1
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Zheng CC, Chen YL, Dong HL, Zhang XH, Tan ZJ. Effect of ethanol on the elasticities of double-stranded RNA and DNA revealed by magnetic tweezers and simulations. J Chem Phys 2024; 161:075101. [PMID: 39145565 DOI: 10.1063/5.0211869] [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: 04/02/2024] [Accepted: 07/29/2024] [Indexed: 08/16/2024] Open
Abstract
The elasticities of double-stranded (ds) DNA and RNA, which are critical to their biological functions and applications in materials science, can be significantly modulated by solution conditions such as ions and temperature. However, there is still a lack of a comprehensive understanding of the role of solvents in the elasticities of dsRNA and dsDNA in a comparative way. In this work, we explored the effect of ethanol solvent on the elasticities of dsRNA and dsDNA by magnetic tweezers and all-atom molecular dynamics simulations. We found that the bending persistence lengths and contour lengths of dsRNA and dsDNA decrease monotonically with the increase in ethanol concentration. Furthermore, the addition of ethanol weakens the positive twist-stretch coupling of dsRNA, while promotes the negative twist-stretch coupling of dsDNA. Counter-intuitively, the lower dielectric environment of ethanol causes a significant re-distribution of counterions and enhanced ion neutralization, which overwhelms the enhanced repulsion along dsRNA/dsDNA, ultimately leading to the softening in bending for dsRNA and dsDNA. Moreover, for dsRNA, ethanol causes slight ion-clamping across the major groove, which weakens the major groove-mediated twist-stretch coupling, while for dsDNA, ethanol promotes the stretch-radius correlation due to enhanced ion binding and consequently enhances the helical radius-mediated twist-stretch coupling.
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Affiliation(s)
- Chen-Chen Zheng
- School of Physics and Technology, College of Life Sciences, Wuhan University, Wuhan 430072, China
| | - Yun-Long Chen
- School of Physics and Technology, College of Life Sciences, Wuhan University, Wuhan 430072, China
| | - Hai-Long Dong
- School of Physics and Technology, College of Life Sciences, Wuhan University, Wuhan 430072, China
| | - Xing-Hua Zhang
- School of Physics and Technology, College of Life Sciences, Wuhan University, Wuhan 430072, China
| | - Zhi-Jie Tan
- School of Physics and Technology, College of Life Sciences, Wuhan University, Wuhan 430072, China
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2
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Rao YF, Sun LZ, Luo MB. Na +-Mg 2+ ion effects on conformation and translocation dynamics of single-stranded RNA: Cooperation and competition. Int J Biol Macromol 2024; 267:131273. [PMID: 38569994 DOI: 10.1016/j.ijbiomac.2024.131273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Revised: 03/20/2024] [Accepted: 03/28/2024] [Indexed: 04/05/2024]
Abstract
The nanopore-based translocation of a single-stranded RNA (ssRNA) in mixed salt solution has garnered increasing interest for its biological and technological significance. However, it is challenging to comprehensively understand the effects of the mixed ion species on the translocation dynamics due to their cooperation and competition, which can be directly reflected by the ion screening and neutralizing effects, respectively. In this study, Langevin dynamics simulation is employed to investigate the properties of ssRNA conformation and translocation in mixed Na+-Mg2+ ion environments. Simulation results reveal that the ion screening effect dominates the change in the ssRNA conformational size, the ion neutralizing effect controls the capture rate of the ssRNA by the nanopore, and both of them take charge of the different changes in translocation time of the ssRNA under various mixed ion environments. Under high Na+ ion concentration, as Mg2+ concentration increases, the ion neutralizing effect strengthens, weakening the driving force inside the nanopore, leading to longer translocation time. Conversely, at low Na+ concentration, an increase in Mg2+ concentration enhances the ion screening effect, aiding in faster translocation. Furthermore, these simulation results will be explained by quantitative analysis, advancing a deeper understanding of the complicated effects of the mixed Na+-Mg2+ ions.
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Affiliation(s)
- Yi-Fan Rao
- School of Physics, Zhejiang University, Hangzhou 310027, China; Department of Applied Physics, Zhejiang University of Technology, Hangzhou 310023, China
| | - Li-Zhen Sun
- Department of Applied Physics, Zhejiang University of Technology, Hangzhou 310023, China.
| | - Meng-Bo Luo
- School of Physics, Zhejiang University, Hangzhou 310027, China.
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3
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Dong HL, Zhang C, Dai L, Zhang Y, Zhang XH, Tan ZJ. The origin of different bending stiffness between double-stranded RNA and DNA revealed by magnetic tweezers and simulations. Nucleic Acids Res 2024; 52:2519-2529. [PMID: 38321947 PMCID: PMC10954459 DOI: 10.1093/nar/gkae063] [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: 06/14/2023] [Revised: 01/16/2024] [Accepted: 01/19/2024] [Indexed: 02/08/2024] Open
Abstract
The subtle differences in the chemical structures of double-stranded (ds) RNA and DNA lead to significant variations in their biological roles and medical implications, largely due to their distinct biophysical properties, such as bending stiffness. Although it is well known that A-form dsRNA is stiffer than B-form dsDNA under physiological salt conditions, the underlying cause of this difference remains unclear. In this study, we employ high-precision magnetic-tweezer experiments along with molecular dynamics simulations and reveal that the relative bending stiffness between dsRNA and dsDNA is primarily determined by the structure- and salt-concentration-dependent ion distribution around their helical structures. At near-physiological salt conditions, dsRNA shows a sparser ion distribution surrounding its phosphate groups compared to dsDNA, causing its greater stiffness. However, at very high monovalent salt concentrations, phosphate groups in both dsRNA and dsDNA become fully neutralized by excess ions, resulting in a similar intrinsic bending persistence length of approximately 39 nm. This similarity in intrinsic bending stiffness of dsRNA and dsDNA is coupled to the analogous fluctuations in their total groove widths and further coupled to the similar fluctuation of base-pair inclination, despite their distinct A-form and B-form helical structures.
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Affiliation(s)
- Hai-Long Dong
- School of Physics and Technology, College of Life Sciences, Renmin Hospital of Wuhan University, Wuhan University, Wuhan 430072, China
| | - Chen Zhang
- School of Physics and Technology, College of Life Sciences, Renmin Hospital of Wuhan University, Wuhan University, Wuhan 430072, China
| | - Liang Dai
- Department of Physics, City University of Hong Kong, Hong Kong 999077, China
| | - Yan Zhang
- Department of Clinical Laboratory, Renmin Hospital of Wuhan University, Wuhan 430072, China
| | - Xing-Hua Zhang
- School of Physics and Technology, College of Life Sciences, Renmin Hospital of Wuhan University, Wuhan University, Wuhan 430072, China
| | - Zhi-Jie Tan
- School of Physics and Technology, College of Life Sciences, Renmin Hospital of Wuhan University, Wuhan University, Wuhan 430072, China
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4
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Sarkar R, Mainan A, Roy S. Influence of ion and hydration atmospheres on RNA structure and dynamics: insights from advanced theoretical and computational methods. Chem Commun (Camb) 2024. [PMID: 38501190 DOI: 10.1039/d3cc06105a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/20/2024]
Abstract
RNA, a highly charged biopolymer composed of negatively charged phosphate groups, defies electrostatic repulsion to adopt well-defined, compact structures. Hence, the presence of positively charged metal ions is crucial not only for RNA's charge neutralization, but they also coherently decorate the ion atmosphere of RNA to stabilize its compact fold. This feature article elucidates various modes of close RNA-ion interactions, with a special emphasis on Mg2+ as an outer-sphere and inner-sphere ion. Through examples, we highlight how inner-sphere chelated Mg2+ stabilizes RNA pseudoknots, while outer-sphere ions can also exert long-range electrostatic interactions, inducing groove narrowing, coaxial helical stacking, and RNA ring formation. In addition to investigating the RNA's ion environment, we note that the RNA's hydration environment is relatively underexplored. Our study delves into its profound interplay with the structural dynamics of RNA, employing state-of-the-art atomistic simulation techniques. Through examples, we illustrate how specific ions and water molecules are associated with RNA functions, leveraging atomistic simulations to identify preferential ion binding and hydration sites. However, understanding their impact(s) on the RNA structure remains challenging due to the involvement of large length and long time scales associated with RNA's dynamic nature. Nevertheless, our contributions and recent advances in coarse-grained simulation techniques offer insights into large-scale structural changes dynamically linked to the RNA ion atmosphere. In this connection, we also review how different cutting-edge computational simulation methods provide a microscopic lens into the influence of ions and hydration on RNA structure and dynamics, elucidating distinct ion atmospheric components and specific hydration layers and their individual and collective impacts.
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Affiliation(s)
- Raju Sarkar
- Department of Chemical Sciences, Indian Institute of Science Education and Research, Kolkata, West Bengal 741246, India.
| | - Avijit Mainan
- Department of Chemical Sciences, Indian Institute of Science Education and Research, Kolkata, West Bengal 741246, India.
| | - Susmita Roy
- Department of Chemical Sciences, Indian Institute of Science Education and Research, Kolkata, West Bengal 741246, India.
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5
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Liu Y, Liu F, Li Y, Li Y, Feng Y, Zhao J, Zhou C, Li C, Shen J, Zhang Y. LncRNA Anxa10-203 enhances Mc1r mRNA stability to promote neuropathic pain by recruiting DHX30 in the trigeminal ganglion. J Headache Pain 2024; 25:28. [PMID: 38433184 PMCID: PMC10910797 DOI: 10.1186/s10194-024-01733-2] [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: 10/23/2023] [Accepted: 02/19/2024] [Indexed: 03/05/2024] Open
Abstract
BACKGROUND Trigeminal nerve injury is one of the most serious complications in oral clinics, and the subsequent chronic orofacial pain is a consumptive disease. Increasing evidence demonstrates long non-coding RNAs (lncRNAs) play an important role in the pathological process of neuropathic pain. This study aims to explore the function and mechanism of LncRNA Anxa10-203 in the development of orofacial neuropathic pain. METHODS A mouse model of orofacial neuropathic pain was established by chronic constriction injury of the infraorbital nerve (CCI-ION). The Von Frey test was applied to evaluate hypersensitivity of mice. RT-qPCR and/or Western Blot were performed to analyze the expression of Anxa10-203, DHX30, and MC1R. Cellular localization of target genes was verified by immunofluorescence and RNA fluorescence in situ hybridization. RNA pull-down and RNA immunoprecipitation were used to detect the interaction between the target molecules. Electrophysiology was employed to assess the intrinsic excitability of TG neurons (TGNs) in vitro. RESULTS Anxa10-203 was upregulated in the TG of CCI-ION mice, and knockdown of Anxa10-203 relieved neuropathic pain. Structurally, Anxa10-203 was located in the cytoplasm of TGNs. Mechanistically, Mc1r expression was positively correlated with Anxa10-203 and was identified as the functional target of Anxa10-203. Besides, Anxa10-203 recruited RNA binding protein DHX30 and formed the Anxa10-203/DHX30 complex to enhance the stability of Mc1r mRNA, resulting in the upregulation of MC1R, which contributed to the enhancement of the intrinsic activity of TGNs in vitro and orofacial neuropathic pain in vivo. CONCLUSIONS LncRNA Anxa10-203 in the TG played an important role in orofacial neuropathic pain and mediated mechanical allodynia in CCI-ION mice by binding with DHX30 to upregulate MC1R expression.
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Affiliation(s)
- YaJing Liu
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, National Center for Stomatology, West China School of Stomatology, Sichuan University, Chengdu, 610041, China
- Department of Prosthodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China
| | - Fei Liu
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, National Center for Stomatology, West China School of Stomatology, Sichuan University, Chengdu, 610041, China
- Department of Prosthodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China
| | - YiKe Li
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, National Center for Stomatology, West China School of Stomatology, Sichuan University, Chengdu, 610041, China
- Department of Prosthodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China
| | - YueLing Li
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, National Center for Stomatology, West China School of Stomatology, Sichuan University, Chengdu, 610041, China
- Department of Prosthodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China
| | - YuHeng Feng
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, National Center for Stomatology, West China School of Stomatology, Sichuan University, Chengdu, 610041, China
- Department of Prosthodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China
| | - JiaShuo Zhao
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, National Center for Stomatology, West China School of Stomatology, Sichuan University, Chengdu, 610041, China
- Department of Prosthodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China
| | - Cheng Zhou
- Laboratory of Anesthesia and Critical Care Medicine, Translational Neuroscience Center, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - ChunJie Li
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, National Center for Stomatology, West China School of Stomatology, Sichuan University, Chengdu, 610041, China
- Department of Head and Neck Oncology, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China
| | - JieFei Shen
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, National Center for Stomatology, West China School of Stomatology, Sichuan University, Chengdu, 610041, China.
- Department of Prosthodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China.
| | - YanYan Zhang
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, National Center for Stomatology, West China School of Stomatology, Sichuan University, Chengdu, 610041, China.
- Department of Prosthodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China.
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6
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Wang F, Xia R, Su Y, Cai P, Xu X. Quantifying RNA structures and interactions with a unified reduced chain representation model. Int J Biol Macromol 2023; 253:127181. [PMID: 37793523 DOI: 10.1016/j.ijbiomac.2023.127181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 08/30/2023] [Accepted: 09/25/2023] [Indexed: 10/06/2023]
Abstract
RNA is a pivotal molecule that plays critical roles in various cellular processes. Quantifying RNA structures and interactions is essential to understanding RNA function and developing RNA-based therapeutics. Using a unified five-bead model and a non-redundant database, this paper investigates the structural features and interactions of five commonly occurring RNA motifs, i.e., double-stranded helices, hairpin loops, internal/bulge loops, multi-branched junctions, and single-stranded terminal tails. Analyzing detailed distributions of RNA local structural features and base-base interactions reveals a preference for helical structures in both local backbone structures and base orientations. The interactions between adjacent bases exhibit motif-specific and sequence-dependent characteristics, reflecting the distinct topological constraints imposed by different loop-helix connection modes and the varying pairing and stacking interactions among different sequences. These findings shed light on the stability of RNA helices, emphasizing their significance in providing dominant base pairing and stacking interactions for RNA structures and stability. The four non-helix motifs encompass unpaired nucleotide loops and exhibit diverse base-base interactions, contributing to the structural diversity observed in RNA. Overall, the complexity of RNA structure arises from the intricate interplay of base-base interactions.
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Affiliation(s)
- Fengfei Wang
- Institute of Bioinformatics and Medical Engineering, School of Mathematics and Physics, Jiangsu University of Technology, Changzhou 213001, China
| | - Renjie Xia
- Institute of Bioinformatics and Medical Engineering, School of Mathematics and Physics, Jiangsu University of Technology, Changzhou 213001, China
| | - Yangyang Su
- Institute of Bioinformatics and Medical Engineering, School of Mathematics and Physics, Jiangsu University of Technology, Changzhou 213001, China
| | - Pinggen Cai
- Department of Applied Physics, Zhejiang University of Technology, Hangzhou 310023, China.
| | - Xiaojun Xu
- Institute of Bioinformatics and Medical Engineering, School of Mathematics and Physics, Jiangsu University of Technology, Changzhou 213001, China.
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7
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Malashin IP, Tynchenko VS, Nelyub VA, Borodulin AS, Gantimurov AP. Estimation and Prediction of the Polymers' Physical Characteristics Using the Machine Learning Models. Polymers (Basel) 2023; 16:115. [PMID: 38201778 PMCID: PMC10780762 DOI: 10.3390/polym16010115] [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: 11/25/2023] [Revised: 12/23/2023] [Accepted: 12/27/2023] [Indexed: 01/12/2024] Open
Abstract
This article investigates the utility of machine learning (ML) methods for predicting and analyzing the diverse physical characteristics of polymers. Leveraging a rich dataset of polymers' characteristics, the study encompasses an extensive range of polymer properties, spanning compressive and tensile strength to thermal and electrical behaviors. Using various regression methods like Ensemble, Tree-based, Regularization, and Distance-based, the research undergoes thorough evaluation using the most common quality metrics. As a result of a series of experimental studies on the selection of effective model parameters, those that provide a high-quality solution to the stated problem were found. The best results were achieved by Random Forest with the highest R2 scores of 0.71, 0.73, and 0.88 for glass transition, thermal decomposition, and melting temperatures, respectively. The outcomes are intricately compared, providing valuable insights into the efficiency of distinct ML approaches in predicting polymer properties. Unknown values for each characteristic were predicted, and a method validation was performed by training on the predicted values, comparing the results with the specified variance values of each characteristic. The research not only advances our comprehension of polymer physics but also contributes to informed model selection and optimization for materials science applications.
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Affiliation(s)
- Ivan Pavlovich Malashin
- Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia; (V.A.N.); (A.S.B.); (A.P.G.)
| | - Vadim Sergeevich Tynchenko
- Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia; (V.A.N.); (A.S.B.); (A.P.G.)
- Information-Control Systems Department, Institute of Computer Science and Telecommunications, Reshetnev Siberian State University of Science and Technology, 660037 Krasnoyarsk, Russia
- Department of Technological Machines and Equipment of Oil and Gas Complex, School of Petroleum and Natural Gas Engineering, Siberian Federal University, 660041 Krasnoyarsk, Russia
| | - Vladimir Aleksandrovich Nelyub
- Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia; (V.A.N.); (A.S.B.); (A.P.G.)
| | - Aleksei Sergeevich Borodulin
- Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia; (V.A.N.); (A.S.B.); (A.P.G.)
| | - Andrei Pavlovich Gantimurov
- Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia; (V.A.N.); (A.S.B.); (A.P.G.)
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8
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Hori N, Thirumalai D. Watching ion-driven kinetics of ribozyme folding and misfolding caused by energetic and topological frustration one molecule at a time. Nucleic Acids Res 2023; 51:10737-10751. [PMID: 37758176 PMCID: PMC10602927 DOI: 10.1093/nar/gkad755] [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: 04/17/2023] [Revised: 08/23/2023] [Accepted: 09/05/2023] [Indexed: 10/03/2023] Open
Abstract
Folding of ribozymes into well-defined tertiary structures usually requires divalent cations. How Mg2+ ions direct the folding kinetics has been a long-standing unsolved problem because experiments cannot detect the positions and dynamics of ions. To address this problem, we used molecular simulations to dissect the folding kinetics of the Azoarcus ribozyme by monitoring the path each molecule takes to reach the folded state. We quantitatively establish that Mg2+ binding to specific sites, coupled with counter-ion release of monovalent cations, stimulate the formation of secondary and tertiary structures, leading to diverse pathways that include direct rapid folding and trapping in misfolded structures. In some molecules, key tertiary structural elements form when Mg2+ ions bind to specific RNA sites at the earliest stages of the folding, leading to specific collapse and rapid folding. In others, the formation of non-native base pairs, whose rearrangement is needed to reach the folded state, is the rate-limiting step. Escape from energetic traps, driven by thermal fluctuations, occurs readily. In contrast, the transition to the native state from long-lived topologically trapped native-like metastable states is extremely slow. Specific collapse and formation of energetically or topologically frustrated states occur early in the assembly process.
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Affiliation(s)
- Naoto Hori
- Department of Chemistry, University of Texas, Austin, TX 78712, USA
- School of Pharmacy, University of Nottingham, Nottingham, UK
| | - D Thirumalai
- Department of Chemistry, University of Texas, Austin, TX 78712, USA
- Department of Physics, University of Texas, Austin, TX 78712, USA
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9
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Wang X, Yu S, Lou E, Tan YL, Tan ZJ. RNA 3D Structure Prediction: Progress and Perspective. Molecules 2023; 28:5532. [PMID: 37513407 PMCID: PMC10386116 DOI: 10.3390/molecules28145532] [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: 06/14/2023] [Revised: 07/05/2023] [Accepted: 07/13/2023] [Indexed: 07/30/2023] Open
Abstract
Ribonucleic acid (RNA) molecules play vital roles in numerous important biological functions such as catalysis and gene regulation. The functions of RNAs are strongly coupled to their structures or proper structure changes, and RNA structure prediction has been paid much attention in the last two decades. Some computational models have been developed to predict RNA three-dimensional (3D) structures in silico, and these models are generally composed of predicting RNA 3D structure ensemble, evaluating near-native RNAs from the structure ensemble, and refining the identified RNAs. In this review, we will make a comprehensive overview of the recent advances in RNA 3D structure modeling, including structure ensemble prediction, evaluation, and refinement. Finally, we will emphasize some insights and perspectives in modeling RNA 3D structures.
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Affiliation(s)
- Xunxun Wang
- Department of Physics, Key Laboratory of Artificial Micro & Nano-Structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China
| | - Shixiong Yu
- Department of Physics, Key Laboratory of Artificial Micro & Nano-Structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China
| | - En Lou
- Department of Physics, Key Laboratory of Artificial Micro & Nano-Structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China
| | - Ya-Lan Tan
- School of Bioengineering and Health, Wuhan Textile University, Wuhan 430200, China
- Research Center of Nonlinear Science, School of Mathematical and Physical Sciences, Wuhan Textile University, Wuhan 430200, China
| | - Zhi-Jie Tan
- Department of Physics, Key Laboratory of Artificial Micro & Nano-Structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China
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10
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Zhang D, Qiao L, Lei X, Dong X, Tong Y, Wang J, Wang Z, Zhou R. Mutagenesis and structural studies reveal the basis for the specific binding of SARS-CoV-2 SL3 RNA element with human TIA1 protein. Nat Commun 2023; 14:3715. [PMID: 37349329 PMCID: PMC10287707 DOI: 10.1038/s41467-023-39410-8] [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: 10/04/2022] [Accepted: 06/12/2023] [Indexed: 06/24/2023] Open
Abstract
Viral RNA-host protein interactions are indispensable during RNA virus transcription and replication, but their detailed structural and dynamical features remain largely elusive. Here, we characterize the binding interface for the SARS-CoV-2 stem-loop 3 (SL3) cis-acting element to human TIA1 protein with a combined theoretical and experimental approaches. The highly structured SARS-CoV-2 SL3 has a high binding affinity to TIA1 protein, in which the aromatic stacking, hydrogen bonds, and hydrophobic interactions collectively direct this specific binding. Further mutagenesis studies validate our proposed 3D binding model and reveal two SL3 variants have enhanced binding affinities to TIA1. And disruptions of the identified RNA-protein interactions with designed antisense oligonucleotides dramatically reduce SARS-CoV-2 infection in cells. Finally, TIA1 protein could interact with conserved SL3 RNA elements within other betacoronavirus lineages. These findings open an avenue to explore the viral RNA-host protein interactions and provide a pioneering structural basis for RNA-targeting antiviral drug design.
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Affiliation(s)
- Dong Zhang
- Institute of Quantitative Biology, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Lulu Qiao
- State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Xiaobo Lei
- NHC Key Laboratory of Systems Biology of Pathogens and Christophe Mérieux Laboratory, Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Xiaojing Dong
- NHC Key Laboratory of Systems Biology of Pathogens and Christophe Mérieux Laboratory, Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Yunguang Tong
- College of Life Sciences, China Jiliang University, Hangzhou, Zhejiang, 310018, China
- Department of Pharmacy, China Jiliang University, Hangzhou, Zhejiang, 310018, China
| | - Jianwei Wang
- NHC Key Laboratory of Systems Biology of Pathogens and Christophe Mérieux Laboratory, Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
| | - Zhiye Wang
- State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China.
- The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310058, China.
| | - Ruhong Zhou
- Institute of Quantitative Biology, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China.
- The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310058, China.
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11
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Watson ZL, Knudson IJ, Ward FR, Miller SJ, Cate JHD, Schepartz A, Abramyan AM. Atomistic simulations of the Escherichia coli ribosome provide selection criteria for translationally active substrates. Nat Chem 2023:10.1038/s41557-023-01226-w. [PMID: 37308707 DOI: 10.1038/s41557-023-01226-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 04/28/2023] [Indexed: 06/14/2023]
Abstract
As genetic code expansion advances beyond L-α-amino acids to backbone modifications and new polymerization chemistries, delineating what substrates the ribosome can accommodate remains a challenge. The Escherichia coli ribosome tolerates non-L-α-amino acids in vitro, but few structural insights that explain how are available, and the boundary conditions for efficient bond formation are so far unknown. Here we determine a high-resolution cryogenic electron microscopy structure of the E. coli ribosome containing α-amino acid monomers and use metadynamics simulations to define energy surface minima and understand incorporation efficiencies. Reactive monomers across diverse structural classes favour a conformational space where the aminoacyl-tRNA nucleophile is <4 Å from the peptidyl-tRNA carbonyl with a Bürgi-Dunitz angle of 76-115°. Monomers with free energy minima that fall outside this conformational space do not react efficiently. This insight should accelerate the in vivo and in vitro ribosomal synthesis of sequence-defined, non-peptide heterooligomers.
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Affiliation(s)
- Zoe L Watson
- Department of Chemistry, University of California, Berkeley, CA, USA
- Center for Genetically Encoded Materials, University of California, Berkeley, CA, USA
- California Institute for Quantitative Biosciences (QB3), University of California, Berkeley, CA, USA
| | - Isaac J Knudson
- Department of Chemistry, University of California, Berkeley, CA, USA
- Center for Genetically Encoded Materials, University of California, Berkeley, CA, USA
| | - Fred R Ward
- Center for Genetically Encoded Materials, University of California, Berkeley, CA, USA
- Department of Molecular and Cellular Biology, University of California, Berkeley, CA, USA
| | - Scott J Miller
- Center for Genetically Encoded Materials, University of California, Berkeley, CA, USA.
- Department of Chemistry, Yale University, New Haven, CT, USA.
| | - Jamie H D Cate
- Department of Chemistry, University of California, Berkeley, CA, USA.
- Center for Genetically Encoded Materials, University of California, Berkeley, CA, USA.
- Department of Molecular and Cellular Biology, University of California, Berkeley, CA, USA.
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
| | - Alanna Schepartz
- Department of Chemistry, University of California, Berkeley, CA, USA.
- Center for Genetically Encoded Materials, University of California, Berkeley, CA, USA.
- California Institute for Quantitative Biosciences (QB3), University of California, Berkeley, CA, USA.
- Department of Molecular and Cellular Biology, University of California, Berkeley, CA, USA.
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
- Chan Zuckerberg Biohub, San Francisco, CA, USA.
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12
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Kamga Youmbi FI, Kengne Tchendji V, Tayou Djamegni C. P-FARFAR2: A multithreaded greedy approach to sampling low-energy RNA structures in Rosetta FARFAR2. Comput Biol Chem 2023; 104:107878. [PMID: 37167861 DOI: 10.1016/j.compbiolchem.2023.107878] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 04/23/2023] [Accepted: 05/01/2023] [Indexed: 05/13/2023]
Abstract
RNA (ribonucleic acid) structure prediction finds many applications in health science and drug discovery due to its importance in several life regulatory processes. But despite significant advances in the close field of protein prediction, RNA 3D structure still poses a tremendous challenge to predict, especially for large sequences. In this regard, the approach unfolded by Rosetta FARFAR2 (Fragment Assembly of RNA with Full-Atom Refinement, version 2) has shown promising results, but the algorithm is non-deterministic by nature. In this paper, we develop P-FARFAR2: a parallel enhancement of FARFAR2 that increases its ability to assemble low-energy structures via multithreaded exploration of random configurations in a greedy manner. This strategy, appearing in the literature under the term "parallel mechanism", is made viable through two measures: first, the synchronization window is coarsened to several Monte Carlo cycles; second, all but one of the threads are differentiated as auxiliary and set to perform a weakened version of the problem. Following empirical analysis on a diverse range of RNA structures, we report achieving statistical significance in lowering the energy levels of ensuing samples. And consequently, despite the moderate-to-weak correlation between energy levels and prediction accuracy, this achievement happens to propagate to accuracy measurements.
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Affiliation(s)
| | - Vianney Kengne Tchendji
- Department of Mathematics and Computer Science, University of Dschang, PO Box 67, Dschang, Cameroon.
| | - Clémentin Tayou Djamegni
- Department of Mathematics and Computer Science, University of Dschang, PO Box 67, Dschang, Cameroon; Department of Computer Engineering, University of Dschang, PO Box 134, Bandjoun, Cameroon.
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13
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Wang X, Tan YL, Yu S, Shi YZ, Tan ZJ. Predicting 3D structures and stabilities for complex RNA pseudoknots in ion solutions. Biophys J 2023; 122:1503-1516. [PMID: 36924021 PMCID: PMC10147842 DOI: 10.1016/j.bpj.2023.03.017] [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: 10/24/2022] [Revised: 03/05/2023] [Accepted: 03/10/2023] [Indexed: 03/17/2023] Open
Abstract
RNA pseudoknots are a kind of important tertiary motif, and the structures and stabilities of pseudoknots are generally critical to the biological functions of RNAs with the motifs. In this work, we have carefully refined our previously developed coarse-grained model with salt effect through involving a new coarse-grained force field and a replica-exchange Monte Carlo algorithm, and employed the model to predict structures and stabilities of complex RNA pseudoknots in ion solutions beyond minimal H-type pseudoknots. Compared with available experimental data, the newly refined model can successfully predict 3D structures from sequences for the complex RNA pseudoknots including SARS-CoV-2 programming-1 ribosomal frameshifting element and Zika virus xrRNA, and can reliably predict the thermal stabilities of RNA pseudoknots with various sequences and lengths over broad ranges of monovalent/divalent salts. In addition, for complex pseudoknots including SARS-CoV-2 frameshifting element, our analyses show that their thermally unfolding pathways are mainly dependent on the relative stabilities of unfolded intermediate states, in analogy to those of minimal H-type pseudoknots.
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Affiliation(s)
- Xunxun Wang
- Department of Physics and Key Laboratory of Artificial Micro & Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan, China
| | - Ya-Lan Tan
- Research Center of Nonlinear Science and School of Mathematical and Physical Sciences, Wuhan Textile University, Wuhan, China
| | - Shixiong Yu
- Department of Physics and Key Laboratory of Artificial Micro & Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan, China
| | - Ya-Zhou Shi
- Research Center of Nonlinear Science and School of Mathematical and Physical Sciences, Wuhan Textile University, Wuhan, China
| | - Zhi-Jie Tan
- Department of Physics and Key Laboratory of Artificial Micro & Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan, China.
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14
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Luo S, Wohl S, Zheng W, Yang S. Biophysical and Integrative Characterization of Protein Intrinsic Disorder as a Prime Target for Drug Discovery. Biomolecules 2023; 13:biom13030530. [PMID: 36979465 PMCID: PMC10046839 DOI: 10.3390/biom13030530] [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: 02/10/2023] [Revised: 03/07/2023] [Accepted: 03/10/2023] [Indexed: 03/17/2023] Open
Abstract
Protein intrinsic disorder is increasingly recognized for its biological and disease-driven functions. However, it represents significant challenges for biophysical studies due to its high conformational flexibility. In addressing these challenges, we highlight the complementary and distinct capabilities of a range of experimental and computational methods and further describe integrative strategies available for combining these techniques. Integrative biophysics methods provide valuable insights into the sequence–structure–function relationship of disordered proteins, setting the stage for protein intrinsic disorder to become a promising target for drug discovery. Finally, we briefly summarize recent advances in the development of new small molecule inhibitors targeting the disordered N-terminal domains of three vital transcription factors.
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Affiliation(s)
- Shuqi Luo
- Center for Proteomics and Department of Nutrition, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Samuel Wohl
- Department of Physics, Arizona State University, Tempe, AZ 85287, USA
| | - Wenwei Zheng
- College of Integrative Sciences and Arts, Arizona State University, Mesa, AZ 85212, USA
- Correspondence: (W.Z.); (S.Y.)
| | - Sichun Yang
- Center for Proteomics and Department of Nutrition, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
- Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH 44106, USA
- Correspondence: (W.Z.); (S.Y.)
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15
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Tan YL, Wang X, Yu S, Zhang B, Tan ZJ. cgRNASP: coarse-grained statistical potentials with residue separation for RNA structure evaluation. NAR Genom Bioinform 2023; 5:lqad016. [PMID: 36879898 PMCID: PMC9985339 DOI: 10.1093/nargab/lqad016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 01/21/2023] [Accepted: 02/03/2023] [Indexed: 03/07/2023] Open
Abstract
Knowledge-based statistical potentials are very important for RNA 3-dimensional (3D) structure prediction and evaluation. In recent years, various coarse-grained (CG) and all-atom models have been developed for predicting RNA 3D structures, while there is still lack of reliable CG statistical potentials not only for CG structure evaluation but also for all-atom structure evaluation at high efficiency. In this work, we have developed a series of residue-separation-based CG statistical potentials at different CG levels for RNA 3D structure evaluation, namely cgRNASP, which is composed of long-ranged and short-ranged interactions by residue separation. Compared with the newly developed all-atom rsRNASP, the short-ranged interaction in cgRNASP was involved more subtly and completely. Our examinations show that, the performance of cgRNASP varies with CG levels and compared with rsRNASP, cgRNASP has similarly good performance for extensive types of test datasets and can have slightly better performance for the realistic dataset-RNA-Puzzles dataset. Furthermore, cgRNASP is strikingly more efficient than all-atom statistical potentials/scoring functions, and can be apparently superior to other all-atom statistical potentials and scoring functions trained from neural networks for the RNA-Puzzles dataset. cgRNASP is available at https://github.com/Tan-group/cgRNASP.
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Affiliation(s)
- Ya-Lan Tan
- Research Center of Nonlinear Science, School of Mathematical and Physical Sciences, Wuhan Textile University, Wuhan 430073, China.,Department of Physics and Key Laboratory of Artificial Micro & Nano-structures of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China
| | - Xunxun Wang
- Department of Physics and Key Laboratory of Artificial Micro & Nano-structures of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China
| | - Shixiong Yu
- Department of Physics and Key Laboratory of Artificial Micro & Nano-structures of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China
| | - Bengong Zhang
- Research Center of Nonlinear Science, School of Mathematical and Physical Sciences, Wuhan Textile University, Wuhan 430073, China
| | - Zhi-Jie Tan
- Department of Physics and Key Laboratory of Artificial Micro & Nano-structures of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China
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16
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Wang F, Li W, Li B, Xie L, Tong Y, Xu X. cRNAsp12 Web Server for the Prediction of Circular RNA Secondary Structures and Stabilities. Int J Mol Sci 2023; 24:ijms24043822. [PMID: 36835231 PMCID: PMC9959564 DOI: 10.3390/ijms24043822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 01/29/2023] [Accepted: 02/07/2023] [Indexed: 02/17/2023] Open
Abstract
Circular RNAs (circRNAs) are a novel class of non-coding RNA that, unlike linear RNAs, form a covalently closed loop without the 5' and 3' ends. Growing evidence shows that circular RNAs play important roles in life processes and have great potential implications in clinical and research fields. The accurate modeling of circRNAs structure and stability has far-reaching impact on our understanding of their functions and our ability to develop RNA-based therapeutics. The cRNAsp12 server offers a user-friendly web interface to predict circular RNA secondary structures and folding stabilities from the sequence. Through the helix-based landscape partitioning strategy, the server generates distinct ensembles of structures and predicts the minimal free energy structures for each ensemble with the recursive partition function calculation and backtracking algorithms. For structure predictions in the limited structural ensemble, the server also provides users with the option to set the structural constraints of forcing the base pairs and/or forcing the unpaired bases, such that only structures that meet the criteria are enumerated recursively.
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Affiliation(s)
- Fengfei Wang
- Institute of Bioinformatics and Medical Engineering, Jiangsu University of Technology, Changzhou 213001, China
| | - Wei Li
- Institute of Bioinformatics and Medical Engineering, Jiangsu University of Technology, Changzhou 213001, China
| | - Baiyi Li
- Institute of Bioinformatics and Medical Engineering, Jiangsu University of Technology, Changzhou 213001, China
| | - Liangxu Xie
- Institute of Bioinformatics and Medical Engineering, Jiangsu University of Technology, Changzhou 213001, China
| | - Yunguang Tong
- Department of Pharmacy, China Jiliang University, Hangzhou 310000, China
| | - Xiaojun Xu
- Institute of Bioinformatics and Medical Engineering, Jiangsu University of Technology, Changzhou 213001, China
- Correspondence:
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17
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Biomotors, viral assembly, and RNA nanobiotechnology: Current achievements and future directions. Comput Struct Biotechnol J 2022; 20:6120-6137. [PMID: 36420155 PMCID: PMC9672130 DOI: 10.1016/j.csbj.2022.11.007] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 11/04/2022] [Accepted: 11/04/2022] [Indexed: 11/13/2022] Open
Abstract
The International Society of RNA Nanotechnology and Nanomedicine (ISRNN) serves to further the development of a wide variety of functional nucleic acids and other related nanotechnology platforms. To aid in the dissemination of the most recent advancements, a biennial discussion focused on biomotors, viral assembly, and RNA nanobiotechnology has been established where international experts in interdisciplinary fields such as structural biology, biophysical chemistry, nanotechnology, cell and cancer biology, and pharmacology share their latest accomplishments and future perspectives. The results summarized here highlight advancements in our understanding of viral biology and the structure-function relationship of frame-shifting elements in genomic viral RNA, improvements in the predictions of SHAPE analysis of 3D RNA structures, and the understanding of dynamic RNA structures through a variety of experimental and computational means. Additionally, recent advances in the drug delivery, vaccine design, nanopore technologies, biomotor and biomachine development, DNA packaging, RNA nanotechnology, and drug delivery are included in this critical review. We emphasize some of the novel accomplishments, major discussion topics, and present current challenges and perspectives of these emerging fields.
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18
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Zhang J, Fakharzadeh A, Roland C, Sagui C. RNA as a Major-Groove Ligand: RNA-RNA and RNA-DNA Triplexes Formed by GAA and UUC or TTC Sequences. ACS OMEGA 2022; 7:38728-38743. [PMID: 36340174 PMCID: PMC9631886 DOI: 10.1021/acsomega.2c04358] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Accepted: 10/04/2022] [Indexed: 06/16/2023]
Abstract
Friedreich's ataxia is associated with noncanonical nucleic acid structures that emerge when GAA:TTC repeats in the first intron of the FXN gene expand beyond a critical number of repeats. Specifically, the noncanonical repeats are associated with both triplexes and R-loops. Here, we present an in silico investigation of all possible triplexes that form by attaching a third RNA strand to an RNA:RNA or DNA:DNA duplex, complementing previous DNA-based triplex studies. For both new triplexes results are similar. For a pyridimine UUC+ third strand, the parallel orientation is stable while its antiparallel counterpart is unstable. For a neutral GAA third strand, the parallel conformation is stable. A protonated GA+A third strand is stable in both parallel and antiparallel orientations. We have also investigated Na+ and Mg2+ ion distributions around the triplexes. The presence of Mg2+ ions helps stabilize neutral, antiparallel GAA triplexes. These results (along with previous DNA-based studies) allow for the emergence of a complete picture of the stability and structural characteristics of triplexes based on the GAA and TTC/UUC sequences, thereby contributing to the field of trinucleotide repeats and the associated unusual structures that trigger expansion.
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19
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Potential effects of metal ion induced two-state allostery on the regulatory mechanism of add adenine riboswitch. Commun Biol 2022; 5:1120. [PMID: 36273041 PMCID: PMC9588036 DOI: 10.1038/s42003-022-04096-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 10/11/2022] [Indexed: 11/09/2022] Open
Abstract
Riboswitches normally regulate gene expression through structural changes in response to the specific binding of cellular metabolites or metal ions. Taking add adenine riboswitch as an example, we explore the influences of metal ions (especially for K+ and Mg2+ ions) on the structure and dynamics of riboswitch aptamer (with and without ligand) by using molecular dynamic (MD) simulations. Our results show that a two-state transition marked by the structural deformation at the connection of J12 and P1 (CJ12-P1) is not only related to the binding of cognate ligands, but also strongly coupled with the change of metal ion environments. Moreover, the deformation of the structure at CJ12-P1 can be transmitted to P1 directly connected to the expression platform in multiple ways, which will affect the structure and stability of P1 to varying degrees, and finally change the regulation state of this riboswitch. Molecular dynamic simulations are employed to assess the influence of metal ions on riboswitch structure and dynamics, suggesting a conformational control of riboswitch aptamers by metal ions before ligand binding.
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20
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Zhou L, Wang X, Yu S, Tan YL, Tan ZJ. FebRNA: An automated fragment-ensemble-based model for building RNA 3D structures. Biophys J 2022; 121:3381-3392. [PMID: 35978551 PMCID: PMC9515226 DOI: 10.1016/j.bpj.2022.08.017] [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: 04/30/2022] [Revised: 07/19/2022] [Accepted: 08/15/2022] [Indexed: 11/23/2022] Open
Abstract
Knowledge of RNA three-dimensional (3D) structures is critical to understanding the important biological functions of RNAs. Although various structure prediction models have been developed, the high-accuracy predictions of RNA 3D structures are still limited to the RNAs with short lengths or with simple topology. In this work, we proposed a new model, namely FebRNA, for building RNA 3D structures through fragment assembly based on coarse-grained (CG) fragment ensembles. Specifically, FebRNA is composed of four processes: establishing the library of different types of non-redundant CG fragment ensembles regardless of the sequences, building CG 3D structure ensemble through fragment assembly, identifying top-scored CG structures through a specific CG scoring function, and rebuilding the all-atom structures from the top-scored CG ones. Extensive examination against different types of RNA structures indicates that FebRNA consistently gives the reliable predictions on RNA 3D structures, including pseudoknots, three-way junctions, four-way and five-way junctions, and RNAs in the RNA-Puzzles. FebRNA is available on the Web site: https://github.com/Tan-group/FebRNA.
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Affiliation(s)
- Li Zhou
- Department of Physics and Key Laboratory of Artificial Micro & Nano-structures of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China
| | - Xunxun Wang
- Department of Physics and Key Laboratory of Artificial Micro & Nano-structures of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China
| | - Shixiong Yu
- Department of Physics and Key Laboratory of Artificial Micro & Nano-structures of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China
| | - Ya-Lan Tan
- Research Center of Nonlinear Science, School of Mathematical and Physical Sciences, Wuhan Textile University, Wuhan 430073, China.
| | - Zhi-Jie Tan
- Department of Physics and Key Laboratory of Artificial Micro & Nano-structures of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China.
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21
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Sun LZ, Qian JL, Cai P, Xu X. Mutual effects between single-stranded DNA conformation and Na +-Mg 2+ ion competition in mixed salt solutions. Phys Chem Chem Phys 2022; 24:20867-20881. [PMID: 36043348 DOI: 10.1039/d2cp02737b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The ion-dependence of single-stranded DNA (ssDNA) conformational changes has attracted growing attention because of its biological and technological importance. Although single-species ion effects have been extensively explored, it is challenging to study the ssDNA conformational properties under mixed monovalent/divalent ion conditions due to the complications of ssDNA flexibility and ion-ion competition. In this study, we apply Langevin dynamics simulations to investigate mixed Na+/Mg2+ ion-dependent ssDNA conformations. The ssDNA structure is described using a coarse-grained model, in which the phosphate, base, and sugar of each nucleotide are represented by three different beads. A novel improvement in our simulation model is that mixed-salt-related electrostatic interactions are computed via combining Manning counterion condensation (MCC) theory with the Monte Carlo tightly bound ion (MCTBI) model. Based on this MCC-MCTBI combination, we report new empirical functions to describe the ion-concentration-dependent and ssDNA conformation/structure-dependent electrostatic effects. The calculation results relating to the ion binding properties and the simulation results relating to the ssDNA conformational properties are validated against experimental results. In addition, our simulation results suggest a quantitative relationship between the ssDNA conformation and Na+-Mg2+ competition; this in turn reveals their mutual impact in the ion atmosphere.
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Affiliation(s)
- Li-Zhen Sun
- Department of Applied Physics, Zhejiang University of Technology, Hangzhou 310023, China.
| | - Jun-Lin Qian
- Department of Applied Physics, Zhejiang University of Technology, Hangzhou 310023, China.
| | - Pinggen Cai
- Department of Applied Physics, Zhejiang University of Technology, Hangzhou 310023, China.
| | - Xiaojun Xu
- Institute of Bioinformatics and Medical Engineering, Jiangsu University of Technology, Changzhou, 213001, China
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22
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Martinez-Monge A, Pastor I, Bustamante C, Manosas M, Ritort F. Measurement of the specific and non-specific binding energies of Mg 2+ to RNA. Biophys J 2022; 121:3010-3022. [PMID: 35864738 PMCID: PMC9463699 DOI: 10.1016/j.bpj.2022.07.020] [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: 11/02/2022] Open
Abstract
Determining the non-specific and specific electrostatic contributions of magnesium binding to RNA is a challenging problem. We introduce a single-molecule method based on measuring the folding energy of a native RNA in magnesium and at its equivalent sodium concentration. The latter is defined so that the folding energy in sodium equals the non-specific electrostatic contribution in magnesium. The sodium equivalent can be estimated according to the empirical 100/1 rule (1 M NaCl is equivalent to 10 mM MgCl2), which is a good approximation for most RNAs. The method is applied to an RNA three-way junction (3WJ) that contains specific Mg2+ binding sites and misfolds into a double hairpin structure without binding sites. We mechanically pull the RNA with optical tweezers and use fluctuation theorems to determine the folding energies of the native and misfolded structures in magnesium (10 mM MgCl2) and at the equivalent sodium condition (1 M NaCl). While the free energies of the misfolded structure are equal in magnesium and sodium, they are not for the native structure, the difference being due to the specific binding energy of magnesium to the 3WJ, which equals ΔG≃ 10 kcal/mol. Besides stabilizing the 3WJ, Mg2+ also kinetically rescues it from the misfolded structure over timescales of tens of seconds in a force-dependent manner. The method should generally be applicable to determine the specific binding energies of divalent cations to other tertiary RNAs.
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Affiliation(s)
- A Martinez-Monge
- Small Biosystems Lab, Departament de Física de la Matèria Condensada, Facultat de Física, Universitat de Barcelona, Carrer de Martí i Franquès, 1, 08028 Barcelona, Spain
| | - Isabel Pastor
- Small Biosystems Lab, Departament de Física de la Matèria Condensada, Facultat de Física, Universitat de Barcelona, Carrer de Martí i Franquès, 1, 08028 Barcelona, Spain; Institut de Nanociència i Nanotecnologia (IN2UB), Universitat de Barcelona, 08028 Barcelona, Spain
| | - Carlos Bustamante
- Departments of Chemistry, Physics and Molecular and Cell Biology, University of California Berkeley, Berkeley, California; Howard Hughes Medical Institute University of California Berkeley, Berkeley, California; Kavli Energy Nanosciences Institute, University of California Berkeley, Berkeley, California
| | - Maria Manosas
- Small Biosystems Lab, Departament de Física de la Matèria Condensada, Facultat de Física, Universitat de Barcelona, Carrer de Martí i Franquès, 1, 08028 Barcelona, Spain; Institut de Nanociència i Nanotecnologia (IN2UB), Universitat de Barcelona, 08028 Barcelona, Spain.
| | - Felix Ritort
- Small Biosystems Lab, Departament de Física de la Matèria Condensada, Facultat de Física, Universitat de Barcelona, Carrer de Martí i Franquès, 1, 08028 Barcelona, Spain; Institut de Nanociència i Nanotecnologia (IN2UB), Universitat de Barcelona, 08028 Barcelona, Spain.
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23
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Zhang M, Hwang IT, Li K, Bai J, Chen JF, Weissman T, Zou JY, Lu Z. Classification and clustering of RNA crosslink-ligation data reveal complex structures and homodimers. Genome Res 2022; 32:968-985. [PMID: 35332099 PMCID: PMC9104705 DOI: 10.1101/gr.275979.121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Accepted: 01/11/2022] [Indexed: 12/04/2022]
Abstract
The recent development and application of methods based on the general principle of "crosslinking and proximity ligation" (crosslink-ligation) are revolutionizing RNA structure studies in living cells. However, extracting structure information from such data presents unique challenges. Here, we introduce a set of computational tools for the systematic analysis of data from a wide variety of crosslink-ligation methods, specifically focusing on read mapping, alignment classification, and clustering. We design a new strategy to map short reads with irregular gaps at high sensitivity and specificity. Analysis of previously published data reveals distinct properties and bias caused by the crosslinking reactions. We perform rigorous and exhaustive classification of alignments and discover eight types of arrangements that provide distinct information on RNA structures and interactions. To deconvolve the dense and intertwined gapped alignments, we develop a network/graph-based tool Crosslinked RNA Secondary Structure Analysis using Network Techniques (CRSSANT), which enables clustering of gapped alignments and discovery of new alternative and dynamic conformations. We discover that multiple crosslinking and ligation events can occur on the same RNA, generating multisegment alignments to report complex high-level RNA structures and multi-RNA interactions. We find that alignments with overlapped segments are produced from potential homodimers and develop a new method for their de novo identification. Analysis of overlapping alignments revealed potential new homodimers in cellular noncoding RNAs and RNA virus genomes in the Picornaviridae family. Together, this suite of computational tools enables rapid and efficient analysis of RNA structure and interaction data in living cells.
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Affiliation(s)
- Minjie Zhang
- Department of Pharmacology and Pharmaceutical Sciences, University of Southern California, Los Angeles, California 90089, USA
| | - Irena T Hwang
- Department of Electrical Engineering, Stanford University, Stanford, California 94305, USA
| | - Kongpan Li
- Department of Pharmacology and Pharmaceutical Sciences, University of Southern California, Los Angeles, California 90089, USA
| | - Jianhui Bai
- Department of Pharmacology and Pharmaceutical Sciences, University of Southern California, Los Angeles, California 90089, USA
| | - Jian-Fu Chen
- Center for Craniofacial Molecular Biology, University of Southern California (USC), Los Angeles, California 90033, USA
| | - Tsachy Weissman
- Department of Electrical Engineering, Stanford University, Stanford, California 94305, USA
| | - James Y Zou
- Department of Electrical Engineering, Stanford University, Stanford, California 94305, USA
- Department of Biomedical Data Science and Chan-Zuckerberg Biohub, Stanford University, Palo Alto, California 94305, USA
| | - Zhipeng Lu
- Department of Pharmacology and Pharmaceutical Sciences, University of Southern California, Los Angeles, California 90089, USA
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24
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Sun LZ, Qian JL, Cai P, Hu HX, Xu X, Luo MB. Mg2+ effects on the single-stranded DNA conformations and nanopore translocation dynamics. POLYMER 2022. [DOI: 10.1016/j.polymer.2022.124895] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
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25
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Zhang S, Cheng Y, Guo P, Chen SJ. VfoldMCPX: predicting multistrand RNA complexes. RNA (NEW YORK, N.Y.) 2022; 28:596-608. [PMID: 35058350 PMCID: PMC8925972 DOI: 10.1261/rna.079020.121] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Accepted: 01/10/2022] [Indexed: 06/14/2023]
Abstract
Multistrand RNA complexes play a critical role in RNA-related biological processes. The understanding of RNA functions and the rational design of RNA nanostructures require accurate prediction of the structure and folding stability of the complexes, including those containing pseudoknots. Here, we present VfoldMCPX, a new model for predicting two-dimensional (2D) structures and folding stabilities of multistrand RNA complexes. Based on a partition function-based algorithm combined with physical loop free energy parameters, the VfoldMCPX model predicts not only the native structure but also the folding stability of the complex. An important advantage of the model is the ability to treat pseudoknotted structures. Extensive tests on structure predictions show the VfoldMCPX model provides improved accuracy for multistranded RNA complexes, especially for RNA complexes with three or more strands and/or containing pseudoknots. We have developed a freely accessible VfoldMCPX web server at http://rna.physics.missouri.edu/vfoldMCPX2.
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Affiliation(s)
- Sicheng Zhang
- Department of Physics, Department of Biochemistry, and Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri 65211, USA
| | - Yi Cheng
- Department of Physics, Department of Biochemistry, and Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri 65211, USA
| | - Peixuan Guo
- Center for RNA Nanobiotechnology and Nanomedicine, College of Pharmacy, Dorothy M. Davis Heart and Lung Research Institute, James Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio 43210, USA
| | - Shi-Jie Chen
- Department of Physics, Department of Biochemistry, and Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri 65211, USA
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26
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Qiang XW, Zhang C, Dong HL, Tian FJ, Fu H, Yang YJ, Dai L, Zhang XH, Tan ZJ. Multivalent Cations Reverse the Twist-Stretch Coupling of RNA. PHYSICAL REVIEW LETTERS 2022; 128:108103. [PMID: 35333091 DOI: 10.1103/physrevlett.128.108103] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 02/10/2022] [Indexed: 06/14/2023]
Abstract
When stretched, both DNA and RNA duplexes change their twist angles through twist-stretch coupling. The coupling is negative for DNA but positive for RNA, which is not yet completely understood. Here, our magnetic tweezers experiments show that the coupling of RNA reverses from positive to negative by multivalent cations. Combining with the previously reported tension-induced negative-to-positive coupling reversal of DNA, we propose a unified mechanism of the couplings of both RNA and DNA based on molecular dynamics simulations. Two deformation pathways are competing when stretched: shrinking the radius causes positive couplings but widening the major groove causes negative couplings. For RNA whose major groove is clamped by multivalent cations and canonical DNA, their radii shrink when stretched, thus exhibiting positive couplings. For elongated DNA whose radius already shrinks to the minimum and canonical RNA, their major grooves are widened when stretched, thus exhibiting negative couplings.
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Affiliation(s)
- Xiao-Wei Qiang
- Department of Physics and Key Laboratory of Artificial Micro & Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China
| | - Chen Zhang
- College of Life Sciences, the Institute for Advanced Studies, State Key Laboratory of Virology, Hubei Key Laboratory of Cell Homeostasis, Wuhan University, Wuhan 430072, China
| | - Hai-Long Dong
- Department of Physics and Key Laboratory of Artificial Micro & Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China
| | - Fu-Jia Tian
- Department of Physics, City University of Hong Kong, Hong Kong 999077, China
| | - Hang Fu
- College of Life Sciences, the Institute for Advanced Studies, State Key Laboratory of Virology, Hubei Key Laboratory of Cell Homeostasis, Wuhan University, Wuhan 430072, China
| | - Ya-Jun Yang
- College of Life Sciences, the Institute for Advanced Studies, State Key Laboratory of Virology, Hubei Key Laboratory of Cell Homeostasis, Wuhan University, Wuhan 430072, China
| | - Liang Dai
- Department of Physics, City University of Hong Kong, Hong Kong 999077, China
| | - Xing-Hua Zhang
- College of Life Sciences, the Institute for Advanced Studies, State Key Laboratory of Virology, Hubei Key Laboratory of Cell Homeostasis, Wuhan University, Wuhan 430072, China
| | - Zhi-Jie Tan
- Department of Physics and Key Laboratory of Artificial Micro & Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China
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27
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rsRNASP: A residue-separation-based statistical potential for RNA 3D structure evaluation. Biophys J 2022; 121:142-156. [PMID: 34798137 PMCID: PMC8758408 DOI: 10.1016/j.bpj.2021.11.016] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 10/23/2021] [Accepted: 11/10/2021] [Indexed: 01/07/2023] Open
Abstract
Knowledge-based statistical potentials have been shown to be rather effective in protein 3-dimensional (3D) structure evaluation and prediction. Recently, several statistical potentials have been developed for RNA 3D structure evaluation, while their performances are either still at a low level for the test datasets from structure prediction models or dependent on the "black-box" process through neural networks. In this work, we have developed an all-atom distance-dependent statistical potential based on residue separation for RNA 3D structure evaluation, namely rsRNASP, which is composed of short- and long-ranged potentials distinguished by residue separation. The extensive examinations against available RNA test datasets show that rsRNASP has apparently higher performance than the existing statistical potentials for the realistic test datasets with large RNAs from structure prediction models, including the newly released RNA-Puzzles dataset, and is comparable to the existing top statistical potentials for the test datasets with small RNAs or near-native decoys. In addition, rsRNASP is superior to RNA3DCNN, a recently developed scoring function through 3D convolutional neural networks. rsRNASP and the relevant databases are available to the public.
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28
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Jiang Y, Chen SJ. RLDOCK method for predicting RNA-small molecule binding modes. Methods 2022; 197:97-105. [PMID: 33549725 PMCID: PMC8333169 DOI: 10.1016/j.ymeth.2021.01.009] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 01/24/2021] [Accepted: 01/27/2021] [Indexed: 01/03/2023] Open
Abstract
RNA molecules play critical roles in cellular functions at the level of gene expression and regulation. The intricate 3D structures and the functional roles of RNAs make RNA molecules ideal targets for therapeutic drugs. The rational design of RNA-targeted drug requires accurate modeling of RNA-ligand interactions. Recently a new computational tool, RLDOCK, was developed to predict ligand binding sites and binding poses. Using an iterative multiscale sampling and search algorithm and a energy-based evaluation of ligand poses, the method enables efficient and accurate predictions for RNA-ligand interactions. Here we present a detailed illustration of the computational procedure for the practical implementation of the RLDOCK method. Using Flavin mononucleotide (FMN) docking to F. nucleatum FMN riboswitch as an example, we illustrate the computational protocol for RLDOCK-based prediction of RNA- ligand interactions. The RLDOCK software is freely accessible at http://https://github.com/Vfold-RNA/RLDOCK.
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Affiliation(s)
- Yangwei Jiang
- Department of Physics, MU Institute for Data Science and Informatics, Department of Biochemistry, University of Missouri, Columbia, MO 65211, USA
| | - Shi-Jie Chen
- Department of Physics, MU Institute for Data Science and Informatics, Department of Biochemistry, University of Missouri, Columbia, MO 65211, USA.
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29
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Zhang D, Chen SJ, Zhou R. Modeling Noncanonical RNA Base Pairs by a Coarse-Grained IsRNA2 Model. J Phys Chem B 2021; 125:11907-11915. [PMID: 34694128 DOI: 10.1021/acs.jpcb.1c07288] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Noncanonical base pairs contribute crucially to the three-dimensional architecture of large RNA molecules; however, how to accurately model them remains an open challenge in RNA 3D structure prediction. Here, we report a promising coarse-grained (CG) IsRNA2 model to predict noncanonical base pairs in large RNAs through molecular dynamics simulations. By introducing a five-bead per nucleotide CG representation to reserve the three interacting edges of nucleobases, IsRNA2 accurately models various base-pairing interactions, including both canonical and noncanonical base pairs. A benchmark test indicated that IsRNA2 achieves a comparable performance to the atomic model in de novo modeling of noncanonical RNA structures. In addition, IsRNA2 was able to refine the 3D structure predictions for large RNAs in RNA-puzzle challenges. Finally, the graphics processing unit acceleration was introduced to speed up the sampling efficiency in IsRNA2 for very large RNA molecules. Therefore, the CG IsRNA2 model reported here offers a reliable approach to predict the structures and dynamics of large RNAs.
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Affiliation(s)
- Dong Zhang
- College of Life Sciences and Institute of Quantitative Biology, Zhejiang University, Hangzhou 310058, China
| | - Shi-Jie Chen
- Department of Physics, Department of Biochemistry, and Institute of Data Science and Informatics, University of Missouri, Columbia, Missouri 65211, United States
| | - Ruhong Zhou
- College of Life Sciences and Institute of Quantitative Biology, Zhejiang University, Hangzhou 310058, China
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30
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Feng Y, Yan Y, He J, Tao H, Wu Q, Huang SY. Docking and scoring for nucleic acid-ligand interactions: Principles and current status. Drug Discov Today 2021; 27:838-847. [PMID: 34718205 DOI: 10.1016/j.drudis.2021.10.013] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 09/06/2021] [Accepted: 10/20/2021] [Indexed: 12/24/2022]
Abstract
Nucleic acid (NA)-ligand interactions have crucial roles in many cellular processes and, thus, are increasingly attracting therapeutic interest in drug discovery. Molecular docking is a valuable tool for studying molecular interactions. However, because NAs differ significantly from proteins in both their physical and chemical properties, traditional docking algorithms and scoring functions for protein-ligand interactions might not be applicable to NA-ligand docking. Therefore, various sampling strategies and scoring functions for NA-ligand interactions have been developed. Here, we review the basic principles and current status of docking algorithms and scoring functions for DNA/RNA-ligand interactions. We also discuss challenges and limitations of current docking and scoring approaches.
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Affiliation(s)
- Yuyu Feng
- School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, PR China
| | - Yumeng Yan
- School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, PR China
| | - Jiahua He
- School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, PR China
| | - Huanyu Tao
- School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, PR China
| | - Qilong Wu
- School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, PR China
| | - Sheng-You Huang
- School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, PR China.
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31
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Cheng Y, Zhang S, Xu X, Chen SJ. Vfold2D-MC: A Physics-Based Hybrid Model for Predicting RNA Secondary Structure Folding. J Phys Chem B 2021; 125:10108-10118. [PMID: 34473508 DOI: 10.1021/acs.jpcb.1c04731] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Accurate prediction of RNA structure and folding stability has a far-reaching impact on our understanding of RNA functions. Here we develop Vfold2D-MC, a new physics-based model, to predict RNA structure and folding thermodynamics from the sequence. The model employs virtual bond-based coarse-graining of RNA backbone conformation and generates RNA conformations through Monte Carlo sampling of the bond angles and torsional angles of the virtual bonds. Using a coarse-grained statistical potential derived from the known structures, we assign each conformation with a statistical weight. The weighted average over the conformational ensemble gives the entropy and free energy parameters for the hairpin, bulge, and internal loops, and multiway junctions. From the thermodynamic parameters, we predict RNA structures, melting curves, and structural changes from the sequence. Theory-experiment comparisons indicate that Vfold2D-MC not only gives improved structure predictions but also enables the interpretation of thermodynamic results for different RNA structures, including multibranched junctions. This new model sets a promising framework to treat more complicated RNA structures, such as pseudoknotted and intramolecular kissing loops, for which experimental thermodynamic parameters are often unavailable.
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Affiliation(s)
- Yi Cheng
- Department of Physics, Department of Biochemistry, and Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri 65211, United States
| | - Sicheng Zhang
- Department of Physics, Department of Biochemistry, and Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri 65211, United States
| | - Xiaojun Xu
- Institute of Bioinformatics and Medical Engineering, Jiangsu University of Technology, Changzhou, Jiangsu 213001, China
| | - Shi-Jie Chen
- Department of Physics, Department of Biochemistry, and Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri 65211, United States
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32
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Predicting RNA Scaffolds with a Hybrid Method of Vfold3D and VfoldLA. Methods Mol Biol 2021. [PMID: 34086269 DOI: 10.1007/978-1-0716-1499-0_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/30/2023]
Abstract
The ever-increasing discoveries of noncoding RNA functions draw a strong demand for RNA structure determination from the sequence. In recently years, computational studies for RNA structures, at both the two-dimensional and the three-dimensional levels, led to several highly promising new developments. In this chapter, we describe a hybrid method, which combines the motif template-based Vfold3D model and the loop template-based VfoldLA model, to predict RNA 3D structures. The main emphasis is placed on the definition of motifs and loops, the treatment of no-template motifs, and the 3D structure assembly from templates of motifs and loops. For illustration, we use the ZIKV xrRNA1 as an example to show the template-based prediction of RNA 3D structures from the 2D structure. The web server for the hybrid model is freely accessible at http://rna.physics.missouri.edu/vfold3D2 .
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33
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Schlick T, Zhu Q, Dey A, Jain S, Yan S, Laederach A. To Knot or Not to Knot: Multiple Conformations of the SARS-CoV-2 Frameshifting RNA Element. J Am Chem Soc 2021; 143:11404-11422. [PMID: 34283611 PMCID: PMC8315264 DOI: 10.1021/jacs.1c03003] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
The SARS-CoV-2 frameshifting RNA element (FSE) is an excellent target for therapeutic intervention against Covid-19. This small gene element employs a shifting mechanism to pause and backtrack the ribosome during translation between Open Reading Frames 1a and 1b, which code for viral polyproteins. Any interference with this process has a profound effect on viral replication and propagation. Pinpointing the structures adapted by the FSE and associated structural transformations involved in frameshifting has been a challenge. Using our graph-theory-based modeling tools for representing RNA secondary structures, "RAG" (RNA-As-Graphs), and chemical structure probing experiments, we show that the 3-stem H-type pseudoknot (3_6 dual graph), long assumed to be the dominant structure, has a viable alternative, an HL-type 3-stem pseudoknot (3_3) for longer constructs. In addition, an unknotted 3-way junction RNA (3_5) emerges as a minor conformation. These three conformations share Stems 1 and 3, while the different Stem 2 may be involved in a conformational switch and possibly associations with the ribosome during translation. For full-length genomes, a stem-loop motif (2_2) may compete with these forms. These structural and mechanistic insights advance our understanding of the SARS-CoV-2 frameshifting process and concomitant virus life cycle, and point to three avenues of therapeutic intervention.
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Affiliation(s)
- Tamar Schlick
- Department of Chemistry, New York University, 100 Washington Square East, Silver Building, New York, New York 10003, United States
- Courant Institute of Mathematical Sciences, New York University, 251 Mercer Street, New York, New York 10012, United States
- New York University-East China Normal University Center for Computational Chemistry, New York University-Shanghai, Shanghai 200062, P. R. China
| | - Qiyao Zhu
- Courant Institute of Mathematical Sciences, New York University, 251 Mercer Street, New York, New York 10012, United States
| | - Abhishek Dey
- Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Swati Jain
- Department of Chemistry, New York University, 100 Washington Square East, Silver Building, New York, New York 10003, United States
| | - Shuting Yan
- Department of Chemistry, New York University, 100 Washington Square East, Silver Building, New York, New York 10003, United States
| | - Alain Laederach
- Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States
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34
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Schlick T, Zhu Q, Dey A, Jain S, Yan S, Laederach A. To knot or not to knot: Multiple conformations of the SARS-CoV-2 frameshifting RNA element. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.03.31.437955. [PMID: 33821274 PMCID: PMC8020974 DOI: 10.1101/2021.03.31.437955] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
The SARS-CoV-2 frameshifting RNA element (FSE) is an excellent target for therapeutic intervention against Covid-19. This small gene element employs a shifting mechanism to pause and backtrack the ribosome during translation between Open Reading Frames 1a and 1b, which code for viral polyproteins. Any interference with this process has profound effect on viral replication and propagation. Pinpointing the structures adapted by the FSE and associated structural transformations involved in frameshifting has been a challenge. Using our graph-theory-based modeling tools for representing RNA secondary structures, "RAG" (RNA-As-Graphs), and chemical structure probing experiments, we show that the 3-stem H-type pseudoknot (3_6 dual graph), long assumed to be the dominant structure has a viable alternative, an HL-type 3-stem pseudoknot (3_3) for longer constructs. In addition, an unknotted 3-way junction RNA (3_5) emerges as a minor conformation. These three conformations share Stems 1 and 3, while the different Stem 2 may be involved in a conformational switch and possibly associations with the ribosome during translation. For full-length genomes, a stem-loop motif (2_2) may compete with these forms. These structural and mechanistic insights advance our understanding of the SARS-CoV-2 frameshifting process and concomitant virus life cycle, and point to three avenues of therapeutic intervention.
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Affiliation(s)
- Tamar Schlick
- Department of Chemistry, 100 Washington Square East, Silver Building, New York University, New York, NY 10003 U.S.A
- Courant Institute of Mathematical Sciences, New York University, 251 Mercer St., New York, NY 10012 U.S.A
- NYU-ECNU Center for Computational Chemistry, NYU Shanghai, Shanghai 200062, P.R. China
| | - Qiyao Zhu
- Courant Institute of Mathematical Sciences, New York University, 251 Mercer St., New York, NY 10012 U.S.A
| | - Abhishek Dey
- Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599
| | - Swati Jain
- Department of Chemistry, 100 Washington Square East, Silver Building, New York University, New York, NY 10003 U.S.A
| | - Shuting Yan
- Department of Chemistry, 100 Washington Square East, Silver Building, New York University, New York, NY 10003 U.S.A
| | - Alain Laederach
- Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599
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35
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Pairing a high-resolution statistical potential with a nucleobase-centric sampling algorithm for improving RNA model refinement. Nat Commun 2021; 12:2777. [PMID: 33986288 PMCID: PMC8119458 DOI: 10.1038/s41467-021-23100-4] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Accepted: 04/13/2021] [Indexed: 12/04/2022] Open
Abstract
Refining modelled structures to approach experimental accuracy is one of the most challenging problems in molecular biology. Despite many years’ efforts, the progress in protein or RNA structure refinement has been slow because the global minimum given by the energy scores is not at the experimentally determined “native” structure. Here, we propose a fully knowledge-based energy function that captures the full orientation dependence of base–base, base–oxygen and oxygen–oxygen interactions with the RNA backbone modelled by rotameric states and internal energies. A total of 4000 quantum-mechanical calculations were performed to reweight base–base statistical potentials for minimizing possible effects of indirect interactions. The resulting BRiQ knowledge-based potential, equipped with a nucleobase-centric sampling algorithm, provides a robust improvement in refining near-native RNA models generated by a wide variety of modelling techniques. Predicting RNA structure from sequence is challenging due to the relative sparsity of experimentally-determined RNA 3D structures for model training. Here, the authors propose a way to incorporate knowledge on interactions at the atomic and base–base level to refine the prediction of RNA structures.
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36
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Lin C, Qiang X, Dong HL, Huo J, Tan ZJ. Multivalent Ion-Mediated Attraction between Like-Charged Colloidal Particles: Nonmonotonic Dependence on the Particle Charge. ACS OMEGA 2021; 6:9876-9886. [PMID: 33869968 PMCID: PMC8047654 DOI: 10.1021/acsomega.1c00613] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 03/26/2021] [Indexed: 06/12/2023]
Abstract
Ion-mediated effective interactions are important for the structure and stability of charged particles such as colloids and nucleic acids. It has been known that the intrinsic electrostatic repulsion between like-charged particles can be modulated into effective attraction by multivalent ions. In this work, we examined the dependence of multivalent ion-mediated attraction between like-charged colloidal particles on the particle charge in a wide range by extensive Monte Carlo simulations. Our calculations show that for both divalent and trivalent salts, the effective attraction between like-charged colloidal particles becomes stronger with the increase of the particle charge, whereas it gradually becomes weakened when the particle charge exceeds a "critical" value. Correspondingly, as the particle charge is increased, the driving force for such effective attraction transits from an attractive electrostatic force to an attractive depletion force, and the attraction weakening by high particle charges is attributed to the transition of electrostatic force from attraction to repulsion. Our analyses suggest that the attractive depletion force and the repulsive electrostatic force at high particle charges result from the Coulomb depletion which suppresses the counterion condensation in the limited region between two like-charged colloidal particles. Moreover, our extensive calculations indicate that the "critical" particle charge decreases apparently for larger ions and smaller colloidal particles due to stronger Coulomb depletion and decreases slightly at higher salt concentrations due to the slightly enhanced Coulomb depletion in the intervening space between colloidal particles. Encouragingly, we derived an analytical formula for the "critical" particle charge based on the Lindemann melting law.
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Affiliation(s)
- Cheng Lin
- Center
for Theoretical Physics and Key Laboratory of Artificial Micro &
Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China
| | - Xiaowei Qiang
- Center
for Theoretical Physics and Key Laboratory of Artificial Micro &
Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China
| | - Hai-Long Dong
- Center
for Theoretical Physics and Key Laboratory of Artificial Micro &
Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China
| | - Jie Huo
- Center
for Theoretical Physics and Key Laboratory of Artificial Micro &
Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China
- School
of Physics and Electronic-Electrical Engineering, Ningxia University, Yinchuan 750021, China
| | - Zhi-Jie Tan
- Center
for Theoretical Physics and Key Laboratory of Artificial Micro &
Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China
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37
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Grotz KK, Cruz-León S, Schwierz N. Optimized Magnesium Force Field Parameters for Biomolecular Simulations with Accurate Solvation, Ion-Binding, and Water-Exchange Properties. J Chem Theory Comput 2021; 17:2530-2540. [PMID: 33720710 PMCID: PMC8047801 DOI: 10.1021/acs.jctc.0c01281] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Indexed: 12/31/2022]
Abstract
Magnesium ions play an essential role in many vital processes. To correctly describe their interactions in molecular dynamics simulations, an accurate parametrization is crucial. Despite the importance and considerable scientific effort, current force fields based on the commonly used 12-6 Lennard-Jones interaction potential fail to reproduce a variety of experimental solution properties. In particular, no parametrization exists so far that simultaneously reproduces the solvation free energy and the distance to the water oxygens in the first hydration shell. Moreover, current Mg2+ force fields significantly underestimate the rate of water exchange leading to unrealistically slow exchange kinetics. In order to make progress in the development of improved models, we systematically optimize the Mg2+ parameters in combination with the TIP3P water model in a much larger parameter space than previously done. The results show that a long-ranged interaction potential and modified Lorentz-Berthelot combination rules allow us to accurately reproduce multiple experimental properties including the solvation free energy, the distances to the oxygens of the first hydration shell, the hydration number, the activity coefficient derivative in MgCl2 solutions, the self-diffusion coefficient, and the binding affinity to the phosphate oxygen of RNA. Matching this broad range of thermodynamic properties, we present two sets of optimal parameters: MicroMg yields water exchange on the microsecond timescale in agreement with experiments. NanoMg yields water exchange on the nanosecond timescale facilitating the direct observation of ion-binding events. As shown for the example of the add A-riboswitch, the optimized parameters correctly reproduce the structure of specifically bound ions and permit the de novo prediction of Mg2+-binding sites in biomolecular simulations.
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Affiliation(s)
- Kara K. Grotz
- Department of Theoretical Biophysics, Max-Planck-Institute of Biophysics, Frankfurt am Main 60438, Germany
| | - Sergio Cruz-León
- Department of Theoretical Biophysics, Max-Planck-Institute of Biophysics, Frankfurt am Main 60438, Germany
| | - Nadine Schwierz
- Department of Theoretical Biophysics, Max-Planck-Institute of Biophysics, Frankfurt am Main 60438, Germany
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38
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Zhang D, Li J, Chen SJ. IsRNA1: De Novo Prediction and Blind Screening of RNA 3D Structures. J Chem Theory Comput 2021; 17:1842-1857. [PMID: 33560836 DOI: 10.1021/acs.jctc.0c01148] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Modeling structures and functions of large ribonucleic acid (RNAs) especially with complicated topologies is highly challenging due to the inefficiency of large conformational sampling and the presence of complicated tertiary interactions. To address this problem, one highly promising approach is coarse-grained modeling. Here, following an iterative simulated reference state approach to decipher the correlations between different structural parameters, we developed a potent coarse-grained RNA model named as IsRNA1 for RNA studies. Molecular dynamics simulations in the IsRNA1 can predict the native structures of small RNAs from a sequence and fold medium-sized RNAs into near-native tertiary structures with the assistance of secondary structure constraints. A large-scale benchmark test on RNA 3D structure prediction shows that IsRNA1 exhibits improved performance for relatively large RNAs of complicated topologies, such as large stem-loop structures and structures containing long-range tertiary interactions. The advantages of IsRNA1 include the consideration of the correlations between the different structural variables, the appropriate characterization of canonical base-pairing and base-stacking interactions, and the better sampling for the backbone conformations. Moreover, a blind screening protocol was developed based on IsRNA1 to identify good structural models from a pool of candidates without prior knowledge of the native structures.
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Affiliation(s)
- Dong Zhang
- Department of Physics, Department of Biochemistry, and Institute of Data Science and Informatics, University of Missouri, Columbia, Missouri 65211, United States
| | - Jun Li
- Department of Physics, Department of Biochemistry, and Institute of Data Science and Informatics, University of Missouri, Columbia, Missouri 65211, United States
| | - Shi-Jie Chen
- Department of Physics, Department of Biochemistry, and Institute of Data Science and Informatics, University of Missouri, Columbia, Missouri 65211, United States
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39
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Feng Y, Huang SY. ITScore-NL: An Iterative Knowledge-Based Scoring Function for Nucleic Acid-Ligand Interactions. J Chem Inf Model 2020; 60:6698-6708. [PMID: 33291885 DOI: 10.1021/acs.jcim.0c00974] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Nucleic acid-ligand complexes underlie numerous cellular processes, such as gene function expression and regulation, in which their three-dimensional structures are important to understand their functions and thus to develop therapeutic interventions. Given the high cost and technical difficulties in experimental methods, computational methods such as molecular docking have been actively used to investigate nucleic acid-ligand interactions in which an accurate scoring function is crucial. However, because of the limited number of experimental nucleic acid-ligand binding data and structures, the scoring function development for nucleic acid-ligand interactions falls far behind that for protein-protein and protein-ligand interactions. Here, based on our statistical mechanics-based iterative approach, we have developed an iterative knowledge-based scoring function for nucleic acid-ligand interactions, named as ITScore-NL, by explicitly including stacking and electrostatic potentials. Our ITScore-NL scoring function was extensively evaluated for its ability in the binding mode and binding affinity predictions on three diverse test sets and compared with state-of-the-art scoring functions. Overall, ITScore-NL obtained significantly better performance than the other 12 scoring functions and predicted near-native poses with rmsd ≤ 1.5 Å for 71.43% of the cases when the top three binding modes were considered and a good correlation of R = 0.64 in binding affinity prediction on the large test set of 77 nucleic acid-ligand complexes. These results suggested the accuracy of ITScore-NL and the necessity of explicitly including stacking and electrostatic potentials.
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Affiliation(s)
- Yuyu Feng
- School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, P. R. China
| | - Sheng-You Huang
- School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, P. R. China
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40
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Zheng Y, Lin C, Zhang JS, Tan ZJ. Ion-mediated interactions between like-charged polyelectrolytes with bending flexibility. Sci Rep 2020; 10:21586. [PMID: 33299024 PMCID: PMC7726156 DOI: 10.1038/s41598-020-78684-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 11/27/2020] [Indexed: 12/12/2022] Open
Abstract
Ion-mediated interactions between polyelectrolytes (PEs) are crucial to the properties of flexible biopolymers such as nucleic acids and proteins but the effect of PE flexibility on such interactions has not been explicitly addressed until now. In this work, the potentials of mean force (PMFs) between like-charged PEs with different bending flexibility have been investigated by Monte Carlo simulations and a cylindrical confinement around each PE was involved to model two PEs in an array. We found that in the absence of trivalent salt, the PMFs between like-charged PEs in an array are apparently repulsive while the bending flexibility can visibly decrease the repulsive PMFs. With the addition of high trivalent salt, the PMFs become significantly attractive whereas the attractive PMFs can be apparently weakened by the bending flexibility. Our analyses reveal that the effect of bending flexibility is attributed to the increased PE conformational space, which allows the PEs to fluctuate away to decrease the monovalent ion-mediated repulsion or to weaken the trivalent ion-mediated attraction through disrupting trivalent ion-bridging configuration. Additionally, our further calculations show that the effect of bending flexibility on the ion-mediated interactions is less apparent for PEs without cylindrical confinement.
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Affiliation(s)
- Yitong Zheng
- Hongyi Honor School, Wuhan University, Wuhan, 430072, China
- Department of Physics and Key Laboratory of Artificial Micro and Nano-Structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan, 430072, China
| | - Cheng Lin
- Department of Physics and Key Laboratory of Artificial Micro and Nano-Structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan, 430072, China
| | - Jin-Si Zhang
- College of Electrical and Photoelectronic Engineering, West Anhui University, Lu'an, 237012, China
| | - Zhi-Jie Tan
- Department of Physics and Key Laboratory of Artificial Micro and Nano-Structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan, 430072, China.
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41
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Sun LZ, Jiang Y, Zhou Y, Chen SJ. RLDOCK: A New Method for Predicting RNA-Ligand Interactions. J Chem Theory Comput 2020; 16:7173-7183. [PMID: 33095555 DOI: 10.1021/acs.jctc.0c00798] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
The ability to accurately predict the binding site, binding pose, and binding affinity for ligand-RNA binding is important for RNA-targeted drug design. Here, we describe a new computational method, RLDOCK, for predicting the binding site and binding pose for ligand-RNA binding. By developing an energy-based scoring function, we sample exhaustively all of the possible binding sites with flexible ligand conformations for a ligand-RNA pair based on the geometric and energetic scores. The model distinguishes from other approaches in three notable features. First, the model enables exhaustive scanning of all of the possible binding sites, including multiple alternative or coexisting binding sites, for a given ligand-RNA pair. Second, the model is based on a new energy-based scoring function developed here. Third, the model employs a novel multistep screening algorithm to improve computational efficiency. Specifically, first, for each binding site, we use a gird-based energy map to rank the binding sites according to the minimum Lennard-Jones potential energy for the different ligand poses. Second, for a given selected binding site, we predict the ligand pose using a two-step algorithm. In the first step, we quickly identify the probable ligand poses using a coarse-grained simplified energy function. In the second step, for each of the probable ligand poses, we predict the ligand poses using a refined energy function. Tests of the RLDOCK for a set of 230 RNA-ligand-bound structures indicate that RLDOCK can successfully predict ligand poses for 27.8, 58.3, and 69.6% of all of the test cases with the root-mean-square deviation within 1.0, 2.0, and 3.0 Å, respectively, for the top three predicted docking poses. The computational method presented here may enable the development of a new, more comprehensive framework for the prediction of ligand-RNA binding with an ensemble of RNA conformations and the metal-ion effects.
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Affiliation(s)
- Li-Zhen Sun
- Department of Applied Physics, Zhejiang University of Technology, Hangzhou 310023, China.,Department of Physics, Department of Biochemistry, and Informatics Institute, University of Missouri, Columbia, Missouri 65211, United States
| | - Yangwei Jiang
- Department of Physics, Department of Biochemistry, and Informatics Institute, University of Missouri, Columbia, Missouri 65211, United States
| | - Yuanzhe Zhou
- Department of Physics, Department of Biochemistry, and Informatics Institute, University of Missouri, Columbia, Missouri 65211, United States
| | - Shi-Jie Chen
- Department of Physics, Department of Biochemistry, and Informatics Institute, University of Missouri, Columbia, Missouri 65211, United States
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42
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Navien TN, Thevendran R, Hamdani HY, Tang TH, Citartan M. In silico molecular docking in DNA aptamer development. Biochimie 2020; 180:54-67. [PMID: 33086095 DOI: 10.1016/j.biochi.2020.10.005] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 09/23/2020] [Accepted: 10/14/2020] [Indexed: 12/21/2022]
Abstract
Aptamers are single-stranded DNA or RNA oligonucleotides generated by SELEX that exhibit binding affinity and specificity against a wide variety of target molecules. Compared to RNA aptamers, DNA aptamers are much more stable and therefore are widely adopted in a number of applications especially in diagnostics. The tediousness and rigor associated with certain steps of the SELEX intensify the efforts to adopt in silico molecular docking approaches together with in vitro SELEX procedures in developing DNA aptamers. Inspired by these endeavors, we carry out an overview of the in silico molecular docking approaches in DNA aptamer generation, by detailing the stepwise procedures as well as shedding some light on the various softwares used. The in silico maturation strategy and the limitations of the in silico approaches are also underscored.
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Affiliation(s)
- Tholasi Nadhan Navien
- Advanced Medical & Dental Institute (AMDI), Universiti Sains Malaysia, Bertam, 13200, Kepala Batas, Penang, Malaysia
| | - Ramesh Thevendran
- Advanced Medical & Dental Institute (AMDI), Universiti Sains Malaysia, Bertam, 13200, Kepala Batas, Penang, Malaysia
| | - Hazrina Yusof Hamdani
- Advanced Medical & Dental Institute (AMDI), Universiti Sains Malaysia, Bertam, 13200, Kepala Batas, Penang, Malaysia
| | - Thean-Hock Tang
- Advanced Medical & Dental Institute (AMDI), Universiti Sains Malaysia, Bertam, 13200, Kepala Batas, Penang, Malaysia.
| | - Marimuthu Citartan
- Advanced Medical & Dental Institute (AMDI), Universiti Sains Malaysia, Bertam, 13200, Kepala Batas, Penang, Malaysia.
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43
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Zhao C, Zhang D, Jiang Y, Chen SJ. Modeling Loop Composition and Ion Concentration Effects in RNA Hairpin Folding Stability. Biophys J 2020; 119:1439-1455. [PMID: 32949490 PMCID: PMC7568001 DOI: 10.1016/j.bpj.2020.07.042] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 06/12/2020] [Accepted: 07/08/2020] [Indexed: 12/21/2022] Open
Abstract
The ability to accurately predict RNA hairpin structure and stability for different loop sequences and salt conditions is important for understanding, modeling, and designing larger RNA folds. However, traditional RNA secondary structure models cannot treat loop-sequence and ionic effects on RNA hairpin folding. Here, we describe a general, three-dimensional (3D) conformation-based computational method for modeling salt concentration-dependent conformational distributions and the detailed 3D structures for a set of three RNA hairpins that contain a variable, 15-nucleotide loop sequence. For a given RNA sequence, the new, to our knowledge, method integrates a Vfold2D two-dimensional structure folding model with IsRNA coarse-grained molecular dynamics 3D folding simulations and Monte Carlo tightly bound ion estimations of ion-mediated electrostatic interactions. The model predicts free-energy landscapes for the different RNA hairpin-forming sequences with variable salt conditions. The theoretically predicted results agree with the experimental fluorescence measurements, validating the strategy. Furthermore, the theoretical model goes beyond the experimental results by enabling in-depth 3D structural analysis, revealing energetic mechanisms for the sequence- and salt-dependent folding stability. Although the computational framework presented here is developed for RNA hairpin systems, the general method may be applied to investigate other RNA systems, such as multiway junctions or pseudoknots in mixed metal ion solutions.
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Affiliation(s)
- Chenhan Zhao
- Department of Physics, Department of Biochemistry, and Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri
| | - Dong Zhang
- Department of Physics, Department of Biochemistry, and Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri
| | - Yangwei Jiang
- Department of Physics, Department of Biochemistry, and Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri
| | - Shi-Jie Chen
- Department of Physics, Department of Biochemistry, and Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri.
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44
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Xu B, Meng Y, Jin Y. RNA structures in alternative splicing and back-splicing. WILEY INTERDISCIPLINARY REVIEWS-RNA 2020; 12:e1626. [PMID: 32929887 DOI: 10.1002/wrna.1626] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 08/14/2020] [Accepted: 08/22/2020] [Indexed: 12/12/2022]
Abstract
Alternative splicing greatly expands the transcriptomic and proteomic diversities related to physiological and developmental processes in higher eukaryotes. Splicing of long noncoding RNAs, and back- and trans- splicing further expanded the regulatory repertoire of alternative splicing. RNA structures were shown to play an important role in regulating alternative splicing and back-splicing. Application of novel sequencing technologies made it possible to identify genome-wide RNA structures and interaction networks, which might provide new insights into RNA splicing regulation in vitro to in vivo. The emerging transcription-folding-splicing paradigm is changing our understanding of RNA alternative splicing regulation. Here, we review the insights into the roles and mechanisms of RNA structures in alternative splicing and back-splicing, as well as how disruption of these structures affects alternative splicing and then leads to human diseases. This article is categorized under: RNA Processing > Splicing Regulation/Alternative Splicing RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems.
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Affiliation(s)
- Bingbing Xu
- MOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Zhejiang, Hangzhou, China
| | - Yijun Meng
- College of Life and Environmental Sciences, Hangzhou Normal University, Zhejiang, Hangzhou, China
| | - Yongfeng Jin
- MOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Zhejiang, Hangzhou, China
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45
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Xu X, Chen SJ. Topological constraints of RNA pseudoknotted and loop-kissing motifs: applications to three-dimensional structure prediction. Nucleic Acids Res 2020; 48:6503-6512. [PMID: 32491164 PMCID: PMC7337929 DOI: 10.1093/nar/gkaa463] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2020] [Accepted: 05/19/2020] [Indexed: 01/23/2023] Open
Abstract
An RNA global fold can be described at the level of helix orientations and relatively flexible loop conformations that connect the helices. The linkage between the helices plays an essential role in determining the structural topology, which restricts RNA local and global folds, especially for RNA tertiary structures involving cross-linked base pairs. We quantitatively analyze the topological constraints on RNA 3D conformational space, in particular, on the distribution of helix orientations, for pseudoknots and loop-loop kissing structures. The result shows that a viable conformational space is predominantly determined by the motif type, helix size, and loop size, indicating a strong topological coupling between helices and loops in RNA tertiary motifs. Moreover, the analysis indicates that (cross-linked) tertiary contacts can cause much stronger topological constraints on RNA global fold than non-cross-linked base pairs. Furthermore, based on the topological constraints encoded in the 2D structure and the 3D templates, we develop a 3D structure prediction approach. This approach can be further combined with structure probing methods to expand the capability of computational prediction for large RNA folds.
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Affiliation(s)
- Xiaojun Xu
- Institute of Bioinformatics and Medical Engineering, Jiangsu University of Technology, Changzhou, Jiangsu 213001, China
| | - Shi-Jie Chen
- Department of Physics, Department of Biochemistry, and Informatics Institute, University of Missouri, Columbia, MO 65211, USA
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46
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Oliver C, Mallet V, Gendron RS, Reinharz V, Hamilton W, Moitessier N, Waldispühl J. Augmented base pairing networks encode RNA-small molecule binding preferences. Nucleic Acids Res 2020; 48:7690-7699. [PMID: 32652015 PMCID: PMC7430648 DOI: 10.1093/nar/gkaa583] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 06/23/2020] [Accepted: 07/08/2020] [Indexed: 12/14/2022] Open
Abstract
RNA-small molecule binding is a key regulatory mechanism which can stabilize 3D structures and activate molecular functions. The discovery of RNA-targeting compounds is thus a current topic of interest for novel therapies. Our work is a first attempt at bringing the scalability and generalization abilities of machine learning methods to the problem of RNA drug discovery, as well as a step towards understanding the interactions which drive binding specificity. Our tool, RNAmigos, builds and encodes a network representation of RNA structures to predict likely ligands for novel binding sites. We subject ligand predictions to virtual screening and show that we are able to place the true ligand in the 71st-73rd percentile in two decoy libraries, showing a significant improvement over several baselines, and a state of the art method. Furthermore, we observe that augmenting structural networks with non-canonical base pairing data is the only representation able to uncover a significant signal, suggesting that such interactions are a necessary source of binding specificity. We also find that pre-training with an auxiliary graph representation learning task significantly boosts performance of ligand prediction. This finding can serve as a general principle for RNA structure-function prediction when data is scarce. RNAmigos shows that RNA binding data contains structural patterns with potential for drug discovery, and provides methodological insights for possible applications to other structure-function learning tasks. The source code, data and a Web server are freely available at http://rnamigos.cs.mcgill.ca.
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Affiliation(s)
- Carlos Oliver
- School of Computer Science, McGill University, Montreal H3A 0E9, Canada
- Mila - Quebec Artificial Intelligence Institute, H2S 3S1, Canada
| | - Vincent Mallet
- Institut Pasteur, Structural Bioinformatics Unit, Paris, F-75015, France
- MINES ParisTech, PSL Research University, CBIO - Centre for Computational Biology, F-75006 Paris, France
| | | | - Vladimir Reinharz
- Department of Computer Science, Université du Québec à Montréal, Montreal H2X 3Y7, Canada
| | - William L Hamilton
- School of Computer Science, McGill University, Montreal H3A 0E9, Canada
- Mila - Quebec Artificial Intelligence Institute, H2S 3S1, Canada
| | | | - Jérôme Waldispühl
- School of Computer Science, McGill University, Montreal H3A 0E9, Canada
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47
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Badu S, Melnik R, Singh S. Mathematical and computational models of RNA nanoclusters and their applications in data-driven environments. MOLECULAR SIMULATION 2020. [DOI: 10.1080/08927022.2020.1804564] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Shyam Badu
- MS2Discovery Interdisciplinary Research Institute, Wilfrid Laurier University, Waterloo, Ontario, Canada
| | - Roderick Melnik
- MS2Discovery Interdisciplinary Research Institute, Wilfrid Laurier University, Waterloo, Ontario, Canada
- BCAM-Basque Center for Applied Mathematics, Bilbao, Spain
| | - Sundeep Singh
- MS2Discovery Interdisciplinary Research Institute, Wilfrid Laurier University, Waterloo, Ontario, Canada
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48
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Perret G, Boschetti E. Aptamer-Based Affinity Chromatography for Protein Extraction and Purification. ADVANCES IN BIOCHEMICAL ENGINEERING/BIOTECHNOLOGY 2020; 174:93-139. [PMID: 31485702 DOI: 10.1007/10_2019_106] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Aptamers are oligonucleotide molecules able to recognize very specifically proteins. Among the possible applications, aptamers have been used for affinity chromatography with effective results and advantages over most advanced protein separation technologies. This chapter first discusses the context of the affinity chromatography with aptamer ligands. With the adaptation of SELEX, the chemical modifications of aptamers to comply with the covalent coupling and the separation process are then extensively presented. A focus is then made about the most important applications for protein separation with real-life examples and the comparison with immunoaffinity chromatography. In spite of well-advanced demonstrations and the extraordinary potential developments, a significant optimization work is still due to deserve large-scale applications with all necessary validations. Graphical Abstract Aptamer-protein complexes by X-ray crystallography.
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49
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Oshiquiri LH, Gomes SL, Georg RC. Blastocladiella emersonii spliceosome is regulated in response to the splicing inhibition caused by the metals cadmium, cobalt and manganese. Fungal Biol 2020; 124:468-474. [PMID: 32389309 DOI: 10.1016/j.funbio.2020.03.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Revised: 03/20/2020] [Accepted: 03/23/2020] [Indexed: 01/08/2023]
Abstract
Blastocladiella emersonii is an aquatic fungus of the phylum Blastocladiomycota, localized near the base of the fungal tree. Previous studies have shown that B. emersonii responds to heat shock and cadmium exposure inducing the transcription of a high number of genes. EST sequencing from heat shocked and cadmium exposed B. emersonii cells has shown that exposure to cadmium causes strong splicing inhibition. Despite the knowledge about splicing inhibition by cadmium, it is still unclear if other metal contaminants can cause the same response. In the present study, we have demonstrated that the effect of cadmium exposure on splicing inhibition is much stronger than that of other divalent metals such as cobalt and manganese. Data presented here also indicate that intron retention occurs randomly among the fungal transcripts, as verified by analyzing differently affected transcripts. In addition, we identified in the genome of B. emersonii the genes encoding the snRNA splicing components U1, U2, U4, U5 and U6 and observed that spliceosome snRNAs are upregulated in the presence of metals, in particular snRNA U1 in cells under cadmium exposure. This observation suggests that snRNA upregulation might be a defense of the fungal cell against the metal stress condition.
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Affiliation(s)
- Letícia Harumi Oshiquiri
- Departamento de Bioquímica e Biologia Molecular, Instituto de Ciências Biológicas, Universidade Federal de Goiás, Goiânia, GO, Brazil
| | - Suely Lopes Gomes
- Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, SP, Brazil
| | - Raphaela Castro Georg
- Departamento de Bioquímica e Biologia Molecular, Instituto de Ciências Biológicas, Universidade Federal de Goiás, Goiânia, GO, Brazil; Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, SP, Brazil.
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50
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Nguyen HT, Thirumalai D. Charge Density of Cation Determines Inner versus Outer Shell Coordination to Phosphate in RNA. J Phys Chem B 2020; 124:4114-4122. [PMID: 32342689 DOI: 10.1021/acs.jpcb.0c02371] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Divalent cations are often required to fold RNA, which is a highly charged polyanion. Condensation of ions, such as Mg2+ or Ca2+, in the vicinity of RNA renormalizes the effective charges on the phosphate groups, thus minimizing the intra RNA electrostatic repulsion. The prevailing view is that divalent ions bind diffusively in a nonspecific manner. In sharp contrast, we arrive at the exact opposite conclusion using a theory for the interaction of ions with the phosphate groups using RISM theory in conjunction with simulations based on an accurate three-interaction-site RNA model. The divalent ions bind in a nucleotide-specific manner using either the inner (partially dehydrated) or outer (fully hydrated) shell coordination. The high charge density Mg2+ ion has a preference to bind to the outer shell, whereas the opposite is the case for Ca2+. Surprisingly, we find that bridging interactions, involving ions that are coordinated to two or more phosphate groups, play a crucial role in maintaining the integrity of the folded state. Their importance could become increasingly prominent as the size of the RNA increases. Because the modes of interaction of divalent ions with DNA are likely to be similar, we propose that specific inner and outer shell coordination could play a role in DNA condensation, and perhaps genome organization as well.
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Affiliation(s)
- Hung T Nguyen
- Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, United States
| | - D Thirumalai
- Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, United States
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