1
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Yuan R, Zhang Z, Wu G, Zhang Y, Sha J, Chen Y, Si W. Unfolding of protein using MoS 2/SnS 2heterostructure for nanopore-based sequencing. NANOTECHNOLOGY 2024; 35:135501. [PMID: 38118165 DOI: 10.1088/1361-6528/ad177f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 12/20/2023] [Indexed: 12/22/2023]
Abstract
Protein sequencing is crucial for understanding the complex mechanisms driving biological functions. However, proteins are usually folded in their native state and the mechanism of fast protein conformation transitions still remains unclear, which make protein sequencing challenging. Molecular dynamics simulations with accurate force field are now able to observe the entire folding/unfolding process, providing valuable insights into protein folding mechanisms. Given that proteins can be unfolded, nanopore technology shows great potential for protein sequencing. In this study, we proposed to use MoS2/SnS2heterostructures to firstly unfold proteins and then detect them by a nanopore in the heterostructural membrane. All-atom molecular dynamics simulations performed in this work provided rich atomic-level information for a comprehensive understanding of protein unfolding process and mechanism on the MoS2/SnS2heterostructure, it was found that the strong binding of protein to SnS2nanostripe and hydrogen bond breaking were the main reasons for unfolding the protein on the heterostructure. After the protein was fully unfolded, it was restrained on the nanostripe because of the affinity of protein to the SnS2nanostripe. Thus by integrating the proposed unfolding technique with nanopore technology, detection of linear unfolded peptide was realized in this work, allowing for the identification of protein components, which is essential for sequencing proteins in the near future.
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Affiliation(s)
- Runyi Yuan
- Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, School of Mechanical Engineering, Southeast University, Nanjing 211100, People's Republic of China
| | - Zhen Zhang
- Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, School of Mechanical Engineering, Southeast University, Nanjing 211100, People's Republic of China
| | - Gensheng Wu
- School of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, People's Republic of China
| | - Yin Zhang
- Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, School of Mechanical Engineering, Southeast University, Nanjing 211100, People's Republic of China
| | - Jingjie Sha
- Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, School of Mechanical Engineering, Southeast University, Nanjing 211100, People's Republic of China
| | - Yunfei Chen
- Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, School of Mechanical Engineering, Southeast University, Nanjing 211100, People's Republic of China
| | - Wei Si
- Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, School of Mechanical Engineering, Southeast University, Nanjing 211100, People's Republic of China
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2
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Abstract
The potential of miniproteins in the biological and chemical sciences is constantly increasing. Significant progress in the design methodologies has been achieved over the last 30 years. Early approaches based on propensities of individual amino acid residues to form individual secondary structures were subsequently improved by structural analyses using NMR spectroscopy and crystallography. Consequently, computational algorithms were developed, which are now highly successful in designing structures with accuracy often close to atomic range. Further perspectives include construction of miniproteins incorporating non-native secondary structures derived from sequences with units other than α-amino acids. Noteworthy, miniproteins with extended structures, which are now feasibly accessible, are excellent scaffolds for construction of functional molecules.
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3
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Ferguson AL, Ranganathan R. 100th Anniversary of Macromolecular Science Viewpoint: Data-Driven Protein Design. ACS Macro Lett 2021; 10:327-340. [PMID: 35549066 DOI: 10.1021/acsmacrolett.0c00885] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The design of synthetic proteins with the desired function is a long-standing goal in biomolecular science, with broad applications in biochemical engineering, agriculture, medicine, and public health. Rational de novo design and experimental directed evolution have achieved remarkable successes but are challenged by the requirement to find functional "needles" in the vast "haystack" of protein sequence space. Data-driven models for fitness landscapes provide a predictive map between protein sequence and function and can prospectively identify functional candidates for experimental testing to greatly improve the efficiency of this search. This Viewpoint reviews the applications of machine learning and, in particular, deep learning as part of data-driven protein engineering platforms. We highlight recent successes, review promising computational methodologies, and provide an outlook on future challenges and opportunities. The article is written for a broad audience comprising both polymer and protein scientists and computer and data scientists interested in an up-to-date review of recent innovations and opportunities in this rapidly evolving field.
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Affiliation(s)
- Andrew L. Ferguson
- Pritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois 60637, United States
| | - Rama Ranganathan
- Pritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois 60637, United States
- Center for Physics of Evolving Systems, University of Chicago, Chicago, Illinois 60637, United States
- Biochemistry and Molecular Biology, University of Chicago, Chicago, Illinois 60637, United States
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4
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Abbass J, Nebel JC. Enhancing fragment-based protein structure prediction by customising fragment cardinality according to local secondary structure. BMC Bioinformatics 2020; 21:170. [PMID: 32357827 PMCID: PMC7195757 DOI: 10.1186/s12859-020-3491-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 04/13/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Whenever suitable template structures are not available, usage of fragment-based protein structure prediction becomes the only practical alternative as pure ab initio techniques require massive computational resources even for very small proteins. However, inaccuracy of their energy functions and their stochastic nature imposes generation of a large number of decoys to explore adequately the solution space, limiting their usage to small proteins. Taking advantage of the uneven complexity of the sequence-structure relationship of short fragments, we adjusted the fragment insertion process by customising the number of available fragment templates according to the expected complexity of the predicted local secondary structure. Whereas the number of fragments is kept to its default value for coil regions, important and dramatic reductions are proposed for beta sheet and alpha helical regions, respectively. RESULTS The evaluation of our fragment selection approach was conducted using an enhanced version of the popular Rosetta fragment-based protein structure prediction tool. It was modified so that the number of fragment candidates used in Rosetta could be adjusted based on the local secondary structure. Compared to Rosetta's standard predictions, our strategy delivered improved first models, + 24% and + 6% in terms of GDT, when using 2000 and 20,000 decoys, respectively, while reducing significantly the number of fragment candidates. Furthermore, our enhanced version of Rosetta is able to deliver with 2000 decoys a performance equivalent to that produced by standard Rosetta while using 20,000 decoys. We hypothesise that, as the fragment insertion process focuses on the most challenging regions, such as coils, fewer decoys are needed to explore satisfactorily conformation spaces. CONCLUSIONS Taking advantage of the high accuracy of sequence-based secondary structure predictions, we showed the value of that information to customise the number of candidates used during the fragment insertion process of fragment-based protein structure prediction. Experimentations conducted using standard Rosetta showed that, when using the recommended number of decoys, i.e. 20,000, our strategy produces better results. Alternatively, similar results can be achieved using only 2000 decoys. Consequently, we recommend the adoption of this strategy to either improve significantly model quality or reduce processing times by a factor 10.
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Affiliation(s)
- Jad Abbass
- Faculty of Science, Engineering and Computing, Kingston University, London, KT1 2EE UK
- Department of Computer Science, Lebanese International University, Bekaa, Lebanon
| | - Jean-Christophe Nebel
- Faculty of Science, Engineering and Computing, Kingston University, London, KT1 2EE UK
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5
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Dawid AE, Gront D, Kolinski A. Coarse-Grained Modeling of the Interplay between Secondary Structure Propensities and Protein Fold Assembly. J Chem Theory Comput 2018; 14:2277-2287. [PMID: 29486120 DOI: 10.1021/acs.jctc.7b01242] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
We recently developed a new coarse-grained model of protein structure and dynamics [ Dawid et al. J. Chem. Theory Comput. 2017 , 13 ( 11 ), 5766 - 5779 ]. The model assumed a single bead representation of amino acid residues, where positions of such united residues were defined by centers of mass of four amino acid fragments. Replica exchange Monte Carlo sampling of the model chains provided good pictures of modeled structures and their dynamics. In its generic form the statistical knowledge-based force field of the model has been dedicated for single-domain globular proteins. Sequence-specific interactions are defined by three-letter secondary structure data. In the present work we demonstrate that different assignments and/or predictions of secondary structures are usually sufficient for enforcing cooperative formation of native-like folds of SURPASS chains for the majority of single-domain globular proteins. Simulations of native-like structure assembly for a representative set of globular proteins have shown that the accuracy of secondary structure data is usually not crucial for model performance, although some specific errors can strongly distort the obtained three-dimensional structures.
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Affiliation(s)
- Aleksandra E Dawid
- Faculty of Chemistry, Biological and Chemical Research Center , University of Warsaw , Pasteura 1 , 02-093 Warsaw , Poland
| | - Dominik Gront
- Faculty of Chemistry, Biological and Chemical Research Center , University of Warsaw , Pasteura 1 , 02-093 Warsaw , Poland
| | - Andrzej Kolinski
- Faculty of Chemistry, Biological and Chemical Research Center , University of Warsaw , Pasteura 1 , 02-093 Warsaw , Poland
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6
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dos Santos RN, Ferrari AJR, de Jesus HCR, Gozzo FC, Morcos F, Martínez L. Enhancing protein fold determination by exploring the complementary information of chemical cross-linking and coevolutionary signals. Bioinformatics 2018; 34:2201-2208. [DOI: 10.1093/bioinformatics/bty074] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2017] [Accepted: 02/10/2018] [Indexed: 11/13/2022] Open
Affiliation(s)
- Ricardo N dos Santos
- Institute of Chemistry, University of Campinas, Campinas, Brazil
- Center for Computational Engineering and Sciences, University of Campinas, Campinas, Brazil
| | | | | | - Fábio C Gozzo
- Institute of Chemistry, University of Campinas, Campinas, Brazil
| | - Faruck Morcos
- Department of Biological Sciences, University of Texas at Dallas, Richardson, USA
| | - Leandro Martínez
- Institute of Chemistry, University of Campinas, Campinas, Brazil
- Center for Computational Engineering and Sciences, University of Campinas, Campinas, Brazil
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7
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Arai R. Hierarchical design of artificial proteins and complexes toward synthetic structural biology. Biophys Rev 2017; 10:391-410. [PMID: 29243094 DOI: 10.1007/s12551-017-0376-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2017] [Accepted: 11/23/2017] [Indexed: 12/14/2022] Open
Abstract
In multiscale structural biology, synthetic approaches are important to demonstrate biophysical principles and mechanisms underlying the structure, function, and action of bio-nanomachines. A central goal of "synthetic structural biology" is the design and construction of artificial proteins and protein complexes as desired. In this paper, I review recent remarkable progress of an array of approaches for hierarchical design of artificial proteins and complexes that signpost the path forward toward synthetic structural biology as an emerging interdisciplinary field. Topics covered include combinatorial and protein-engineering approaches for directed evolution of artificial binding proteins and membrane proteins, binary code strategy for structural and functional de novo proteins, protein nanobuilding block strategy for constructing nano-architectures, protein-metal-organic frameworks for 3D protein complex crystals, and rational and computational approaches for design/creation of artificial proteins and complexes, novel protein folds, ideal/optimized protein structures, novel binding proteins for targeted therapeutics, and self-assembling nanomaterials. Protein designers and engineers look toward a bright future in synthetic structural biology for the next generation of biophysics and biotechnology.
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Affiliation(s)
- Ryoichi Arai
- Department of Applied Biology, Faculty of Textile Science and Technology, Shinshu University, Ueda, Nagano 386-8567, Japan. .,Department of Supramolecular Complexes, Research Center for Fungal and Microbial Dynamism, Shinshu University, Minamiminowa, Nagano 399-4598, Japan. .,Institute for Biomedical Sciences, Interdisciplinary Cluster for Cutting Edge Research, Shinshu University, Matsumoto, Nagano 390-8621, Japan. .,Division of Structural and Synthetic Biology, RIKEN Center for Life Science Technologies, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.
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8
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Mazurenko S, Kunka A, Beerens K, Johnson CM, Damborsky J, Prokop Z. Exploration of Protein Unfolding by Modelling Calorimetry Data from Reheating. Sci Rep 2017; 7:16321. [PMID: 29176711 PMCID: PMC5701188 DOI: 10.1038/s41598-017-16360-y] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2017] [Accepted: 11/10/2017] [Indexed: 01/14/2023] Open
Abstract
Studies of protein unfolding mechanisms are critical for understanding protein functions inside cells, de novo protein design as well as defining the role of protein misfolding in neurodegenerative disorders. Calorimetry has proven indispensable in this regard for recording full energetic profiles of protein unfolding and permitting data fitting based on unfolding pathway models. While both kinetic and thermodynamic protein stability are analysed by varying scan rates and reheating, the latter is rarely used in curve-fitting, leading to a significant loss of information from experiments. To extract this information, we propose fitting both first and second scans simultaneously. Four most common single-peak transition models are considered: (i) fully reversible, (ii) fully irreversible, (iii) partially reversible transitions, and (iv) general three-state models. The method is validated using calorimetry data for chicken egg lysozyme, mutated Protein A, three wild-types of haloalkane dehalogenases, and a mutant stabilized by protein engineering. We show that modelling of reheating increases the precision of determination of unfolding mechanisms, free energies, temperatures, and heat capacity differences. Moreover, this modelling indicates whether alternative refolding pathways might occur upon cooling. The Matlab-based data fitting software tool and its user guide are provided as a supplement.
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Affiliation(s)
- Stanislav Mazurenko
- Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00, Brno, Czech Republic
| | - Antonin Kunka
- Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00, Brno, Czech Republic
- International Clinical Research Center, St. Anne's University Hospital, Pekarska 53, 656 91, Brno, Czech Republic
| | - Koen Beerens
- Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00, Brno, Czech Republic
| | - Christopher M Johnson
- Biophysics Facilities, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge Biomedical Campus, Cambridge, CB2 0QH, UK
| | - Jiri Damborsky
- Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00, Brno, Czech Republic.
- International Clinical Research Center, St. Anne's University Hospital, Pekarska 53, 656 91, Brno, Czech Republic.
| | - Zbynek Prokop
- Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment RECETOX, Faculty of Science, Masaryk University, Kamenice 5/A13, 625 00, Brno, Czech Republic.
- International Clinical Research Center, St. Anne's University Hospital, Pekarska 53, 656 91, Brno, Czech Republic.
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9
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van IJzendoorn DGP, Forghany Z, Liebelt F, Vertegaal AC, Jochemsen AG, Bovée JVMG, Szuhai K, Baker DA. Functional analyses of a human vascular tumor FOS variant identify a novel degradation mechanism and a link to tumorigenesis. J Biol Chem 2017; 292:21282-21290. [PMID: 29150442 DOI: 10.1074/jbc.c117.815845] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2017] [Revised: 11/03/2017] [Indexed: 11/06/2022] Open
Abstract
Epithelioid hemangioma is a locally aggressive vascular neoplasm, found in bones and soft tissue, whose cause is currently unknown, but may involve oncogene activation. FOS is one of the earliest viral oncogenes to be characterized, and normal cellular FOS forms part of the activator protein 1 (AP-1) transcription factor complex, which plays a pivotal role in cell growth, differentiation, and survival as well as the DNA damage response. Despite this, a causal link between aberrant FOS function and naturally occurring tumors has not yet been established. Here, we describe a thorough molecular and biochemical analysis of a mutant FOS protein we identified in these vascular tumors. The mutant protein lacks a highly conserved helix consisting of the C-terminal four amino acids of FOS, which we show is indispensable for fast, ubiquitin-independent FOS degradation via the 20S proteasome. Our work reveals that FOS stimulates endothelial sprouting and that perturbation of normal FOS degradation could account for the abnormal vessel growth typical of epithelioid hemangioma. To the best of our knowledge, this is the first functional characterization of mutant FOS proteins found in tumors.
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Affiliation(s)
| | - Zary Forghany
- Molecular Cell Biology, Leiden University Medical Center (LUMC), 2300 RC Leiden, The Netherlands
| | - Frauke Liebelt
- Molecular Cell Biology, Leiden University Medical Center (LUMC), 2300 RC Leiden, The Netherlands
| | - Alfred C Vertegaal
- Molecular Cell Biology, Leiden University Medical Center (LUMC), 2300 RC Leiden, The Netherlands
| | - Aart G Jochemsen
- Molecular Cell Biology, Leiden University Medical Center (LUMC), 2300 RC Leiden, The Netherlands
| | | | - Karoly Szuhai
- Molecular Cell Biology, Leiden University Medical Center (LUMC), 2300 RC Leiden, The Netherlands
| | - David A Baker
- Molecular Cell Biology, Leiden University Medical Center (LUMC), 2300 RC Leiden, The Netherlands
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10
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Abstract
Computational modeling of proteins using evolutionary or de novo approaches offers rapid structural characterization, but often suffers from low success rates in generating high quality models comparable to the accuracy of structures observed in X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy. A computational/experimental hybrid approach incorporating sparse experimental restraints in computational modeling algorithms drastically improves reliability and accuracy of 3D models. This chapter discusses the use of structural information obtained from various paramagnetic NMR measurements and demonstrates computational algorithms implementing pseudocontact shifts as restraints to determine the structure of proteins at atomic resolution.
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11
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Geng X, Zhou J, Guan J. Side-chain dynamics analysis of KE07 series. Comput Biol Chem 2016; 65:148-153. [PMID: 27825588 DOI: 10.1016/j.compbiolchem.2016.09.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2016] [Accepted: 09/07/2016] [Indexed: 11/25/2022]
Abstract
The significant improvement of KE07 series in catalytic activities shows the great success of computational design approaches combined with directed evolution in protein design. Understanding the protein dynamics in the evolutionary optimization process of computationally designed enzyme will provide profound implication to study enzyme function and guide protein design. Here, side chain squared generalized order parameters and entropy of each protein are calculated using 50ns molecular dynamics simulation data in both apo and bound states. Our results show a correlation between the increase of side chain motion amplitude and catalytic efficiency. By analyzing the relationship between these two values, we find side chain squared generalized order parameter is linearly related to side chain entropy, which indicates the computationally designed KE07 series have similar dynamics property with natural enzymes.
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Affiliation(s)
- Xin Geng
- Department of Computer Science and Technology, Tongji University, Shanghai 201804, China.
| | - Jiaogen Zhou
- The Institute of Subtropical Agriculture, China Academy of Sciences, Changsha 410125, China.
| | - Jihong Guan
- Department of Computer Science and Technology, Tongji University, Shanghai 201804, China.
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12
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Zhu C, Zhang C, Zhang T, Zhang X, Shen Q, Tang B, Liang H, Lai L. Rational design of TNFα binding proteins based on the de novo designed protein DS119. Protein Sci 2016; 25:2066-2075. [PMID: 27571536 DOI: 10.1002/pro.3029] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2016] [Accepted: 08/26/2016] [Indexed: 12/11/2022]
Abstract
De novo protein design offers templates for engineering tailor-made protein functions and orthogonal protein interaction networks for synthetic biology research. Various computational methods have been developed to introduce functional sites in known protein structures. De novo designed protein scaffolds provide further opportunities for functional protein design. Here we demonstrate the rational design of novel tumor necrosis factor alpha (TNFα) binding proteins using a home-made grafting program AutoMatch. We grafted three key residues from a virus 2L protein to a de novo designed small protein, DS119, with consideration of backbone flexibility. The designed proteins bind to TNFα with micromolar affinities. We further optimized the interface residues with RosettaDesign and significantly improved the binding capacity of one protein Tbab1-4. These designed proteins inhibit the activity of TNFα in cellular luciferase assays. Our work illustrates the potential application of the de novo designed protein DS119 in protein engineering, biomedical research, and protein sequence-structure-function studies.
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Affiliation(s)
- Cheng Zhu
- BNLMS, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
| | - Changsheng Zhang
- BNLMS, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
| | - Tao Zhang
- BNLMS, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
| | - Xiaoling Zhang
- Center for Quantitative Biology, Peking University, Beijing, 100871, China
| | - Qi Shen
- Center for Quantitative Biology, Peking University, Beijing, 100871, China
| | - Bo Tang
- Center for Quantitative Biology, Peking University, Beijing, 100871, China
| | - Huanhuan Liang
- National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Luhua Lai
- BNLMS, State Key Laboratory for Structural Chemistry of Unstable and Stable Species, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China. .,Center for Quantitative Biology, Peking University, Beijing, 100871, China. .,Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China.
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13
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Design of Self-Assembling Protein-Polymer Conjugates. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2016; 940:179-214. [PMID: 27677514 DOI: 10.1007/978-3-319-39196-0_9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Protein-polymer conjugates are of particular interest for nanobiotechnology applications because of the various and complementary roles that each component may play in composite hybrid-materials. This chapter focuses on the design principles and applications of self-assembling protein-polymer conjugate materials. We address the general design methodology, from both synthetic and genetic perspective, conjugation strategies, protein vs. polymer driven self-assembly and finally, emerging applications for conjugate materials. By marrying proteins and polymers into conjugated bio-hybrid materials, materials scientists, chemists, and biologists alike, have at their fingertips a vast toolkit for material design. These inherently hierarchical structures give rise to useful patterning, mechanical and transport properties that may help realize new, more efficient materials for energy generation, catalysis, nanorobots, etc.
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14
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Pottel J, Moitessier N. Single-Point Mutation with a Rotamer Library Toolkit: Toward Protein Engineering. J Chem Inf Model 2015; 55:2657-71. [PMID: 26623941 DOI: 10.1021/acs.jcim.5b00525] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Protein engineers have long been hard at work to harness biocatalysts as a natural source of regio-, stereo-, and chemoselectivity in order to carry out chemistry (reactions and/or substrates) not previously achieved with these enzymes. The extreme labor demands and exponential number of mutation combinations have induced computational advances in this domain. The first step in our virtual approach is to predict the correct conformations upon mutation of residues (i.e., rebuilding side chains). For this purpose, we opted for a combination of molecular mechanics and statistical data. In this work, we have developed automated computational tools to extract protein structural information and created conformational libraries for each amino acid dependent on a variable number of parameters (e.g., resolution, flexibility, secondary structure). We have also developed the necessary tool to apply the mutation and optimize the conformation accordingly. For side-chain conformation prediction, we obtained overall average root-mean-square deviations (RMSDs) of 0.91 and 1.01 Å for the 18 flexible natural amino acids within two distinct sets of over 3000 and 1500 side-chain residues, respectively. The commonly used dihedral angle differences were also evaluated and performed worse than the state of the art. These two metrics are also compared. Furthermore, we generated a family-specific library for kinases that produced an average 2% lower RMSD upon side-chain reconstruction and a residue-specific library that yielded a 17% improvement. Ultimately, since our protein engineering outlook involves using our docking software, Fitted/Impacts, we applied our mutation protocol to a benchmarked data set for self- and cross-docking. Our side-chain reconstruction does not hinder our docking software, demonstrating differences in pose prediction accuracy of approximately 2% (RMSD cutoff metric) for a set of over 200 protein/ligand structures. Similarly, when docking to a set of over 100 kinases, side-chain reconstruction (using both general and biased conformation libraries) had minimal detriment to the docking accuracy.
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Affiliation(s)
- Joshua Pottel
- Department of Chemistry, McGill University , 801 Sherbrooke Street West, Montreal, QC, Canada H3A 0B8
| | - Nicolas Moitessier
- Department of Chemistry, McGill University , 801 Sherbrooke Street West, Montreal, QC, Canada H3A 0B8
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15
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Improving Protein Fold Recognition by Deep Learning Networks. Sci Rep 2015; 5:17573. [PMID: 26634993 PMCID: PMC4669437 DOI: 10.1038/srep17573] [Citation(s) in RCA: 90] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2015] [Accepted: 11/02/2015] [Indexed: 12/31/2022] Open
Abstract
For accurate recognition of protein folds, a deep learning network method (DN-Fold) was developed to predict if a given query-template protein pair belongs to the same structural fold. The input used stemmed from the protein sequence and structural features extracted from the protein pair. We evaluated the performance of DN-Fold along with 18 different methods on Lindahl’s benchmark dataset and on a large benchmark set extracted from SCOP 1.75 consisting of about one million protein pairs, at three different levels of fold recognition (i.e., protein family, superfamily, and fold) depending on the evolutionary distance between protein sequences. The correct recognition rate of ensembled DN-Fold for Top 1 predictions is 84.5%, 61.5%, and 33.6% and for Top 5 is 91.2%, 76.5%, and 60.7% at family, superfamily, and fold levels, respectively. We also evaluated the performance of single DN-Fold (DN-FoldS), which showed the comparable results at the level of family and superfamily, compared to ensemble DN-Fold. Finally, we extended the binary classification problem of fold recognition to real-value regression task, which also show a promising performance. DN-Fold is freely available through a web server at http://iris.rnet.missouri.edu/dnfold.
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16
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Verheggen K, Maddelein D, Hulstaert N, Martens L, Barsnes H, Vaudel M. Pladipus Enables Universal Distributed Computing in Proteomics Bioinformatics. J Proteome Res 2015; 15:707-12. [DOI: 10.1021/acs.jproteome.5b00850] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Kenneth Verheggen
- Medical
Biotechnology Center, VIB, Albert Baertsoenkaai 3, Ghent B-9000, Belgium
- Department
of Biochemistry, Ghent University, Albert Baertsoenkaai 3, Ghent B-9000, Belgium
- Bioinformatics
Institute Ghent, Ghent University, Albert Baertsoenkaai 3, Ghent B-9000, Belgium
| | - Davy Maddelein
- Medical
Biotechnology Center, VIB, Albert Baertsoenkaai 3, Ghent B-9000, Belgium
- Department
of Biochemistry, Ghent University, Albert Baertsoenkaai 3, Ghent B-9000, Belgium
- Bioinformatics
Institute Ghent, Ghent University, Albert Baertsoenkaai 3, Ghent B-9000, Belgium
| | - Niels Hulstaert
- Medical
Biotechnology Center, VIB, Albert Baertsoenkaai 3, Ghent B-9000, Belgium
- Department
of Biochemistry, Ghent University, Albert Baertsoenkaai 3, Ghent B-9000, Belgium
- Bioinformatics
Institute Ghent, Ghent University, Albert Baertsoenkaai 3, Ghent B-9000, Belgium
| | - Lennart Martens
- Medical
Biotechnology Center, VIB, Albert Baertsoenkaai 3, Ghent B-9000, Belgium
- Department
of Biochemistry, Ghent University, Albert Baertsoenkaai 3, Ghent B-9000, Belgium
- Bioinformatics
Institute Ghent, Ghent University, Albert Baertsoenkaai 3, Ghent B-9000, Belgium
| | - Harald Barsnes
- Proteomics
Unit, Department of Biomedicine, University of Bergen, Postboks 7804, N-5020 Bergen, Norway
- KG
Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Postboks 7804, N-5020 Bergen, Norway
| | - Marc Vaudel
- Proteomics
Unit, Department of Biomedicine, University of Bergen, Postboks 7804, N-5020 Bergen, Norway
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17
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Nguyen VP, Alves DS, Scott HL, Davis FL, Barrera FN. A Novel Soluble Peptide with pH-Responsive Membrane Insertion. Biochemistry 2015; 54:6567-75. [DOI: 10.1021/acs.biochem.5b00856] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Vanessa P. Nguyen
- Department of Biochemistry
and Cellular and Molecular Biology, University of Tennessee, Knoxville, Tennessee 37996, United States
| | - Daiane S. Alves
- Department of Biochemistry
and Cellular and Molecular Biology, University of Tennessee, Knoxville, Tennessee 37996, United States
| | - Haden L. Scott
- Department of Biochemistry
and Cellular and Molecular Biology, University of Tennessee, Knoxville, Tennessee 37996, United States
| | - Forrest L. Davis
- Department of Biochemistry
and Cellular and Molecular Biology, University of Tennessee, Knoxville, Tennessee 37996, United States
| | - Francisco N. Barrera
- Department of Biochemistry
and Cellular and Molecular Biology, University of Tennessee, Knoxville, Tennessee 37996, United States
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18
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van Vliet LD, Colin PY, Hollfelder F. Bioinspired genotype-phenotype linkages: mimicking cellular compartmentalization for the engineering of functional proteins. Interface Focus 2015; 5:20150035. [PMID: 26464791 PMCID: PMC4590426 DOI: 10.1098/rsfs.2015.0035] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
The idea of compartmentalization of genotype and phenotype in cells is key for enabling Darwinian evolution. This contribution describes bioinspired systems that use in vitro compartments-water-in-oil droplets and gel-shell beads-for the directed evolution of functional proteins. Technologies based on these principles promise to provide easier access to protein-based therapeutics, reagents for processes involving enzyme catalysis, parts for synthetic biology and materials with biological components.
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Affiliation(s)
| | | | - Florian Hollfelder
- Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, UK
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19
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Kobayashi N, Yanase K, Sato T, Unzai S, Hecht MH, Arai R. Self-Assembling Nano-Architectures Created from a Protein Nano-Building Block Using an Intermolecularly Folded Dimeric de Novo Protein. J Am Chem Soc 2015; 137:11285-93. [PMID: 26120734 DOI: 10.1021/jacs.5b03593] [Citation(s) in RCA: 77] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The design of novel proteins that self-assemble into supramolecular complexes is an important step in the development of synthetic biology and nanotechnology. Recently, we described the three-dimensional structure of WA20, a de novo protein that forms an intermolecularly folded dimeric 4-helix bundle (PDB code 3VJF ). To harness the unusual intertwined structure of WA20 for the self-assembly of supramolecular nanostructures, we created a protein nanobuilding block (PN-Block), called WA20-foldon, by fusing the dimeric structure of WA20 to the trimeric foldon domain of fibritin from bacteriophage T4. The WA20-foldon fusion protein was expressed in the soluble fraction in Escherichia coli, purified, and shown to form several homooligomeric forms. The stable oligomeric forms were further purified and characterized by a range of biophysical techniques. Size exclusion chromatography, multiangle light scattering, analytical ultracentrifugation, and small-angle X-ray scattering (SAXS) analyses indicate that the small (S form), middle (M form), and large (L form) forms of the WA20-foldon oligomers exist as hexamer (6-mer), dodecamer (12-mer), and octadecamer (18-mer), respectively. These findings suggest that the oligomers in multiples of 6-mer are stably formed by fusing the interdigitated dimer of WA20 with the trimer of foldon domain. Pair-distance distribution functions obtained from the Fourier inversion of the SAXS data suggest that the S and M forms have barrel- and tetrahedron-like shapes, respectively. These results demonstrate that the de novo WA20-foldon is an effective building block for the creation of self-assembling artificial nanoarchitectures.
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Affiliation(s)
- Naoya Kobayashi
- Japan Society for the Promotion of Science , Chiyoda, Tokyo 102-8471, Japan
| | | | | | - Satoru Unzai
- Graduate School of Medical Life Science, Yokohama City University , Tsurumi, Yokohama, Kanagawa 230-0045, Japan
| | - Michael H Hecht
- Department of Chemistry, Princeton University , Princeton, New Jersey 08544, United States
| | - Ryoichi Arai
- Institute for Biomedical Sciences, Interdisciplinary Cluster for Cutting Edge Research, Shinshu University , Matsumoto, Nagano 390-8621, Japan
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20
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Zhang Z, Schindler CEM, Lange OF, Zacharias M. Application of Enhanced Sampling Monte Carlo Methods for High-Resolution Protein-Protein Docking in Rosetta. PLoS One 2015; 10:e0125941. [PMID: 26053419 PMCID: PMC4459952 DOI: 10.1371/journal.pone.0125941] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2015] [Accepted: 03/26/2015] [Indexed: 11/30/2022] Open
Abstract
The high-resolution refinement of docked protein-protein complexes can provide valuable structural and mechanistic insight into protein complex formation complementing experiment. Monte Carlo (MC) based approaches are frequently applied to sample putative interaction geometries of proteins including also possible conformational changes of the binding partners. In order to explore efficiency improvements of the MC sampling, several enhanced sampling techniques, including temperature or Hamiltonian replica exchange and well-tempered ensemble approaches, have been combined with the MC method and were evaluated on 20 protein complexes using unbound partner structures. The well-tempered ensemble method combined with a 2-dimensional temperature and Hamiltonian replica exchange scheme (WTE-H-REMC) was identified as the most efficient search strategy. Comparison with prolonged MC searches indicates that the WTE-H-REMC approach requires approximately 5 times fewer MC steps to identify near native docking geometries compared to conventional MC searches.
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Affiliation(s)
- Zhe Zhang
- Physik-Department T38, Technische Universität München, James-Franck-Str. 1, 84748 Garching, Germany
| | | | - Oliver F. Lange
- Biomolecular NMR and Munich Center for Integrated Protein Science, Department Chemie, Technische Universität München, Lichtenbergstr. 4, 85748 Garching, Germany
| | - Martin Zacharias
- Physik-Department T38, Technische Universität München, James-Franck-Str. 1, 84748 Garching, Germany
- * E-mail:
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21
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Toward understanding driving forces in membrane protein folding. Arch Biochem Biophys 2014; 564:297-313. [DOI: 10.1016/j.abb.2014.07.031] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2014] [Revised: 07/21/2014] [Accepted: 07/23/2014] [Indexed: 12/13/2022]
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22
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Voet ARD, Noguchi H, Addy C, Simoncini D, Terada D, Unzai S, Park SY, Zhang KYJ, Tame JRH. Computational design of a self-assembling symmetrical β-propeller protein. Proc Natl Acad Sci U S A 2014; 111:15102-7. [PMID: 25288768 PMCID: PMC4210308 DOI: 10.1073/pnas.1412768111] [Citation(s) in RCA: 93] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The modular structure of many protein families, such as β-propeller proteins, strongly implies that duplication played an important role in their evolution, leading to highly symmetrical intermediate forms. Previous attempts to create perfectly symmetrical propeller proteins have failed, however. We have therefore developed a new and rapid computational approach to design such proteins. As a test case, we have created a sixfold symmetrical β-propeller protein and experimentally validated the structure using X-ray crystallography. Each blade consists of 42 residues. Proteins carrying 2-10 identical blades were also expressed and purified. Two or three tandem blades assemble to recreate the highly stable sixfold symmetrical architecture, consistent with the duplication and fusion theory. The other proteins produce different monodisperse complexes, up to 42 blades (180 kDa) in size, which self-assemble according to simple symmetry rules. Our procedure is suitable for creating nano-building blocks from different protein templates of desired symmetry.
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Affiliation(s)
- Arnout R D Voet
- Structural Bioinformatics Team, Division of Structural and Synthetic Biology, Center for Life Science Technologies, RIKEN, 1-7-22 Suehiro, Yokohama, Kanagawa 230-0045, Japan; and Drug Design Laboratory, Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro, Yokohama, Kanagawa 230-0045, Japan
| | - Hiroki Noguchi
- Drug Design Laboratory, Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro, Yokohama, Kanagawa 230-0045, Japan
| | - Christine Addy
- Drug Design Laboratory, Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro, Yokohama, Kanagawa 230-0045, Japan
| | - David Simoncini
- Structural Bioinformatics Team, Division of Structural and Synthetic Biology, Center for Life Science Technologies, RIKEN, 1-7-22 Suehiro, Yokohama, Kanagawa 230-0045, Japan; and
| | - Daiki Terada
- Drug Design Laboratory, Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro, Yokohama, Kanagawa 230-0045, Japan
| | - Satoru Unzai
- Drug Design Laboratory, Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro, Yokohama, Kanagawa 230-0045, Japan
| | - Sam-Yong Park
- Drug Design Laboratory, Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro, Yokohama, Kanagawa 230-0045, Japan
| | - Kam Y J Zhang
- Structural Bioinformatics Team, Division of Structural and Synthetic Biology, Center for Life Science Technologies, RIKEN, 1-7-22 Suehiro, Yokohama, Kanagawa 230-0045, Japan; and
| | - Jeremy R H Tame
- Drug Design Laboratory, Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro, Yokohama, Kanagawa 230-0045, Japan
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23
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Doble MV, Ward AC, Deuss PJ, Jarvis AG, Kamer PC. Catalyst design in oxidation chemistry; from KMnO4 to artificial metalloenzymes. Bioorg Med Chem 2014; 22:5657-77. [DOI: 10.1016/j.bmc.2014.07.002] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2014] [Revised: 06/27/2014] [Accepted: 07/01/2014] [Indexed: 01/07/2023]
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