The 1 H, 15 N, and 13 C resonance assignments of a single-domain antibody against immunoglobulin G

The 1 H, 15 N, and 13 C resonance assignments of a single-domain antibody against immunoglobulin G | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The 1 H, 15 N, and 13 C resonance assignments of a single-domain antibody against immunoglobulin G Vanessa Bezerra Oliveira Leite, Rafael Alves Andrade, Fabio Ceneviva Lacerda Almeida, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4836731/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Sep, 2024 Read the published version in Biomolecular NMR Assignments → Version 1 posted 7 You are reading this latest preprint version Abstract Research on camelid-derived single-domain antibodies (sdAbs) has demonstrated their significant utility in diverse biotechnological applications, including therapy and diagnostic. This is largely due to their relative simplicity as monomeric proteins, ranging from 12–15 kDa, in contrast to immunoglobulin G (IgG) antibodies, which are glycosylated heterotetramers of 150–160 kDa. Single-domain antibodies exhibit high conformational stability and adopt the typical immunoglobulin domain fold, consisting of a two-layer sandwich of 7–9 antiparallel beta-strands. They contain three loops, known as complementary-determining regions (CDRs), which are assembled on the sdAb surface and are responsible for antigen recognition. The single-domain antibody examined in this study, sdAb-mrh-IgG, was engineered to recognize IgG from rats, mice, but it also weakly recognizes IgG from humans (Pleiner et al. 2018 ). A search of the Protein Data Bank revealed only one NMR structure of a single-domain antibody, which is unrelated to sdAb-mrh-IgG. The NMR chemical shift assignments of sdAb-mrh-IgG will be utilized to study its molecular dynamics and interactions with antigens in solution, which is fundamental for the rational design of novel single-domain antibodies. Single domain antibodies Nanobodies Variable heavy domain Immunoglobulin G Solution NMR Figures Figure 1 Figure 2 Biological context Discovered in camelid serum in the early 90’s, heavy-chain antibodies (HCAbs) have a singular exception when it comes about the structure of antibodies. HCAbs are composed of two heavy chains only, lacking the additional light chains of conventional antibodies (Hamers-Casterman et al. 1993 ). Nanobodies, also known as the variable heavy domain (V HH ) or single-domain antibodies (sdAb), consist of the antigen-binding immunoglobulin domain of the HCAbs (Muyldermans 2013 ). They are characterized by their relatively small size (~ 12–16 kDa), which is about ten times smaller than conventional antibodies (~ 150–160 kDa). Their 3D structure consists of a sandwich of two antiparallel β-sheets, with multiple loops, three of which are known as complementary-determining regions (CDRs) 1, 2 and 3, and are responsible for antigen interaction (Bork et al. 1994 ). Their immunoglobulin domain contains a hydrophobic core and at least one disulfide bond. Even though the nanobodies have three CDRs compared to six found in typical Immunoglobulin G, they still exhibit high binding specificity due to a longer CDR3 (Muyldermans 2013 ). Nanobodies also possess high conformational stability, capable of withstanding temperatures around 60 o C and 3 M guanidine chloride (van der Linden et al. 1999 ). Their high solubility is related to the substitution of four hydrophobic amino acids in conventional antibodies with four hydrophilic residues on the surface of their 3D structure (Vu et al. 1997). Because of their simpler structure and lack of glycosylation, nanobodies can be readily produced recombinantly in Escherichia coli . These characteristics make nanobodies a groundbreaking alternative to monoclonal antibodies. The nanobody studied in this work, sdAb-mrh-IgG, was engineered to recognize IgG from rats and mice, but it also weakly recognizes IgG from humans (Pleiner et al. 2018 ). The development of this antibody followed a traditional protocol, which involved immunizing alpacas and then selecting antigen-specific nanobodies through phage display. Due to the difficulties associated with animal manipulation and the phage display procedure, there are growing efforts for in silico nanobody development. In this context, the use of 3D structural data, including NMR data that reveals molecular dynamics and interactions in solution, is crucial for advancing computational methodologies. Methods and experiments Protein expression and purification The cDNA for the sdAb-mrh-IgG construct, containing a hexahistidine (His 6 ) tag at its C-terminus, was synthesized and cloned into the expression vector pET25(b) + under the MscI/NheI restriction sites (GenScript). Escherichia coli BL21 (DE3), transformed with this vector, was grown in minimal medium (M9) containing 15 NH 4 Cl (1 g/L), 13 C-glucose (3 g/L) and ampicilin (100 µg/mL). The expression was induced with 1.0 mM IPTG (isopropyl β-D-thiogalactoside) at 37 ºC for 16 h. Cells were centrifuged, and the pellet was disrupted by ultrasonication in buffer A (20 mM sodium phosphate pH 6.5, 150 mM NaCl, and 3 mM NaN 3 ), containing EDTA-free SigmaFast protease inhibitor cocktail. The cell debris was removed by centrifugation (8,000 ×g for 15 min at 4°C) and filtration through a 0.45 µm membrane. This supernatant was loaded onto a 5 mL HiTrap Chelating column (GE Healthcare Life Sciences), equilibrated with buffer A, and eluted with a gradient (0-100% in 50 mL) of buffer B (buffer A with 500 mM imidazole). The fractions containing the sdAb-mrh-IgG were collected and loaded onto a Superdex 75 column equilibrated with buffer A. The fractions containing the sdAb-mrh-IgG were concentrated to 0.5 µM using a 3 kDa MWCO Amicon Ultra-15 centrifugal filter unit (Merck Millipore). NMR experiments The samples for NMR were in buffer A with 10% D 2 O and 0.2 mM sodium 3-(trimethylsilyl)-1-propanesulfonate (DSS). The triple resonance NMR spectra were acquired at 25 o C on a Bruker 600 MHz AVANCE III spectrometer equipped with a pulse-field Z-axis gradient triple-resonance probe. The backbone resonances were sequence-specific assigned using 2D [ 15 N, 1 H]-HSQC spectrum (Fig. 1 ), 3D HNCO, 3D HNCA, 3D CBCA(CO)NH, 3D HNCACB, and 3D HBHA(CO)NH (Whitehead et al. 1997 ). The side-chain resonances were assigned using 2D [ 15 N, 1 H]-HSQC, 2D [ 13 C, 1 H]-HSQC, 3D (H)CCH-TOCSY, 3D HCCH-TOCSY (Kay et al. 1993 ), 3D CC(CO)NH (Carlomagno et al. 1996 ), 3D 15 N-edited [ 1 H, 1 H]-NOESY and 3D 13 C-edited [ 1 H, 1 H]-NOESY (one for aliphatic and one for aromatic groups). The NOESY spectra were acquired on a Bruker 900 MHz AVANCE III HD spectrometer using a pulse-field Z-axis gradient triple-resonance probe. The 1 H chemical shifts were directly referenced to DSS, enabling the indirect referencing of 15 N and 13 C chemical shifts according to the absolute frequency ratios (Wishart et al. 1995 ). The triple resonance spectra were collected with 25% non-uniform sampling (NUS) making use of Poisson-gap sampling and reconstructed the spectra using iterative soft threshold method (Hyberts et al. 2012 ). All spectral parameters are described in Table 1 . Data was processed using either Topspin v. 4.0.6 (Bruker Biospin) or NMRPipe v. 2023.129.13.28 (Delaglio et al. 1995 ) and analyzed with CCPNMR Analysis v. 2.5.2 (Vranken et al. 2005 ) available on NMRbox (Maciejewski et al. 2017 ). Table 1 Acquisition parameters for the NMR experiments used for sequence-specific backbone and side-chain resonance assignments of sdAb-mrh-IgG Experiment Pulse sequence Main aquisition parameters 2D [ 1 H, 15 N]-HSQC hsqcetf3gpsi TD: 1024/256; DS = 32; NS = 16 2D [ 1 H, 13 C]-HSQC hsqcetgpsi TD: 1024/256; DS = 16; NS = 8 3D HNCO hncogp3d TD: 1024/128/200; DS = 16; NS = 8 3D HNCA hncagp3d TD: 1024/128/256; DS = 128; NS = 120 3D HNCACB hncacbgp3d TD: 1024/80/140; DS = 128; NS = 96 3D CBCA(CO)NH cbcaconhgp3d TD: 1024/96/128; DS = 32; NS = 32 3D HBHA(CO)NH hbhaconhgp3d TD: 1024/96/144; DS = 32; NS = 16 3D 15 N-edited [ 1 H, 1 H]-TOCSY dipsihsqcetf3gpsi3d TD: 1024/96/128; DS = 128; NS = 16 3D CC(CO)NH ccconhgp3d TD: 1024/96/200; DS = 128; NS = 32 3D HCcH-TOCSY hcchdigp3d TD: 1024/160/160; DS = 128; NS = 16 3D HCCh-TOCSY hcchdigp3d2 TD: 1024/160/160; DS = 128; NS = 16 3D 13 C-edited [ 1 H- 1 H]-NOESY aliphatic noesyhsqcetgpsi3d TD: 2048/80/280; DS = 32; NS = 16 3D 13 C-edited [ 1 H- 1 H]-NOESY aromatic noesyhsqcetgpsi3d TD: 2048/72/180; DS = 32; NS = 16 3D 15 N- edited [ 1 H- 1 H]-NOESY noesyhsqcf3gpsi3d TD: 2048/64/256; DS = 32; NS = 16 3D 13 C-edited [ 1 H, 1 H]-COSY hcchcogp3d TD: 2048/100/180; DS = 32; NS = 16 Assignment and data deposition Chemical shift assignments for 1 H, 15 N, and 13 C have been deposited in Biological Magnetic Resonance Bank (BMRB) under ID 52557. Figure 1 shows the assigned 2D [ 1 H, 15 N]-HSQC spectrum of sdAb-mrh-IgG. We assigned 97.0% of the backbone nuclei ( 13 C α , 13 CO, H α , amide H N , and 15 N), excluding the C-terminal 6× His-tag. We assigned a total of 111 amide 1 H N (98.2%), 111 15 N (98.2%), 111 13 CO (92.5%), 118 13 C α (98.3%), and 131 H α (97.8%). For the 13 CH n aliphatic side chain moieties of the protein, 200 13 C (89.3%) and 446 1 H (91.0%) were assigned. For the 13 CH aromatic side chain moieties of the protein, 40 13 C (72.7%) and 46 1 H (83.6%) were assigned. From the resonance assignment, we could compare the chemical shift-derived order parameter (S 2 ) from the random coil index (Berjanskii and Wishart 2005 ) and calculate the secondary structure propensity using Talos-N (Shen and Bax 2013 ). It is clear that the secondary structure elements and order parameter of the sdAb-mrh-IgG are compatible with the secondary structures in the crystal structure of the Nanobody 11 in complex with Staphylococcus aureus endoribonuclease MazF [PDB Id.: 9G5Z], which is the most similar nanobody with 78% amino acid sequence identity to sdAb-mrh-IgG. The only two differences among these structures are the presence of helical content in residues 62–64, which is not present in 9G5Z, and a dislocation of an extended segment found in residues 108–111, which is represented by a β-strand in residues 105–110 of 9G5Z. It is worth noting that the lowest order parameter in the polypeptide segment correlates to residues 100–110, which correspond to the CDR3. Further studies are necessary to understand these structural features. Declarations All authors contributed to the study's conception and design, as well as to material preparation, data collection, and analysis. Vanessa Bezerra de Oliveira Leite wrote the first draft of the manuscript, and all authors commented on previous versions. All authors read and approved the final manuscript. Acknowledgements This work was supported by Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) and Conselho Nacional de Desenvolvimento Científco e Tecnológico (CNPq). The author TSA gratefully acknowledges the post-doctoral fellowship and financial support from FAPERJ (grant E-26/203.321/2022). We acknowledge the National Center of Nuclear Magnetic Resonance (CNRMN) for the NMR spectrometers. Conflict of interest The authors declare that there are no conflicts of interest. References Berjanskii MV, Wishart DS (2005) A simple method to predict protein flexibility using secondary chemical shifts. J Am Chem Soc 127:14970–14971. https://doi.org/10.1021/ja054842f Bork P, Holm L, Sander C (1994) The immunoglobulin fold. Structural classification, sequence patterns and common core. J Mol Biol 242:309–320. https://doi.org/10.1006/jmbi.1994.1582 Carlomagno T, Maurer M, Sattler M et al (1996) PLUSH TACSY: homonuclear planar TACSY with two-band selective shaped pulses applied to C(α), C’ transfer and C(β), C(aromatic) correlations. J Biomol NMR 8:161–170. https://doi.org/10.1007/BF00211162 Delaglio F, Grzesiek S, Vuister GW et al (1995) NMRPipe: a multi-dimensional spectral processing system based on UNIX pipes. J Biomol NMR 6:277–293. https://doi.org/10.1007/BF00197809 Hamers-Casterman C, Atarhouch T, Muyldermans S et al (1993) Naturally occurring antibodies devoid of light chains. Nature 363:446–448. https://doi: 10.1038/363446a0. Hyberts SG, Milbradt AG, Wagner AB et al (2012) Application of iterative soft thresholding for fast reconstruction of NMR data non-uniformly sampled with multidimensional Poisson Gap scheduling. J Biomol NMR 52:315–327. https://doi.org/10.1007/s10858-012-9611-z Kay LE, Xu GY, Singer AU et al (1993) A gradient-enhanced HCCH-TOCSY experiment for recording side-chain 1 H and 13 C correlations in H 2 O samples of proteins. J Magn Reson Ser B 101:333–337. https://doi.org/10.1006/jmrb.1993.1053 Maciejewski MW, Schuyler AD, Gryk MR et al (2017) NMRbox: a resource for biomolecular NMR computation. Biophys J 112:1529–1534. https://doi.org/10.1016/j.bpj.2017.03.011 Muyldermans S (2013) Nanobodies: natural single-domain antibodies. Annu rev biochem 82:775–797. https://doi.org/10.1146/annurev-biochem-063011-092449 Pleiner T, Bates M, Görlich D (2018) A toolbox of anti–mouse and anti–rabbit IgG secondary nanobodies. J Cell Biol 217:1143–1154. https://doi.org/10.1083/jcb.201709115 Shen Y, Bax A (2013) Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks. J Biomol NMR 56:227–241. https:// doi. org/ 10. 1007/s10858-013-9741-y van der Linden RH, Frenken LG, de Geus B et al (1999) Comparison of physical chemical properties of llama VHH antibody fragments and mouse monoclonal antibodies. Biochim Biophys acta, 1431:37–46. https://doi.org/10.1016/s0167-4838(99)00030-8 Vranken WF, Boucher W, Stevens TJ et al (2005) The CCPN data model for NMR spectroscopy: development of a software pipeline. Proteins 59:687–696. https://doi.org/10.1002/prot.20449 Whitehead B, Craven CJ, Waltho JP (1997) Double and triple resonance NMR methods for protein assignment. Methods Mol Biol 60:29–52. https://doi.org/10.1385/0-89603-309-0:29 Wishart DS, Bigam CG, Yao J et al (1995) 1 H, 13 C and 15 N chemical shift referencing in biomolecular NMR. J Biomol NMR 6:135–140. https://doi.org/10.1007/BF00211777 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 13 Sep, 2024 Read the published version in Biomolecular NMR Assignments → Version 1 posted Editorial decision: Revision requested 27 Aug, 2024 Reviews received at journal 27 Aug, 2024 Reviewers agreed at journal 15 Aug, 2024 Reviewers invited by journal 15 Aug, 2024 Editor assigned by journal 02 Aug, 2024 Submission checks completed at journal 02 Aug, 2024 First submitted to journal 31 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4836731","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":345768119,"identity":"f8b150f4-28bd-426e-a02c-7e38b5bcea72","order_by":0,"name":"Vanessa Bezerra Oliveira Leite","email":"","orcid":"","institution":"Federal University of Rio de Janeiro","correspondingAuthor":false,"prefix":"","firstName":"Vanessa","middleName":"Bezerra Oliveira","lastName":"Leite","suffix":""},{"id":345768120,"identity":"5890f159-f0a0-4036-8e19-8d5445f52429","order_by":1,"name":"Rafael Alves Andrade","email":"","orcid":"","institution":"Federal University of Rio de Janeiro","correspondingAuthor":false,"prefix":"","firstName":"Rafael","middleName":"Alves","lastName":"Andrade","suffix":""},{"id":345768121,"identity":"0fa8ff58-0d54-4e10-bf04-8a41627ba486","order_by":2,"name":"Fabio Ceneviva Lacerda Almeida","email":"","orcid":"","institution":"Federal University of Rio de Janeiro","correspondingAuthor":false,"prefix":"","firstName":"Fabio","middleName":"Ceneviva Lacerda","lastName":"Almeida","suffix":""},{"id":345768122,"identity":"2b40e01c-b15c-419c-a733-5a95b79c43c0","order_by":3,"name":"Claudia Jorge Nascimento","email":"","orcid":"","institution":"Federal University of the State of Rio de Janeiro (UNIRIO)","correspondingAuthor":false,"prefix":"","firstName":"Claudia","middleName":"Jorge","lastName":"Nascimento","suffix":""},{"id":345768123,"identity":"d121fb5d-bfd3-40a2-b03e-576ce8e816b7","order_by":4,"name":"Talita Stelling Araújo","email":"","orcid":"","institution":"Federal University of Rio de Janeiro","correspondingAuthor":false,"prefix":"","firstName":"Talita","middleName":"Stelling","lastName":"Araújo","suffix":""},{"id":345768124,"identity":"1e2dcabf-b7b5-4b71-bbcd-dbe6a6bfd878","order_by":5,"name":"Marcius Silva Almeida","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABD0lEQVRIie3PPUsDMRjA8ScIdYmdI7T6CYQrB62DH+ayOOUOpVA6iOYodDroel30K9wtzqkBbzl1PclicRYyOonxDjqIqTcK5g9PIMMvLwAu198MCQCC+G4Cot6bVQOGYJtpCC43BKUtCCBO2GZrCNjJ0UK+3FXT4/5i+bYSenJ70BV4MJv2IBrxn8mwOvUkK4mfqihYpY/K3zckLjGMe8JGwJPhnFCumCf35opmAo/WHANNLQ8bPhVahh+E3jyXNbnKvm7ZSoQ5POSEZhWuSeD9Sip2Jtk98fOy+ctgKTvnhpAxsT8sf2UXl/3r4kFqPVGH3WKWx3FyEtnItzpmdsygpCVoSN17W+FyuVz/oE/eCmvdKuQORAAAAABJRU5ErkJggg==","orcid":"","institution":"Federal University of Rio de Janeiro","correspondingAuthor":true,"prefix":"","firstName":"Marcius","middleName":"Silva","lastName":"Almeida","suffix":""}],"badges":[],"createdAt":"2024-07-31 15:29:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4836731/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4836731/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s12104-024-10199-x","type":"published","date":"2024-09-13T15:57:58+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":63577310,"identity":"49488ad7-b44b-49fa-825b-6136540b2d26","added_by":"auto","created_at":"2024-08-29 19:56:28","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":543511,"visible":true,"origin":"","legend":"\u003cp\u003eTwo-dimensional [\u003csup\u003e1\u003c/sup\u003eH, \u003csup\u003e15\u003c/sup\u003eN]-HSQC spectrum of uniformly \u003csup\u003e15\u003c/sup\u003eN/\u003csup\u003e13\u003c/sup\u003eC-labelled sdAb-mrh-IgG at 25 \u003csup\u003eo\u003c/sup\u003eC in 20 mM sodium phosphate pH 6.5, 150 mM NaCl, 3 mM NaN\u003csub\u003e3\u003c/sub\u003e and 10% (v/v) D\u003csub\u003e2\u003c/sub\u003eO. The labels show the assigned HN from the backbone and side-chain of the amino acid residues\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4836731/v1/572031a1cf0b8868d479e1a4.jpg"},{"id":63576823,"identity":"2a2e0e88-78c9-427f-aae3-039cd6019abe","added_by":"auto","created_at":"2024-08-29 19:48:28","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":502950,"visible":true,"origin":"","legend":"\u003cp\u003eSecondary structure and order parameter calculated from chemical shift assignments of uniformly \u003csup\u003e15\u003c/sup\u003eN/\u003csup\u003e13\u003c/sup\u003eC-labelled sdAb-mrh-IgG. \u003cstrong\u003ea\u003c/strong\u003e Talos-N secondary structure calculation as a function of residue number. In blue the probabilities for helix and in red for extended structure (β-strand). Dots represent the confidence for the secondary structure calculation. On the top, the red rectangles represent the β-strands and the blue the helices, corresponding to the secondary structure in the crystal structure of the most similar nanobody with 78% Identity with sdAb-mrh-IgG [PDB Id.: 9G5Z] \u003cstrong\u003eb\u003c/strong\u003e Random-coil index order parameter as a function of the residue number\u003c/p\u003e","description":"","filename":"Figure21.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4836731/v1/8fe3d9b8b60d7cb12040cf35.jpg"},{"id":64619213,"identity":"79286f41-3276-4a9e-b35c-c8332f8d2325","added_by":"auto","created_at":"2024-09-16 16:12:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1386090,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4836731/v1/43a05b1b-2e53-43fc-ab25-c29f0f79ef74.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The 1 H, 15 N, and 13 C resonance assignments of a single-domain antibody against immunoglobulin G","fulltext":[{"header":"Biological context","content":"\u003cp\u003eDiscovered in camelid serum in the early 90\u0026rsquo;s, heavy-chain antibodies (HCAbs) have a singular exception when it comes about the structure of antibodies. HCAbs are composed of two heavy chains only, lacking the additional light chains of conventional antibodies (Hamers-Casterman et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). Nanobodies, also known as the variable heavy domain (V\u003csub\u003eHH\u003c/sub\u003e) or single-domain antibodies (sdAb), consist of the antigen-binding immunoglobulin domain of the HCAbs (Muyldermans \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). They are characterized by their relatively small size (~\u0026thinsp;12\u0026ndash;16 kDa), which is about ten times smaller than conventional antibodies (~\u0026thinsp;150\u0026ndash;160 kDa). Their 3D structure consists of a sandwich of two antiparallel β-sheets, with multiple loops, three of which are known as complementary-determining regions (CDRs) 1, 2 and 3, and are responsible for antigen interaction (Bork et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). Their immunoglobulin domain contains a hydrophobic core and at least one disulfide bond.\u003c/p\u003e \u003cp\u003eEven though the nanobodies have three CDRs compared to six found in typical Immunoglobulin G, they still exhibit high binding specificity due to a longer CDR3 (Muyldermans \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Nanobodies also possess high conformational stability, capable of withstanding temperatures around 60 \u003csup\u003eo\u003c/sup\u003eC and 3 M guanidine chloride (van der Linden et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Their high solubility is related to the substitution of four hydrophobic amino acids in conventional antibodies with four hydrophilic residues on the surface of their 3D structure (Vu et al. 1997). Because of their simpler structure and lack of glycosylation, nanobodies can be readily produced recombinantly in \u003cem\u003eEscherichia coli\u003c/em\u003e. These characteristics make nanobodies a groundbreaking alternative to monoclonal antibodies.\u003c/p\u003e \u003cp\u003eThe nanobody studied in this work, sdAb-mrh-IgG, was engineered to recognize IgG from rats and mice, but it also weakly recognizes IgG from humans (Pleiner et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The development of this antibody followed a traditional protocol, which involved immunizing alpacas and then selecting antigen-specific nanobodies through phage display. Due to the difficulties associated with animal manipulation and the phage display procedure, there are growing efforts for \u003cem\u003ein silico\u003c/em\u003e nanobody development. In this context, the use of 3D structural data, including NMR data that reveals molecular dynamics and interactions in solution, is crucial for advancing computational methodologies.\u003c/p\u003e"},{"header":"Methods and experiments","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eProtein expression and purification\u003c/h2\u003e \u003cp\u003eThe cDNA for the sdAb-mrh-IgG construct, containing a hexahistidine (His\u003csub\u003e6\u003c/sub\u003e) tag at its C-terminus, was synthesized and cloned into the expression vector pET25(b)\u0026thinsp;+\u0026thinsp;under the MscI/NheI restriction sites (GenScript). \u003cem\u003eEscherichia coli\u003c/em\u003e BL21 (DE3), transformed with this vector, was grown in minimal medium (M9) containing \u003csup\u003e15\u003c/sup\u003eNH\u003csub\u003e4\u003c/sub\u003eCl (1 g/L), \u003csup\u003e13\u003c/sup\u003eC-glucose (3 g/L) and ampicilin (100 \u0026micro;g/mL). The expression was induced with 1.0 mM IPTG (isopropyl β-D-thiogalactoside) at 37 \u0026ordm;C for 16 h. Cells were centrifuged, and the pellet was disrupted by ultrasonication in buffer A (20 mM sodium phosphate pH 6.5, 150 mM NaCl, and 3 mM NaN\u003csub\u003e3\u003c/sub\u003e), containing EDTA-free SigmaFast protease inhibitor cocktail. The cell \u003cem\u003edebris\u003c/em\u003e was removed by centrifugation (8,000 \u0026times;g for 15 min at 4\u0026deg;C) and filtration through a 0.45 \u0026micro;m membrane. This supernatant was loaded onto a 5 mL HiTrap Chelating column (GE Healthcare Life Sciences), equilibrated with buffer A, and eluted with a gradient (0-100% in 50 mL) of buffer B (buffer A with 500 mM imidazole). The fractions containing the sdAb-mrh-IgG were collected and loaded onto a Superdex 75 column equilibrated with buffer A. The fractions containing the sdAb-mrh-IgG were concentrated to 0.5 \u0026micro;M using a 3 kDa MWCO Amicon Ultra-15 centrifugal filter unit (Merck Millipore).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eNMR experiments\u003c/h2\u003e \u003cp\u003eThe samples for NMR were in buffer A with 10% D\u003csub\u003e2\u003c/sub\u003eO and 0.2 mM sodium 3-(trimethylsilyl)-1-propanesulfonate (DSS). The triple resonance NMR spectra were acquired at 25 \u003csup\u003eo\u003c/sup\u003eC on a Bruker 600 MHz AVANCE III spectrometer equipped with a pulse-field Z-axis gradient triple-resonance probe. The backbone resonances were sequence-specific assigned using 2D [\u003csup\u003e15\u003c/sup\u003eN,\u003csup\u003e1\u003c/sup\u003eH]-HSQC spectrum (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), 3D HNCO, 3D HNCA, 3D CBCA(CO)NH, 3D HNCACB, and 3D HBHA(CO)NH (Whitehead et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). The side-chain resonances were assigned using 2D [\u003csup\u003e15\u003c/sup\u003eN,\u003csup\u003e1\u003c/sup\u003eH]-HSQC, 2D [\u003csup\u003e13\u003c/sup\u003eC,\u003csup\u003e1\u003c/sup\u003eH]-HSQC, 3D (H)CCH-TOCSY, 3D HCCH-TOCSY (Kay et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1993\u003c/span\u003e), 3D CC(CO)NH (Carlomagno et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1996\u003c/span\u003e), 3D \u003csup\u003e15\u003c/sup\u003eN-edited [\u003csup\u003e1\u003c/sup\u003eH,\u003csup\u003e1\u003c/sup\u003eH]-NOESY and 3D \u003csup\u003e13\u003c/sup\u003eC-edited [\u003csup\u003e1\u003c/sup\u003eH,\u003csup\u003e1\u003c/sup\u003eH]-NOESY (one for aliphatic and one for aromatic groups). The NOESY spectra were acquired on a Bruker 900 MHz AVANCE III HD spectrometer using a pulse-field Z-axis gradient triple-resonance probe. The \u003csup\u003e1\u003c/sup\u003eH chemical shifts were directly referenced to DSS, enabling the indirect referencing of \u003csup\u003e15\u003c/sup\u003eN and \u003csup\u003e13\u003c/sup\u003eC chemical shifts according to the absolute frequency ratios (Wishart et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). The triple resonance spectra were collected with 25% non-uniform sampling (NUS) making use of Poisson-gap sampling and reconstructed the spectra using iterative soft threshold method (Hyberts et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). All spectral parameters are described in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Data was processed using either Topspin v. 4.0.6 (Bruker Biospin) or NMRPipe v. 2023.129.13.28 (Delaglio et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1995\u003c/span\u003e) and analyzed with CCPNMR Analysis v. 2.5.2 (Vranken et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) available on NMRbox (Maciejewski et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAcquisition parameters for the NMR experiments used for sequence-specific backbone and side-chain resonance assignments of sdAb-mrh-IgG\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExperiment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePulse sequence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMain aquisition parameters\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2D [\u003csup\u003e1\u003c/sup\u003eH,\u003csup\u003e15\u003c/sup\u003eN]-HSQC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehsqcetf3gpsi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTD: 1024/256; DS\u0026thinsp;=\u0026thinsp;32; NS\u0026thinsp;=\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2D [\u003csup\u003e1\u003c/sup\u003eH,\u003csup\u003e13\u003c/sup\u003eC]-HSQC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehsqcetgpsi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTD: 1024/256; DS\u0026thinsp;=\u0026thinsp;16; NS\u0026thinsp;=\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3D HNCO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehncogp3d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTD: 1024/128/200; DS\u0026thinsp;=\u0026thinsp;16; NS\u0026thinsp;=\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3D HNCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehncagp3d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTD: 1024/128/256; DS\u0026thinsp;=\u0026thinsp;128; NS\u0026thinsp;=\u0026thinsp;120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3D HNCACB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehncacbgp3d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTD: 1024/80/140; DS\u0026thinsp;=\u0026thinsp;128; NS\u0026thinsp;=\u0026thinsp;96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3D CBCA(CO)NH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecbcaconhgp3d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTD: 1024/96/128; DS\u0026thinsp;=\u0026thinsp;32; NS\u0026thinsp;=\u0026thinsp;32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3D HBHA(CO)NH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehbhaconhgp3d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTD: 1024/96/144; DS\u0026thinsp;=\u0026thinsp;32; NS\u0026thinsp;=\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3D \u003csup\u003e15\u003c/sup\u003eN-edited [\u003csup\u003e1\u003c/sup\u003eH,\u003csup\u003e1\u003c/sup\u003eH]-TOCSY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003edipsihsqcetf3gpsi3d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTD: 1024/96/128; DS\u0026thinsp;=\u0026thinsp;128; NS\u0026thinsp;=\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3D CC(CO)NH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eccconhgp3d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTD: 1024/96/200; DS\u0026thinsp;=\u0026thinsp;128; NS\u0026thinsp;=\u0026thinsp;32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3D HCcH-TOCSY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehcchdigp3d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTD: 1024/160/160; DS\u0026thinsp;=\u0026thinsp;128; NS\u0026thinsp;=\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3D HCCh-TOCSY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehcchdigp3d2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTD: 1024/160/160; DS\u0026thinsp;=\u0026thinsp;128; NS\u0026thinsp;=\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3D \u003csup\u003e13\u003c/sup\u003eC-edited [\u003csup\u003e1\u003c/sup\u003eH-\u003csup\u003e1\u003c/sup\u003eH]-NOESY aliphatic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003enoesyhsqcetgpsi3d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTD: 2048/80/280; DS\u0026thinsp;=\u0026thinsp;32; NS\u0026thinsp;=\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3D \u003csup\u003e13\u003c/sup\u003eC-edited [\u003csup\u003e1\u003c/sup\u003eH-\u003csup\u003e1\u003c/sup\u003eH]-NOESY aromatic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003enoesyhsqcetgpsi3d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTD: 2048/72/180; DS\u0026thinsp;=\u0026thinsp;32; NS\u0026thinsp;=\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3D \u003csup\u003e15\u003c/sup\u003eN- edited [\u003csup\u003e1\u003c/sup\u003eH-\u003csup\u003e1\u003c/sup\u003eH]-NOESY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003enoesyhsqcf3gpsi3d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTD: 2048/64/256; DS\u0026thinsp;=\u0026thinsp;32; NS\u0026thinsp;=\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3D \u003csup\u003e13\u003c/sup\u003eC-edited [\u003csup\u003e1\u003c/sup\u003eH,\u003csup\u003e1\u003c/sup\u003eH]-COSY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehcchcogp3d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTD: 2048/100/180; DS\u0026thinsp;=\u0026thinsp;32; NS\u0026thinsp;=\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eAssignment and data deposition\u003c/h2\u003e \u003cp\u003eChemical shift assignments for \u003csup\u003e1\u003c/sup\u003eH, \u003csup\u003e15\u003c/sup\u003eN, and \u003csup\u003e13\u003c/sup\u003eC have been deposited in Biological Magnetic Resonance Bank (BMRB) under ID 52557. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the assigned 2D [\u003csup\u003e1\u003c/sup\u003eH, \u003csup\u003e15\u003c/sup\u003eN]-HSQC spectrum of sdAb-mrh-IgG. We assigned 97.0% of the backbone nuclei (\u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eα\u003c/sub\u003e, \u003csup\u003e13\u003c/sup\u003eCO, H\u003csub\u003eα\u003c/sub\u003e, amide H\u003csub\u003eN\u003c/sub\u003e, and \u003csup\u003e15\u003c/sup\u003eN), excluding the C-terminal 6\u0026times; His-tag. We assigned a total of 111 amide \u003csup\u003e1\u003c/sup\u003eH\u003csub\u003eN\u003c/sub\u003e (98.2%), 111 \u003csup\u003e15\u003c/sup\u003eN (98.2%), 111 \u003csup\u003e13\u003c/sup\u003eCO (92.5%), 118 \u003csup\u003e13\u003c/sup\u003eC\u003csub\u003eα\u003c/sub\u003e (98.3%), and 131 H\u003csub\u003eα\u003c/sub\u003e (97.8%). For the \u003csup\u003e13\u003c/sup\u003eCH\u003csub\u003en\u003c/sub\u003e aliphatic side chain moieties of the protein, 200 \u003csup\u003e13\u003c/sup\u003eC (89.3%) and 446 \u003csup\u003e1\u003c/sup\u003eH (91.0%) were assigned. For the \u003csup\u003e13\u003c/sup\u003eCH aromatic side chain moieties of the protein, 40 \u003csup\u003e13\u003c/sup\u003eC (72.7%) and 46 \u003csup\u003e1\u003c/sup\u003eH (83.6%) were assigned. From the resonance assignment, we could compare the chemical shift-derived order parameter (S\u003csup\u003e2\u003c/sup\u003e) from the random coil index (Berjanskii and Wishart \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) and calculate the secondary structure propensity using Talos-N (Shen and Bax \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). It is clear that the secondary structure elements and order parameter of the sdAb-mrh-IgG are compatible with the secondary structures in the crystal structure of the Nanobody 11 in complex with \u003cem\u003eStaphylococcus aureus\u003c/em\u003e endoribonuclease MazF [PDB Id.: 9G5Z], which is the most similar nanobody with 78% amino acid sequence identity to sdAb-mrh-IgG. The only two differences among these structures are the presence of helical content in residues 62\u0026ndash;64, which is not present in 9G5Z, and a dislocation of an extended segment found in residues 108\u0026ndash;111, which is represented by a β-strand in residues 105\u0026ndash;110 of 9G5Z. It is worth noting that the lowest order parameter in the polypeptide segment correlates to residues 100\u0026ndash;110, which correspond to the CDR3. Further studies are necessary to understand these structural features.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eAll authors contributed to the study\u0026apos;s conception and design, as well as to material preparation, data collection, and analysis. Vanessa Bezerra de Oliveira Leite wrote the first draft of the manuscript, and all authors commented on previous versions. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e This work was supported by Funda\u0026ccedil;\u0026atilde;o Carlos Chagas Filho de Amparo \u0026agrave; Pesquisa do Estado do Rio de Janeiro (FAPERJ) and Conselho Nacional de Desenvolvimento Cient\u0026iacute;fco e Tecnol\u0026oacute;gico (CNPq). The author TSA gratefully acknowledges the post-doctoral fellowship and financial support from FAPERJ (grant E-26/203.321/2022). We acknowledge the National Center of Nuclear Magnetic Resonance (CNRMN) for the NMR spectrometers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e The authors declare that there are no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBerjanskii MV, Wishart DS (2005) A simple method to predict protein flexibility using secondary chemical shifts. J Am Chem Soc 127:14970\u0026ndash;14971. https://doi.org/10.1021/ja054842f\u003c/li\u003e\n\u003cli\u003eBork P, Holm L, Sander C (1994) The immunoglobulin fold. Structural classification, sequence patterns and common core. J Mol Biol 242:309\u0026ndash;320. https://doi.org/10.1006/jmbi.1994.1582\u003c/li\u003e\n\u003cli\u003eCarlomagno T, Maurer M, Sattler M et al (1996) PLUSH TACSY: homonuclear planar TACSY with two-band selective shaped pulses applied to C(\u0026alpha;), C\u0026rsquo; transfer and C(\u0026beta;), C(aromatic) correlations. J Biomol NMR 8:161\u0026ndash;170. https://doi.org/10.1007/BF00211162\u003c/li\u003e\n\u003cli\u003eDelaglio F, Grzesiek S, Vuister GW et al (1995) NMRPipe: a multi-dimensional spectral processing system based on UNIX pipes. J Biomol NMR 6:277\u0026ndash;293. https://doi.org/10.1007/BF00197809\u003c/li\u003e\n\u003cli\u003eHamers-Casterman C, Atarhouch T, Muyldermans S et al (1993) Naturally occurring antibodies devoid of light chains. Nature 363:446\u0026ndash;448. https://doi: 10.1038/363446a0.\u003c/li\u003e\n\u003cli\u003eHyberts SG, Milbradt AG, Wagner AB et al (2012) Application of iterative soft thresholding for fast reconstruction of NMR data non-uniformly sampled with multidimensional Poisson Gap scheduling. J Biomol NMR 52:315\u0026ndash;327. https://doi.org/10.1007/s10858-012-9611-z\u003c/li\u003e\n\u003cli\u003eKay LE, Xu GY, Singer AU et al (1993) A gradient-enhanced HCCH-TOCSY experiment for recording side-chain \u003csup\u003e1\u003c/sup\u003eH and \u003csup\u003e13\u003c/sup\u003eC correlations in H\u003csub\u003e2\u003c/sub\u003eO samples of proteins. J Magn Reson Ser B 101:333\u0026ndash;337. https://doi.org/10.1006/jmrb.1993.1053\u003c/li\u003e\n\u003cli\u003eMaciejewski MW, Schuyler AD, Gryk MR et al (2017) NMRbox: a resource for biomolecular NMR computation. Biophys J 112:1529\u0026ndash;1534. https://doi.org/10.1016/j.bpj.2017.03.011\u003c/li\u003e\n\u003cli\u003eMuyldermans S (2013) Nanobodies: natural single-domain antibodies. Annu rev biochem 82:775\u0026ndash;797. https://doi.org/10.1146/annurev-biochem-063011-092449\u003c/li\u003e\n\u003cli\u003ePleiner T, Bates M, G\u0026ouml;rlich D (2018) A toolbox of anti\u0026ndash;mouse and anti\u0026ndash;rabbit IgG secondary nanobodies. J Cell Biol 217:1143\u0026ndash;1154. https://doi.org/10.1083/jcb.201709115\u003c/li\u003e\n\u003cli\u003eShen Y, Bax A (2013) Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks. J Biomol NMR 56:227\u0026ndash;241. https:// doi. org/ 10. 1007/s10858-013-9741-y\u003c/li\u003e\n\u003cli\u003evan der Linden RH, Frenken LG, de Geus B et al (1999) Comparison of physical chemical properties of llama VHH antibody fragments and mouse monoclonal antibodies. Biochim Biophys acta, 1431:37\u0026ndash;46. https://doi.org/10.1016/s0167-4838(99)00030-8\u003c/li\u003e\n\u003cli\u003eVranken WF, Boucher W, Stevens TJ et al (2005) The CCPN data model for NMR spectroscopy: development of a software pipeline. Proteins 59:687\u0026ndash;696. https://doi.org/10.1002/prot.20449\u003c/li\u003e\n\u003cli\u003eWhitehead B, Craven CJ, Waltho JP (1997) Double and triple resonance NMR methods for protein assignment. Methods Mol Biol 60:29\u0026ndash;52. https://doi.org/10.1385/0-89603-309-0:29\u003c/li\u003e\n\u003cli\u003eWishart DS, Bigam CG, Yao J et al (1995) \u003csup\u003e1\u003c/sup\u003eH, \u003csup\u003e13\u003c/sup\u003eC and \u003csup\u003e15\u003c/sup\u003eN chemical shift referencing in biomolecular NMR. J Biomol NMR 6:135\u0026ndash;140. https://doi.org/10.1007/BF00211777\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"biomolecular-nmr-assignments","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnmr","sideBox":"Learn more about [Biomolecular NMR Assignments](http://link.springer.com/journal/12104)","snPcode":"12104","submissionUrl":"https://submission.nature.com/new-submission/12104/3","title":"Biomolecular NMR Assignments","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Single domain antibodies, Nanobodies, Variable heavy domain, Immunoglobulin G, Solution NMR","lastPublishedDoi":"10.21203/rs.3.rs-4836731/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4836731/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eResearch on camelid-derived single-domain antibodies (sdAbs) has demonstrated their significant utility in diverse biotechnological applications, including therapy and diagnostic. This is largely due to their relative simplicity as monomeric proteins, ranging from 12\u0026ndash;15 kDa, in contrast to immunoglobulin G (IgG) antibodies, which are glycosylated heterotetramers of 150\u0026ndash;160 kDa. Single-domain antibodies exhibit high conformational stability and adopt the typical immunoglobulin domain fold, consisting of a two-layer sandwich of 7\u0026ndash;9 antiparallel beta-strands. They contain three loops, known as complementary-determining regions (CDRs), which are assembled on the sdAb surface and are responsible for antigen recognition. The single-domain antibody examined in this study, sdAb-mrh-IgG, was engineered to recognize IgG from rats, mice, but it also weakly recognizes IgG from humans (Pleiner et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). A search of the Protein Data Bank revealed only one NMR structure of a single-domain antibody, which is unrelated to sdAb-mrh-IgG. The NMR chemical shift assignments of sdAb-mrh-IgG will be utilized to study its molecular dynamics and interactions with antigens in solution, which is fundamental for the rational design of novel single-domain antibodies.\u003c/p\u003e","manuscriptTitle":"The 1 H, 15 N, and 13 C resonance assignments of a single-domain antibody against immunoglobulin G","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-29 19:48:23","doi":"10.21203/rs.3.rs-4836731/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-27T12:53:40+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-27T12:53:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"262798092712559215044698309958781239135","date":"2024-08-15T20:57:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-15T20:56:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-02T14:48:38+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-02T14:47:15+00:00","index":"","fulltext":""},{"type":"submitted","content":"Biomolecular NMR Assignments","date":"2024-07-31T15:28:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"biomolecular-nmr-assignments","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnmr","sideBox":"Learn more about [Biomolecular NMR Assignments](http://link.springer.com/journal/12104)","snPcode":"12104","submissionUrl":"https://submission.nature.com/new-submission/12104/3","title":"Biomolecular NMR Assignments","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"7fbc3fcb-e016-4e9b-852e-e1f2dfa9462b","owner":[],"postedDate":"August 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-09-16T16:03:56+00:00","versionOfRecord":{"articleIdentity":"rs-4836731","link":"https://doi.org/10.1007/s12104-024-10199-x","journal":{"identity":"biomolecular-nmr-assignments","isVorOnly":false,"title":"Biomolecular NMR Assignments"},"publishedOn":"2024-09-13 15:57:58","publishedOnDateReadable":"September 13th, 2024"},"versionCreatedAt":"2024-08-29 19:48:23","video":"","vorDoi":"10.1007/s12104-024-10199-x","vorDoiUrl":"https://doi.org/10.1007/s12104-024-10199-x","workflowStages":[]},"version":"v1","identity":"rs-4836731","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4836731","identity":"rs-4836731","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}