advanced Interdisciplinary Science and Biomedicine of IHM, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230027, China
| | - Qiangfeng Cliff Zhang
- MOE Key Laboratory of Bioinformatics, Beijing Advanced Innovation Center for Structural Biology & Frontier Research Center for Biological Structure, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing 100084, China
- Tsinghua-Peking Center for Life Sciences, Beijing 100084, China
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29
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Mathez G, Cagno V. Small Molecules Targeting Viral RNA. Int J Mol Sci 2023; 24:13500. [PMID: 37686306 PMCID: PMC10487773 DOI: 10.3390/ijms241713500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 08/25/2023] [Accepted: 08/28/2023] [Indexed: 09/10/2023] Open
Abstract
The majority of antivirals available target viral proteins; however, RNA is emerging as a new and promising antiviral target due to the presence of highly structured RNA in viral genomes fundamental for their replication cycle. Here, we discuss methods for the identification of RNA-targeting compounds, starting from the determination of RNA structures either from purified RNA or in living cells, followed by in silico screening on RNA and phenotypic assays to evaluate viral inhibition. Moreover, we review the small molecules known to target the programmed ribosomal frameshifting element of SARS-CoV-2, the internal ribosomal entry site of different viruses, and RNA elements of HIV.
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Affiliation(s)
| | - Valeria Cagno
- Institute of Microbiology, University Hospital of Lausanne, University of Lausanne, 1011 Lausanne, Switzerland
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30
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Yang M, Olatunji FP, Rhodes C, Balaratnam S, Dunne-Dombrink K, Seshadri S, Liang X, Jones CP, Le Grice SFJ, Ferré-D’Amaré AR, Schneekloth JS. Discovery of Small Molecules Targeting the Frameshifting Element RNA in SARS-CoV-2 Viral Genome. ACS Med Chem Lett 2023; 14:757-765. [PMID: 37312842 PMCID: PMC10258829 DOI: 10.1021/acsmedchemlett.3c00051] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 05/02/2023] [Indexed: 06/15/2023] Open
Abstract
Targeting structured RNA elements in the SARS-CoV-2 viral genome with small molecules is an attractive strategy for pharmacological control over viral replication. In this work, we report the discovery of small molecules that target the frameshifting element (FSE) in the SARS-CoV-2 RNA genome using high-throughput small-molecule microarray (SMM) screening. A new class of aminoquinazoline ligands for the SARS-CoV-2 FSE are synthesized and characterized using multiple orthogonal biophysical assays and structure-activity relationship (SAR) studies. This work reveals compounds with mid-micromolar binding affinity (KD = 60 ± 6 μM) to the FSE RNA and supports a binding mode distinct from previously reported FSE binders MTDB and merafloxacin. In addition, compounds are active in in vitro dual-luciferase and in-cell dual-fluorescent-reporter frameshifting assays, highlighting the promise of targeting structured elements of RNAs with druglike compounds to alter expression of viral proteins.
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Affiliation(s)
- Mo Yang
- Chemical
Biology Laboratory, Center for Cancer Research, National Cancer Institute, Frederick, Maryland 21702-1201, United States
| | - Feyisola P. Olatunji
- Chemical
Biology Laboratory, Center for Cancer Research, National Cancer Institute, Frederick, Maryland 21702-1201, United States
| | - Curran Rhodes
- Chemical
Biology Laboratory, Center for Cancer Research, National Cancer Institute, Frederick, Maryland 21702-1201, United States
| | - Sumirtha Balaratnam
- Chemical
Biology Laboratory, Center for Cancer Research, National Cancer Institute, Frederick, Maryland 21702-1201, United States
| | - Kara Dunne-Dombrink
- Chemical
Biology Laboratory, Center for Cancer Research, National Cancer Institute, Frederick, Maryland 21702-1201, United States
| | - Srinath Seshadri
- Chemical
Biology Laboratory, Center for Cancer Research, National Cancer Institute, Frederick, Maryland 21702-1201, United States
| | - Xiao Liang
- Chemical
Biology Laboratory, Center for Cancer Research, National Cancer Institute, Frederick, Maryland 21702-1201, United States
| | - Christopher P. Jones
- Biochemistry
and Biophysics Center, National Heart, Lung,
and Blood Institute, Bethesda, Maryland 20892, United States
| | - Stuart F. J. Le Grice
- Cancer
Innovation Laboratory, Center for Cancer Research, National Cancer Institute, Frederick Maryland 21702-1201, United States
| | - Adrian R. Ferré-D’Amaré
- Biochemistry
and Biophysics Center, National Heart, Lung,
and Blood Institute, Bethesda, Maryland 20892, United States
| | - John S. Schneekloth
- Chemical
Biology Laboratory, Center for Cancer Research, National Cancer Institute, Frederick, Maryland 21702-1201, United States
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31
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Sekar RV, Oliva PJ, Woodside MT. Modelling the structures of frameshift-stimulatory pseudoknots from representative bat coronaviruses. PLoS Comput Biol 2023; 19:e1011124. [PMID: 37205708 DOI: 10.1371/journal.pcbi.1011124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 04/24/2023] [Indexed: 05/21/2023] Open
Abstract
Coronaviruses (CoVs) use -1 programmed ribosomal frameshifting stimulated by RNA pseudoknots in the viral genome to control expression of enzymes essential for replication, making CoV pseudoknots a promising target for anti-coronaviral drugs. Bats represent one of the largest reservoirs of CoVs and are the ultimate source of most CoVs infecting humans, including those causing SARS, MERS, and COVID-19. However, the structures of bat-CoV frameshift-stimulatory pseudoknots remain largely unexplored. Here we use a combination of blind structure prediction followed by all-atom molecular dynamics simulations to model the structures of eight pseudoknots that, together with the SARS-CoV-2 pseudoknot, are representative of the range of pseudoknot sequences in bat CoVs. We find that they all share some key qualitative features with the pseudoknot from SARS-CoV-2, notably the presence of conformers with two distinct fold topologies differing in whether or not the 5' end of the RNA is threaded through a junction, and similar conformations for stem 1. However, they differed in the number of helices present, with half sharing the 3-helix architecture of the SARS-CoV-2 pseudoknot but two containing 4 helices and two others only 2. These structure models should be helpful for future work studying bat-CoV pseudoknots as potential therapeutic targets.
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Affiliation(s)
| | | | - Michael T Woodside
- Department of Physics, University of Alberta, Edmonton, Canada
- Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Canada
- Centre for Prions and Protein Folding Diseases, University of Alberta, Edmonton, Canada
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32
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Schroeder GM, Akinyemi O, Malik J, Focht CM, Pritchett E, Baker C, McSally JP, Jenkins JL, Mathews D, Wedekind J. A riboswitch separated from its ribosome-binding site still regulates translation. Nucleic Acids Res 2023; 51:2464-2484. [PMID: 36762498 PMCID: PMC10018353 DOI: 10.1093/nar/gkad056] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 01/14/2023] [Accepted: 02/07/2023] [Indexed: 02/11/2023] Open
Abstract
Riboswitches regulate downstream gene expression by binding cellular metabolites. Regulation of translation initiation by riboswitches is posited to occur by metabolite-mediated sequestration of the Shine-Dalgarno sequence (SDS), causing bypass by the ribosome. Recently, we solved a co-crystal structure of a prequeuosine1-sensing riboswitch from Carnobacterium antarcticum that binds two metabolites in a single pocket. The structure revealed that the second nucleotide within the gene-regulatory SDS, G34, engages in a crystal contact, obscuring the molecular basis of gene regulation. Here, we report a co-crystal structure wherein C10 pairs with G34. However, molecular dynamics simulations reveal quick dissolution of the pair, which fails to reform. Functional and chemical probing assays inside live bacterial cells corroborate the dispensability of the C10-G34 pair in gene regulation, leading to the hypothesis that the compact pseudoknot fold is sufficient for translation attenuation. Remarkably, the C. antarcticum aptamer retained significant gene-regulatory activity when uncoupled from the SDS using unstructured spacers up to 10 nucleotides away from the riboswitch-akin to steric-blocking employed by sRNAs. Accordingly, our work reveals that the RNA fold regulates translation without SDS sequestration, expanding known riboswitch-mediated gene-regulatory mechanisms. The results infer that riboswitches exist wherein the SDS is not embedded inside a stable fold.
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Affiliation(s)
- Griffin M Schroeder
- Department of Biochemistry and Biophysics, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA
- Center for RNA Biology, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA
| | - Olayinka Akinyemi
- Center for RNA Biology, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA
- Department of Physics, University of Rochester, Rochester, NY 14642, USA
| | - Jeffrey Malik
- Genomics Research Center, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA
| | - Caroline M Focht
- Department of Molecular Biophysics and Biochemistry and the Institute of Biomolecular Design and Discovery, Yale University, New Haven, CT 06516, USA
| | - Elizabeth M Pritchett
- Genomics Research Center, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA
| | - Cameron D Baker
- Genomics Research Center, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA
| | - James P McSally
- Department of Biochemistry and Biophysics, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA
- Center for RNA Biology, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA
| | - Jermaine L Jenkins
- Department of Biochemistry and Biophysics, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA
- Center for RNA Biology, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA
| | - David H Mathews
- Department of Biochemistry and Biophysics, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA
- Center for RNA Biology, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA
| | - Joseph E Wedekind
- Department of Biochemistry and Biophysics, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA
- Center for RNA Biology, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA
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33
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Length-dependent motions of SARS-CoV-2 frameshifting RNA pseudoknot and alternative conformations suggest avenues for frameshifting suppression. Nat Commun 2022; 13:4284. [PMID: 35879278 PMCID: PMC9310368 DOI: 10.1038/s41467-022-31353-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 06/10/2022] [Indexed: 12/16/2022] Open
Abstract
The SARS-CoV-2 frameshifting element (FSE), a highly conserved mRNA region required for correct translation of viral polyproteins, defines an excellent therapeutic target against Covid-19. As discovered by our prior graph-theory analysis with SHAPE experiments, the FSE adopts a heterogeneous, length-dependent conformational landscape consisting of an assumed 3-stem H-type pseudoknot (graph motif 3_6), and two alternative motifs (3_3 and 3_5). Here, for the first time, we build and simulate, by microsecond molecular dynamics, 30 models for all three motifs plus motif-stabilizing mutants at different lengths. Our 3_6 pseudoknot systems, which agree with experimental structures, reveal interconvertible L and linear conformations likely related to ribosomal pausing and frameshifting. The 3_6 mutant inhibits this transformation and could hamper frameshifting. Our 3_3 systems exhibit length-dependent stem interactions that point to a potential transition pathway connecting the three motifs during ribosomal elongation. Together, our observations provide new insights into frameshifting mechanisms and anti-viral strategies.
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34
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Eriani G, Martin F. Viral and cellular translation during SARS‐CoV‐2 infection. FEBS Open Bio 2022; 12:1584-1601. [PMID: 35429230 PMCID: PMC9110871 DOI: 10.1002/2211-5463.13413] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 03/30/2022] [Accepted: 04/14/2022] [Indexed: 11/16/2022] Open
Abstract
SARS‐CoV‐2 is a betacoronavirus that emerged in China in December 2019 and which is the causative agent of the Covid‐19 pandemic. This enveloped virus contains a large positive‐sense single‐stranded RNA genome. In this review, we summarize the current knowledge on the molecular mechanisms for the translation of both viral transcripts and cellular messenger RNAs. Non‐structural proteins are encoded by the genomic RNA and are produced in the early steps of infection. In contrast, the structural proteins are produced from subgenomic RNAs that are translated in the late phase of the infectious program. Non‐structural protein 1 (NSP1) is a key molecule that regulates both viral and cellular translation. In addition, NSP1 interferes with multiple steps of the interferon I pathway and thereby blocks host antiviral responses. Therefore, NSP1 is a drug target of choice for the development of antiviral therapies.
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Affiliation(s)
- Gilbert Eriani
- Université de Strasbourg Institut de Biologie Moléculaire et Cellulaire Architecture et Réactivité de l’ARN CNRS UPR9002 2, allée Konrad Roentgen F‐67084 Strasbourg France
| | - Franck Martin
- Université de Strasbourg Institut de Biologie Moléculaire et Cellulaire Architecture et Réactivité de l’ARN CNRS UPR9002 2, allée Konrad Roentgen F‐67084 Strasbourg France
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35
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Zhang D, Zhu L, Wang Y, Li P, Gao Y. Translational Control of COVID-19 and Its Therapeutic Implication. Front Immunol 2022; 13:857490. [PMID: 35422818 PMCID: PMC9002053 DOI: 10.3389/fimmu.2022.857490] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 03/07/2022] [Indexed: 12/19/2022] Open
Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of COVID-19, which has broken out worldwide for more than two years. However, due to limited treatment, new cases of infection are still rising. Therefore, there is an urgent need to understand the basic molecular biology of SARS-CoV-2 to control this virus. SARS-CoV-2 replication and spread depend on the recruitment of host ribosomes to translate viral messenger RNA (mRNA). To ensure the translation of their own mRNAs, the SARS-CoV-2 has developed multiple strategies to globally inhibit the translation of host mRNAs and block the cellular innate immune response. This review provides a comprehensive picture of recent advancements in our understanding of the molecular basis and complexity of SARS-CoV-2 protein translation. Specifically, we summarize how this viral infection inhibits host mRNA translation to better utilize translation elements for translation of its own mRNA. Finally, we discuss the potential of translational components as targets for therapeutic interventions.
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Affiliation(s)
- Dejiu Zhang
- Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine, Qingdao University, Qingdao, China
| | - Lei Zhu
- College of Basic Medical, Qingdao Binhai University, Qingdao, China
| | - Yin Wang
- Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine, Qingdao University, Qingdao, China
| | - Peifeng Li
- Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine, Qingdao University, Qingdao, China
| | - Yanyan Gao
- Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine, Qingdao University, Qingdao, China
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36
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Wang S, Chen D, Gao L, Liu Y. Short Oligonucleotides Facilitate Co-transcriptional Labeling of RNA at Specific Positions. J Am Chem Soc 2022; 144:5494-5502. [PMID: 35293210 DOI: 10.1021/jacs.2c00020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Labeling RNA molecules at specific positions is critical for RNA research and applications. Such methods are in high demand but still a challenge, especially those that enable native co-synthesis rather than post-synthesis labeling of long RNAs. The method we developed in this work meets these requirements, in which a leader RNA is extended on the hybrid solid-liquid phase by an engineered transcriptional complex following the pause-restart mode. A custom-designed short oligonucleotide is used to functionalize the engineered complex. This remarkable co-transcriptional labeling method incorporates labels into RNAs in high yields with great flexibility. We demonstrate the method by successfully introducing natural modifications, a fluorescent nucleotide analogue and a donor-acceptor fluorophore pair to specific sites located at an internal loop, a pseudoknot, a junction, a helix, and the middle of consecutive identical nucleotides of various RNAs. This newly developed method overcomes efficiency and position-choosing constraints that have hampered routine strategies to label RNAs beyond 200 nucleotides (nt).
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Affiliation(s)
- Siyu Wang
- State Key Laboratory of Microbial Metabolism, School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Dian Chen
- State Key Laboratory of Microbial Metabolism, School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Lingzhi Gao
- State Key Laboratory of Microbial Metabolism, School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Yu Liu
- State Key Laboratory of Microbial Metabolism, School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.,Shanghai Artificial Intelligence Laboratory, Shanghai 200232, China
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Zafferani M, Muralidharan D, Montalvan NI, Hargrove AE. RT-qPCR as a screening platform for mutational and small molecule impacts on structural stability of RNA tertiary structures. RSC Chem Biol 2022; 3:905-915. [PMID: 35866161 PMCID: PMC9257624 DOI: 10.1039/d2cb00015f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 05/25/2022] [Indexed: 11/21/2022] Open
Abstract
The exponential increase in the discovery and characterization of RNA tertiary structures has highlighted their active role in a variety of human diseases, yet often their interactome and specific function remain unknown. Small molecules offer opportunities to both decode these cellular roles and develop therapeutics, however there are few examples of small molecules that target biologically relevant RNA tertiary structures. While RNA triple helices are a particularly attractive target, discovery of triple helix modulators has been hindered by the lack of correlation between small molecule affinity and effect on structural modulation, thereby limiting the utility of affinity-based screening as a primary filtering method. To address this challenge, we developed a high-throughput RT-qPCR screening platform that reports on the effect of mutations and additives, such as small molecules, on the stability of triple helices. Using the 3′-end of the oncogenic long non-coding RNA MALAT1 as a proof-of-concept, we demonstrated the applicability of both a two-step and a one-pot method to assess the impact of mutations and small molecules on the stability of the triple helix. We demonstrated the adaptability of the assay to diverse RNA tertiary structures by applying it to the SARS-CoV-2 pseudoknot, a key viral RNA structure recently identified as an attractive therapeutic target for the development of antivirals. Employment of a functional high-throughput assay as a primary screen will significantly expedite the discovery of probes that modulate the structural landscape of RNA structures and, consequently, help gain insight into the roles of these pervasive structures. RT-qPCR can be harnessed as a small molecule screening platform to read out the effect of small molecules on the structural stability of a variety of RNA targets.![]()
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Affiliation(s)
- Martina Zafferani
- Department of Chemistry, Duke University, 124 Science Drive, Durham, NC 27705, USA
| | | | - Nadeska I. Montalvan
- Department of Chemistry, Duke University, 124 Science Drive, Durham, NC 27705, USA
| | - Amanda E. Hargrove
- Department of Chemistry, Duke University, 124 Science Drive, Durham, NC 27705, USA
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