ABangle: characterising the VH-VL orientation in antibodies
Abstract
The binding site of an antibody is formed between the two variable domains, VH and VL, of its antigen binding fragment (Fab). Understanding how VH and VL orientate with respect to one another is important both for studying the mechanisms of antigen specificity and affinity and improving antibody modelling, docking and engineering. Different VH-VL orientations are commonly described using relative measures such as root-mean-square deviation. Recently, the orientation has also been characterised using the absolute measure of a VH-VL packing angle. However, a single angle cannot fully describe all modes of orientation. Here, we present a method which fully characterises VH-VL orientation in a consistent and absolute sense using five angles (HL, HC1, LC1, HC2 and LC2) and a distance (dc). Additionally, we provide a computational tool, ABangle, to allow the VH-VL orientation for any antibody to be automatically calculated and compared with all other known structures. We compare previous studies and show how the modes of orientation being identified relate to movements of different angles. Thus, we are able to explain why different studies identify different structural clusters and different residues as important. Given this result, we then identify those positions and their residue identities which influence each of the angular measures of orientation. Finally, by analysing VH-VL orientation in bound and unbound forms, we find that antibodies specific for protein antigens are significantly more flexible in their unbound form than antibodies specific for hapten antigens. ABangle is freely available at http://opig.stats.ox.ac.uk/webapps/abangle.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Accurate determination of the relative orientation of the VH and VL domains is crucial to determine the correct shape of the paratope.
“The second step involves accurate determination of the relative orientation of the VH and VL domains, which is crucial to determine the correct shape of the paratope [107, 109].”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [109]
Cites
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538 · see citing works
The PyMOL Molecular Graphics System
DeLano, W. L. (2002) · Medical Entomology and Zoology · Cited by 18,147 · see citing works
Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences
Li, W.-Z., & Godzik, A. (2006) · Bioinform. · doi:10.1093/bioinformatics/btl158 · Cited by 10,994 · see citing works
The protein data bank: A computer-based archival file for macromolecular structures
Bernstein, F. C., Koetzle, T. F., Williams, G. J. B., Meyer, E. F., Brice, M. D., Rodgers, J. R., Kennard, O., Shimanouchi, T., & Tasumi, M. (1977) · Journal of Molecular Biology · doi:10.1016/s0022-2836(77)80200-3 · Cited by 8,582 · see citing works
The Kolmogorov-Smirnov Test for Goodness of Fit
Massey, F. J. (1951) · Journal of the American Statistical Association · doi:10.1080/01621459.1951.10500769 · Cited by 7,210 · see citing works
TM-align: a protein structure alignment algorithm based on the TM-score
Zhang, Y. (2005) · Nucleic Acids Research · doi:10.1093/nar/gki524 · Cited by 3,774 · see citing works
Reshaping human antibodies for therapy
Riechmann, L., Clark, M., Waldmann, H., & Winter, G. P. (1988) · Nature · doi:10.1038/332323a0 · Cited by 1,562 · see citing works
Canonical structures for the hypervariable regions of immunoglobulins
Chothia, C., & Lesk, A. M. (1987) · Journal of Molecular Biology · doi:10.1016/0022-2836(87)90412-8 · Cited by 1,406 · see citing works
Wu, T. T., & Kabat, E. A. (1970) · The Journal of Experimental Medicine · doi:10.1084/jem.132.2.211 · Cited by 1,340 · see citing works
Conformations of immunoglobulin hypervariable regions
Chothia, C., Lesk, A. M., Tramontano, A. L., Levitt, M., Smith‐Gill, S. J., Air, G. M., Sheriff, S., PADLAN, E. A., Davies, D. R., Tulip, W. R., et al. (1989) · Nature · doi:10.1038/342877a0 · Cited by 1,185 · see citing works
LGA: a method for finding 3D similarities in protein structures
Zemla, A. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkg571 · Cited by 1,069 · see citing works
Three-Dimensional Structure of Immunoglobulins
Amzel, L. M., & Poljak, R. J. (1979) · Annual Review of Biochemistry · doi:10.1146/annurev.bi.48.070179.004525 · Cited by 697 · see citing works
Three-dimensional structure of a complex of antibody with influenza virus neuraminidase
Colman, P. M., Laver, W. G., Varghese, J. N., Baker, A. T., Tulloch, P. A., Air, G. M., & Webster, R. G. (1987) · Nature · doi:10.1038/326358a0 · Cited by 553 · see citing works
Antibody framework residues affecting the conformation of the hypervariable loops
Foote, J., & Winter, G. P. (1992) · Journal of Molecular Biology · doi:10.1016/0022-2836(92)91010-m · Cited by 525 · see citing works
Domain association in immunoglobulin molecules
Chothia, C., Novotný, J., Bruccoleri, R. E., & Karplus, M. (1985) · Journal of Molecular Biology · doi:10.1016/0022-2836(85)90137-8 · Cited by 396 · see citing works
JOY: protein sequence-structure representation and analysis.
Mizuguchi, K., Deane, C. M., Blundell, T. L., Johnson, M. S., & Overington, J. P. (1998) · Bioinformatics · doi:10.1093/bioinformatics/14.7.617 · Cited by 390 · see citing works
Structural Basis of Antibody Function
Davies, D. R., & Metzger, H. (1983) · Annual Review of Immunology · doi:10.1146/annurev.iy.01.040183.000511 · Cited by 375 · see citing works
Comparing sequences without using alignments: application to HIV/SIV subtyping
Didier, G., Debomy, L., Pupin, M., Zhang, M., Großmann, A., Landès, C., & Laprevotte, I. (2007) · BMC Bioinformatics · doi:10.1186/1471-2105-8-1 · Cited by 362 · see citing works
Prediction of protein conformational freedom from distance constraints
de Groot, B. L., van Aalten, D. M. F., Scheek, R. M., Amadei, A., Vriend, G., & Berendsen, H. J. C. (1997) · Proteins Structure Function and Bioinformatics · doi:10.1002/(sici)1097-0134(199710)29:2 · Cited by 269 · see citing works
Analysis and improvements to Kabat and structurally correct numbering of antibody variable domains
Abhinandan, K. R., & Martin, A. C. R. (2008) · Molecular Immunology · doi:10.1016/j.molimm.2008.05.022 · Cited by 234 · see citing works
Computer-aided antibody design
Kuroda, D., Shirai, H., Jacobson, M. P., & Nakamura, H. (2012) · Protein Engineering Design and Selection · doi:10.1093/protein/gzs024 · Cited by 223 · see citing works
Structure of Antibody-Antigen Complexes: Implications for Immune Recognition
Colman, P. M. (1988) · Advances in immunology · doi:10.1016/s0065-2776(08)60364-8 · Cited by 209 · see citing works
Major antigen-induced domain rearrangements in an antibody
Stanfield, R. L., Takimoto‐Kamimura, M., Rini, J. M., Profy, A. T., & Wilson, I. A. (1993) · Structure · doi:10.1016/0969-2126(93)90024-b · Cited by 209 · see citing works
Strobl, C., Hothorn, T., & Zeileis, A. (2009) · The R Journal · doi:10.32614/rj-2009-013 · Cited by 202 · see citing works
Sivasubramanian, A., Sircar, A., Chaudhury, S., & Gray, J. J. (2008) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22309 · Cited by 185 · see citing works
PIGS: automatic prediction of antibody structures
Marcatili, P., Rosi, A., & Tramontano, A. L. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn341 · Cited by 174 · see citing works
RosettaAntibody: antibody variable region homology modeling server
Sircar, A., Kim, E. T., & Gray, J. J. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp387 · Cited by 161 · see citing works
WAM: an improved algorithm for modelling antibodies on the WEB
Whitelegg, N., & Rees, A. R. (2000) · Protein Engineering Design and Selection · doi:10.1093/protein/13.12.819 · Cited by 159 · see citing works
A new progressive-iterative algorithm for multiple structure alignment
Lupyan, D., Leo‐Macías, A., & Ortíz, Á. R. (2005) · Bioinformatics · doi:10.1093/bioinformatics/bti527 · Cited by 145 · see citing works
Almagro, J. C., Beavers, M. P., Hernandez‐Guzman, F., Maier, J., Shaulsky, J., Butenhof, K., Labute, P., Thorsteinson, N., Kelly, K., Teplyakov, A., et al. (2011) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.23130 · Cited by 131 · see citing works
A Systematic Comparison of Free and Bound Antibodies Reveals Binding-Related Conformational Changes
Sela‐Culang, I., Alon, S., & Ofran, Y. (2012) · The Journal of Immunology · doi:10.4049/jimmunol.1201493 · Cited by 115 · see citing works
Assessment of CASP7 predictions in the high accuracy template-based modeling category
Read, R. J., & Chavali, G. B. (2007) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.21662 · Cited by 111 · see citing works
Chailyan, A., Marcatili, P., & Tramontano, A. L. (2011) · FEBS Journal · doi:10.1111/j.1742-4658.2011.08207.x · Cited by 106 · see citing works
Li, Y., Li, H., Smith‐Gill, S. J., & Mariuzza, R. A. (2000) · Biochemistry · doi:10.1021/bi000054l · Cited by 92 · see citing works
Analysis and prediction of VH/VL packing in antibodies
Abhinandan, K. R., & Martin, A. C. R. (2010) · Protein Engineering Design and Selection · doi:10.1093/protein/gzq043 · Cited by 88 · see citing works
Germline VH/VL pairing in antibodies
Jayaram, N., Bhowmick, P., & Martin, A. C. R. (2012) · Protein Engineering Design and Selection · doi:10.1093/protein/gzs043 · Cited by 64 · see citing works
Vargas‐Madrazo, E., & Paz‐García, E. (2003) · Journal of Molecular Recognition · doi:10.1002/jmr.613 · Cited by 53 · see citing works
Narayanan, A., Sellers, B. D., & Jacobson, M. P. (2009) · Journal of Molecular Biology · doi:10.1016/j.jmb.2009.03.043 · Cited by 41 · see citing works
Antigen recognition by antibody C836 through adjustment of VL/VHpacking
Teplyakov, A., Obmolova, G., Malia, T., & Gilliland, G. L. (2011) · Acta Crystallographica Section F Structural Biology and Crystallization Communications · doi:10.1107/s1744309111027746 · Cited by 16 · see citing works
Nagl, S., Das, S., & Smith, T. (2000) · Journal of Molecular Recognition · doi:10.1002/1099-1352(200005/06)13:3
Flagged first, then by citations
Cited by
Sorted by citations
SAbDab: the structural antibody database
Dunbar, J., Krawczyk, K., Leem, J., Baker, T., Fuchs, A., Georges, G., Shi, J., & Deane, C. M. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1043 · Cited by 674 · see citing works
Antibody Structure and Function: The Basis for Engineering Therapeutics
Chiu, M. L., Goulet, D. R., Teplyakov, A., & Gilliland, G. L. (2019) · Antibodies · doi:10.3390/antib8040055 · Cited by 646 · see citing works
Efficient evolution of human antibodies from general protein language models
Hie, B., Shanker, V. R., Xu, D., Bruun, T. U. J., Weidenbacher, P. A. B., Tang, S., Wu, W. C. H., Pak, J. E., & Kim, P. S. (2023) · Nature Biotechnology · doi:10.1038/s41587-023-01763-2 · Cited by 444 · see citing works
Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies
Ruffolo, J. A., Chu, L., Mahajan, S. P., & Gray, J. J. (2023) · Nature Communications · doi:10.1038/s41467-023-38063-x · Cited by 339 · see citing works
ImmuneBuilder: Deep-Learning models for predicting the structures of immune proteins
Abanades, B., Wong, W. K., Boyles, F., Georges, G. J., Bujotzek, A., & Deane, C. M. (2023) · Communications Biology · doi:10.1038/s42003-023-04927-7 · Cited by 316 · see citing works
ABodyBuilder: automated antibody structure prediction with data-driven accuracy estimation
Leem, J., Dunbar, J., Georges, G., Shi, J., & Deane, C. M. (2016) · mAbs · doi:10.1080/19420862.2016.1205773 · Cited by 238 · see citing works
Comparative analysis of nanobody sequence and structure data
Mitchell, L. S., & Colwell, L. J. (2018) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.25497 · Cited by 233 · see citing works
Computational approaches to therapeutic antibody design: established methods and emerging trends
Norman, R. A., Ambrosetti, F., Bonvin, A. M. J. J., Colwell, L. J., Kelm, S., Kumar, S., & Krawczyk, K. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbz095 · Cited by 219 · see citing works
“Specific algorithms have been developed for this and incorporated into available software packages such as AbAngle [109].”
BackgroundMethodAntibody structure prediction using interpretable deep learning
Ruffolo, J. A., Sulam, J., & Gray, J. J. (2022) · Patterns · doi:10.1016/j.patter.2021.100406 · Cited by 216 · see citing works
SAbPred: a structure-based antibody prediction server
Dunbar, J., Krawczyk, K., Leem, J., Marks, C., Nowak, J., Regep, C., Georges, G. J., Kelm, S., Popovic, B., & Deane, C. M. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw361 · Cited by 202 · see citing works
Parks, T., Mirabel, M., Kado, J. H., Auckland, K., Nowak, J., Rautanen, A., Mentzer, A. J., Marijon, É., Jouven, X., Perman, M. L., et al. (2017) · Nature Communications · doi:10.1038/ncomms14946 · Cited by 138 · see citing works
Fully automated antibody structure prediction using BIOVIA tools: Validation study
Kemmish, H., Fasnacht, M., & Yan, L. (2017) · PLoS ONE · doi:10.1371/journal.pone.0177923 · Cited by 141 · see citing works
Robin, G., Sato, Y., Desplancq, D., Rochel, N., Weiss, É., & Martineau, P. (2014) · Journal of Molecular Biology · doi:10.1016/j.jmb.2014.08.013 · Cited by 109 · see citing works
Koenig, P., Lee, C. V., Walters, B. T., Janakiraman, V., Stinson, J., Patapoff, T. W., & Fuh, G. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1613231114 · Cited by 107 · see citing works
Dondelinger, M., Filée, P., Sauvage, E., Quinting, B., Muyldermans, S., Galleni, M., & Vandevenne, M. S. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.02278 · Cited by 107 · see citing works
Weitzner, B. D., Kuroda, D., Marze, N. A., Xu, J., & Gray, J. J. (2014) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.24534 · Cited by 97 · see citing works
Krawczyk, K., Baker, T., Shi, J., & Deane, C. M. (2013) · Protein Engineering Design and Selection · doi:10.1093/protein/gzt043 · Cited by 87 · see citing works
Kuroda, D., & Gray, J. J. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw197 · Cited by 81 · see citing works
Antibody humanization by structure-based computational protein design
Choi, Y., Hua, C. K., Sentman, C. L., Ackerman, M. E., & Bailey‐Kellogg, C. (2015) · mAbs · doi:10.1080/19420862.2015.1076600 · Cited by 77 · see citing works
Antibody informatics for drug discovery
Shirai, H., Prades, C., Vita, R., Marcatili, P., Popovic, B., Xu, J., Overington, J. P., Hirayama, K., Soga, S., Tsunoyama, K., et al. (2014) · Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics · doi:10.1016/j.bbapap.2014.07.006 · Cited by 73 · see citing works
Antibody modeling assessment II. Structures and models
Teplyakov, A., Luo, J., Obmolova, G., Malia, T. J., Sweet, R., Stanfield, R. L., Kodangattil, S., Almagro, J. C., & Gilliland, G. L. (2014) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.24554 · Cited by 72 · see citing works
A Review of Deep Learning Methods for Antibodies
Graves, J., Byerly, J., Priego, E., Makkapati, N., Parish, S., Medellin, B. P., & Berrondo, M. (2020) · Antibodies · doi:10.3390/antib9020012 · Cited by 73 · see citing works
In silico methods for design of biological therapeutics
Roy, A., Nair, S. A., Sen, N., Soni, N., & Madhusudhan, M. S. (2017) · Methods · doi:10.1016/j.ymeth.2017.09.008 · Cited by 62 · see citing works
Structural diversity in a human antibody germline library
Teplyakov, A., Obmolova, G., Malia, T., Luo, J., Muzammil, S., Sweet, R. W., Almagro, J. C., & Gilliland, G. L. (2016) · mAbs · doi:10.1080/19420862.2016.1190060 · Cited by 62 · see citing works
Antibody modeling using the Prediction of ImmunoGlobulin Structure (PIGS) web server
Marcatili, P., Olimpieri, P. P., Chailyan, A., & Tramontano, A. L. (2014) · Nature Protocols · doi:10.1038/nprot.2014.189 · Cited by 58 · see citing works
Antibodies exhibit multiple paratope states influencing VH–VL domain orientations
Fernández‐Quintero, M. L., Pomarici, N. D., Math, B. A., Kroell, K. B., Waibl, F., Bujotzek, A., Georges, G. J., & Liedl, K. R. (2020) · Communications Biology · doi:10.1038/s42003-020-01319-z · Cited by 57 · see citing works
Prediction of VH-VL domain orientation for antibody variable domain modeling
Bujotzek, A., Dunbar, J., Lipsmeier, F., Schäfer, W., Antes, I., Deane, C. M., & Georges, G. (2015) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.24756 · Cited by 56 · see citing works
Computational design of antibodies
Fischman, S., & Ofran, Y. (2018) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2018.04.007 · Cited by 56 · see citing works
Challenges in antibody structure prediction
Fernández-Quintero, M. L., Kokot, J., Waibl, F., Fischer, A.-L. M., Quoika, P. K., Deane, C. M., & Liedl, K. R. (2023) · mAbs · doi:10.1080/19420862.2023.2175319 · Cited by 55 · see citing works
Improved prediction of antibody VL–VHorientation
Marze, N. A., Lyskov, S., & Gray, J. J. (2016) · Protein Engineering Design and Selection · doi:10.1093/protein/gzw013 · Cited by 55 · see citing works
Current status and future challenges in T-cell receptor/peptide/MHC molecular dynamics simulations
Knapp, B., Demharter, S., Esmaielbeiki, R., & Deane, C. M. (2015) · Briefings in Bioinformatics · doi:10.1093/bib/bbv005 · Cited by 52 · see citing works
How B-Cell Receptor Repertoire Sequencing Can Be Enriched with Structural Antibody Data
Kovaltsuk, A., Krawczyk, K., Galson, J. D., Kelly, D. F., Deane, C. M., & Trück, J. (2017) · Frontiers in Immunology · doi:10.3389/fimmu.2017.01753 · Cited by 48 · see citing works
Orr, C. M., Fisher, H., Yu, X., Chan, H. T. C., Gao, Y., Duriez, P. J., Booth, S. G., Elliott, I. G., Inzhelevskaya, T., Mockridge, C. I., et al. (2022) · Science Immunology · doi:10.1126/sciimmunol.abm3723 · Cited by 47 · see citing works
Henderson, R. C., Watts, B. E., Ergin, H. N., Anasti, K. M., Parks, R., Xia, S.-M., Trama, A. M., Liao, H., Saunders, K. O., Bonsignori, M., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-08415-7 · Cited by 42 · see citing works
Polonsky, K., Pupko, T., & Freund, N. T. (2023) · The Journal of Immunology · doi:10.4049/jimmunol.2300150 · Cited by 41 · see citing works
Inherent Biophysical Properties Modulate the Toxicity of Soluble Amyloidogenic Light Chains
Maritan, M., Romeo, M., Oberti, L., Sormanni, P., Tasaki, M., Russo, R., Ambrosetti, A., Motta, P., Rognoni, P., Mazzini, G., et al. (2019) · Journal of Molecular Biology · doi:10.1016/j.jmb.2019.12.015 · Cited by 41 · see citing works
VH-VL orientation prediction for antibody humanization candidate selection: A case study
Bujotzek, A., Lipsmeier, F., Harris, S. F., Benz, J., Kuglstatter, A., & Georges, G. J. (2015) · mAbs · doi:10.1080/19420862.2015.1117720 · Cited by 40 · see citing works
Liu, X., Taylor, R. D., Griffin, L., Coker, S.-F., Adams, R., Ceska, T., Shi, J., Lawson, A. D. G., & Baker, T. (2017) · Scientific Reports · doi:10.1038/srep41306 · Cited by 39 · see citing works
ABodyBuilder3: improved and scalable antibody structure predictions
Kenlay, H., Dreyer, F. A., Cutting, D., Nissley, D. A., & Deane, C. M. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae576 · Cited by 39 · see citing works
Quantitative approaches for decoding the specificity of the human T cell repertoire
Ghoreyshi, Z. S., & George, J. T. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1228873 · Cited by 39 · see citing works
Knapp, B., Dunbar, J., & Deane, C. M. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003748 · Cited by 33 · see citing works
VH‐VL interdomain dynamics observed by computer simulations and NMR
Fernández‐Quintero, M. L., Hoerschinger, V. J., Lamp, L. M., Bujotzek, A., Georges, G. J., & Liedl, K. R. (2020) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.25872 · Cited by 32 · see citing works
Biophysical characterization of dynamic structures of immunoglobulin G
Yanaka, S., Yogo, R., & Kato, K. (2020) · Biophysical Reviews · doi:10.1007/s12551-020-00698-1 · Cited by 32 · see citing works
ImmuneBuilder: Deep-Learning models for predicting the structures of immune proteinsPreprint
Abanades, B., Wong, W. K., Boyles, F., Georges, G. J., Bujotzek, A., & Deane, C. M. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.11.04.514231 · Cited by 32 · see citing works
Conformational Ensembles of Antibodies Determine Their Hydrophobicity
Waibl, F., Fernández‐Quintero, M. L., Kamenik, A. S., Kraml, J., Hofer, F., Kettenberger, H., Georges, G. J., & Liedl, K. R. (2020) · Biophysical Journal · doi:10.1016/j.bpj.2020.11.010 · Cited by 31 · see citing works
Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodiesPreprint
Ruffolo, J. A., Chu, L., Mahajan, S. P., & Gray, J. J. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.04.20.488972 · Cited by 33 · see citing works
Ensembles in solution as a new paradigm for antibody structure prediction and design
Fernández‐Quintero, M. L., Georges, G. J., Varga, J. M., & Liedl, K. R. (2021) · mAbs · doi:10.1080/19420862.2021.1923122 · Cited by 30 · see citing works
Dunbar, J., Knapp, B., Fuchs, A., Shi, J., & Deane, C. M. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003852 · Cited by 29 · see citing works
Burkovitz, A., & Ofran, Y. (2015) · mAbs · doi:10.1080/19420862.2015.1123365 · Cited by 29 · see citing works
Germline-Dependent Antibody Paratope States and Pairing Specific VH-VL Interface Dynamics
Fernández‐Quintero, M. L., Kroell, K. B., Bacher, L. M., Loeffler, J. R., Quoika, P. K., Georges, G. J., Bujotzek, A., Kettenberger, H., & Liedl, K. R. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.675655 · Cited by 27 · see citing works
Kizhedath, A., Wilkinson, S. C., & Glassey, J. (2016) · Archives of Toxicology · doi:10.1007/s00204-016-1876-7 · Cited by 27 · see citing works
Computational tools for aiding rational antibody design
Krawczyk, K., Dunbar, J., & Deane, C. M. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-6637-0_21 · Cited by 26 · see citing works
Mutation of Framework Residue H71 Results in Different Antibody Paratope States in Solution
Fernández‐Quintero, M. L., Kroell, K. B., Hofer, F., Riccabona, J. R., & Liedl, K. R. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.630034 · Cited by 26 · see citing works
The therapeutic antibody profiler for computational developability assessment
Raybould, M. I. J., & Deane, C. M. (2022) · Methods in molecular biology · doi:10.1007/978-1-0716-1450-1_5 · Cited by 25 · see citing works
Knapp, B., Dunbar, J., Alcala, M., & Deane, C. M. (2017) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.7b00080 · Cited by 25 · see citing works
Conformational selection of allergen-antibody complexes—surface plasticity of paratopes and epitopes
Fernández‐Quintero, M. L., Loeffler, J. R., Waibl, F., Kamenik, A. S., Hofer, F., & Liedl, K. R. (2019) · Protein Engineering Design and Selection · doi:10.1093/protein/gzaa014 · Cited by 24 · see citing works
Surprisingly Fast Interface and Elbow Angle Dynamics of Antigen-Binding Fragments
Fernández‐Quintero, M. L., Kroell, K. B., Heiss, M. C., Loeffler, J. R., Quoika, P. K., Waibl, F., Bujotzek, A., Moessner, E., Georges, G. J., & Liedl, K. R. (2020) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2020.609088 · Cited by 23 · see citing works
Jaszczyszyn, I., Bielska, W., Gawłowski, T., Dudzic, P., Satława, T., Kończak, J., Wilman, W., Janusz, B., Wróbel, S., Chomicz, D., et al. (2023) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2023.1214424 · Cited by 23 · see citing works
MoFvAb: Modeling the Fv region of antibodies
Bujotzek, A., Fuchs, A., Qu, C., Benz, J., Klostermann, S., Antes, I., & Georges, G. J. (2015) · mAbs · doi:10.1080/19420862.2015.1068492 · Cited by 22 · see citing works
PEP-Patch: Electrostatics in Protein–Protein Recognition, Specificity, and Antibody Developability
Hoerschinger, V. J., Waibl, F., Pomarici, N. D., Loeffler, J. R., Deane, C. M., Georges, G. J., Kettenberger, H., Fernández‐Quintero, M. L., & Liedl, K. R. (2023) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.3c01490 · Cited by 19 · see citing works
Fernández‐Quintero, M. L., Heiss, M. C., & Liedl, K. R. (2019) · Protein Engineering Design and Selection · doi:10.1093/protein/gzaa004 · Cited by 19 · see citing works
Accurate determination of epitope for antibodies with unknown 3D structures
Tahir, S., Bourquard, T., Musnier, A., Jullian, Y., Corde, Y., Omahdi, Z., Mathias, L., Reiter, É., Crépieux, P., Bruneau, G., et al. (2021) · mAbs · doi:10.1080/19420862.2021.1961349 · Cited by 18 · see citing works
Defining and Studying B Cell Receptor and TCR Interactions
Rappazzo, C. G., Fernández‐Quintero, M. L., Mayer, A., Wu, N. C., Greiff, V., & Guthmiller, J. J. (2023) · The Journal of Immunology · doi:10.4049/jimmunol.2300136 · Cited by 18 · see citing works
Structure and Dynamics Guiding Design of Antibody Therapeutics and Vaccines
Fernández‐Quintero, M. L., Pomarici, N. D., Fischer, A.-L. M., Hoerschinger, V. J., Kroell, K. B., Riccabona, J. R., Kamenik, A. S., Loeffler, J. R., Ferguson, J. A., Perrett, H. R., et al. (2023) · Antibodies · doi:10.3390/antib12040067 · Cited by 19 · see citing works
Modelling the assembly and flexibility of antibody structures
Guo, D., Sciscio, M. L. D., Ng, J. C.-F., & Fraternali, F. (2023) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2023.102757 · Cited by 18 · see citing works
Considering B7-CD28 as a family through sequence and structure
West, S. M., & Deng, X. (2019) · Experimental Biology and Medicine · doi:10.1177/1535370219855970 · Cited by 17 · see citing works
Licari, G., Martin, K., Crames, M., Mozdzierz, J., Marlow, M. S., Karow‐Zwick, A. R., Kumar, S., & Bauer, J. (2022) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.2c00838 · Cited by 16 · see citing works
Antibody–antigen complex modelling in the era of immunoglobulin repertoire sequencing
Raybould, M. I. J., Wong, W. K., & Deane, C. M. (2019) · Molecular Systems Design & Engineering · doi:10.1039/c9me00034h · Cited by 14 · see citing works
Dudzic, P., Chomicz, D., Bielska, W., Jaszczyszyn, I., Zieliński, M., Janusz, B., Wróbel, S., Pannérer, M.-M. L., Phillips, A., Prabakaran, P., et al. (2025) · Communications Biology · doi:10.1038/s42003-025-08388-y · Cited by 15 · see citing works
High-Throughput Antibody Structure Modeling and Design Using ABodyBuilder
Leem, J., & Deane, C. M. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-8736-8_21 · Cited by 15 · see citing works
Non-covalent Fc-Fab interactions significantly alter internal dynamics of an IgG1 antibody
Natesan, R., & Agrawal, N. J. (2022) · Scientific Reports · doi:10.1038/s41598-022-13370-3 · Cited by 15 · see citing works
Tulika, T., Pedersen, R. W., Rimbault, C., Ahmadi, S., Rivera‐de‐Torre, E., Fernández‐Quintero, M. L., Loeffler, J. R., Bohn, M., Ljungars, A., Ledsgaard, L., et al. (2023) · Protein Science · doi:10.1002/pro.4821 · Cited by 11 · see citing works
Sheng, Z., Bimela, J. S., Katsamba, P. S., Patel, S. D., Guo, Y., Zhao, H., Guo, Y., Kwong, P. D., & Shapiro, L. S. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2021.811632 · Cited by 13 · see citing works
Fernández‐Quintero, M. L., Kroell, K. B., Grunewald, L., Fischer, A.-L. M., Riccabona, J. R., & Liedl, K. R. (2022) · mAbs · doi:10.1080/19420862.2021.2024118 · Cited by 13 · see citing works
Common framework mutations impact antibody interfacial dynamics and flexibility
Rhodes, E. R., Faris, J. G., Petersen, B. M., & Sprenger, K. G. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1120582 · Cited by 11 · see citing works
Hoffmann, T., Marion, A., & Antes, I. (2017) · BMC Structural Biology · doi:10.1186/s12900-016-0071-7 · Cited by 11 · see citing works
Hoffmann, T., Krackhardt, A. M., & Antes, I. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004244 · Cited by 11 · see citing works
AbLEF: antibody language ensemble fusion for thermodynamically empowered property predictions
Rollins, Z. A., Widatalla, T., Waight, A. B., Cheng, A. C., & Metwally, E. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae268 · Cited by 10 · see citing works
AbMelt: Learning antibody thermostability from molecular dynamics
Rollins, Z. A., Widatalla, T., Cheng, A. C., & Metwally, E. (2024) · Biophysical Journal · doi:10.1016/j.bpj.2024.06.003 · Cited by 9 · see citing works
Peplau, E., Rose, F. D., Eichinger, A., Reder, S., Mittelhäuser, M., Scafetta, G., Schwaiger, M., Weber, W., Bartolazzi, A., D’Alessandria, C., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-86641-0 · Cited by 10 · see citing works
Crystal structures of the human IgD Fab reveal insights into CH1 domain diversity
Davies, A. M., Beavil, R. L., Barbolov, M., Sandhar, B. S., Gould, H. J., Beavil, A. J., Sutton, B. J., & McDonnell, J. M. (2023) · Molecular Immunology · doi:10.1016/j.molimm.2023.05.006 · Cited by 9 · see citing works
Benchmarking TriadAb using targets from the second antibody modeling assessment
Lee, F. S., Anderson, A. G., & Olafson, B. D. (2023) · Protein Engineering Design and Selection · doi:10.1093/protein/gzad013 · Cited by 8 · see citing works
Xing, C., Li, G., Zheng, X., Li, P., Yuan, J. L., & Yan, W. (2024) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.4c00736 · Cited by 8 · see citing works
Structural mechanism of Fab domain dissociation as a measure of interface stability
Pomarici, N. D., Waibl, F., Quoika, P. K., Bujotzek, A., Georges, G. J., Fernández‐Quintero, M. L., & Liedl, K. R. (2023) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-023-00501-9 · Cited by 8 · see citing works
Quantitative Description of Surface Complementarity of Antibody-Antigen Interfaces
Rienzo, L. D., Milanetti, E., Ruocco, G., & Lepore, R. (2021) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2021.749784 · Cited by 8 · see citing works
ASAP-SML: An antibody sequence analysis pipeline using statistical testing and machine learning
Li, X., Deventer, J. A. V., & Hassoun, S. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007779 · Cited by 9 · see citing works
SAAINT-DB: a comprehensive structural antibody database for antibody modeling and design
Huang, X., Zhou, J., Chen, S., Xia, X., Chen, Y. E., & Xu, J. (2025) · Acta Pharmacologica Sinica · doi:10.1038/s41401-025-01608-5 · Cited by 8 · see citing works
Cisneros, A., Nargi, R. S., Parrish, E. H., Haliburton, C. M., Meiler, J., & Crowe, J. E. (2019) · Molecular Systems Design & Engineering · doi:10.1039/c8me00080h · Cited by 7 · see citing works
Insights into Comparative Modeling of VHH Domains
Vattekatte, A. M., Cadet, F., Gelly, J., & de Brevern, A. G. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22189771 · Cited by 7 · see citing works
Comparing Antibody Interfaces to Inform Rational Design of New Antibody Formats
Fernández‐Quintero, M. L., Quoika, P. K., Wedl, F. S., Seidler, C. A., Kroell, K. B., Loeffler, J. R., Pomarici, N. D., Hoerschinger, V. J., Bujotzek, A., Georges, G. J., et al. (2022) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2022.812750 · Cited by 8 · see citing works
Bispecific antibodies—effects of point mutations on CH3-CH3 interface stability
Pomarici, N. D., Fernández‐Quintero, M. L., Quoika, P. K., Waibl, F., Bujotzek, A., Georges, G. J., & Liedl, K. R. (2022) · Protein Engineering Design and Selection · doi:10.1093/protein/gzac012 · Cited by 6 · see citing works
Sangha, A. K., Dong, J., Williamson, L. E., Hashiguchi, T., Saphire, E. O., Crowe, J. E., & Meiler, J. (2017) · Structure · doi:10.1016/j.str.2017.10.005 · Cited by 6 · see citing works
McConnell, S. A., & Casadevall, A. (2024) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2024.107397 · Cited by 5 · see citing works
Homology Modeling of Antibody Variable Regions: Methods and Applications
Bansia, H., & Ramakumar, S. (2023) · Methods in molecular biology · doi:10.1007/978-1-0716-2974-1_16 · Cited by 5 · see citing works
Sheng, Z., Bimela, J. S., Wang, M., Li, Z., Guo, Y., & Ho, D. D. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1190416 · Cited by 5 · see citing works
OCD.py - Characterizing immunoglobulin inter-domain orientationsPreprint
Hoerschinger, V. J., Fernández‐Quintero, M. L., Waibl, F., Kraml, J., Bujotzek, A., Georges, G. J., & Liedl, K. R. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.15.435379 · Cited by 5 · see citing works
Cagiada, M., Spoendlin, F. C., Ifashe, K., & Deane, C. M. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.11.10.687725 · Cited by 5 · see citing works
Unlocking the potential of in silico approach in designing antibodies against SARS-CoV-2
Subramaniam, T. R., Mualif, S. A., Chan, W. H., & Halim, K. B. A. (2025) · Frontiers in Bioinformatics · doi:10.3389/fbinf.2025.1533983 · Cited by 4 · see citing works
Conformation-aware structure prediction of antigen-recognizing immune proteins
Dreyer, F. A., Ludwiczak, J., Martinkus, K., Abanades, B., Alberstein, R. G., Kessel, P., Rao, P., Lee, J. H., Bonneau, R., Watkins, A. M., et al. (2025) · mAbs · doi:10.1080/19420862.2025.2602217 · Cited by 4 · see citing works
Cross‐linking disulfide bonds govern solution structures of diabodies
Math, B. A., Waibl, F., Lamp, L. M., Fernández‐Quintero, M. L., & Liedl, K. R. (2023) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.26509 · Cited by 4 · see citing works
- Authors
- Dunbar, J., Fuchs, A., Shi, J., & Deane, C. M.
- Affiliations
- University of Oxford (GB)
- UCB Pharma (United Kingdom) (GB)
- ORCID
- Venue
- Protein Engineering Design and Selection
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-05-24
- Volume
- 26
- Issue
- 10
- Pages
- 611-620
- ISSN
- 0269-2139 (ISSN-L)
- 1741-0126
- 1741-0134
- OpenAlex
- W2154135618
- Cited by
- 125
- References
- 40
- Citations by year
- 2026: 5 · 2025: 11 · 2024: 6 · 2023: 22 · 2022: 11 · 2021: 12 · 2020: 8 · 2019: 11 · 2018: 7 · 2017: 9 · 2016: 7 · 2015: 7 · 2014: 7 · 2013: 2
- FWCI
- 3.43
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Protein Engineering Design and Selection (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Engineering and Physical Sciences Research Council
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Monoclonal and Polyclonal Antibodies Research
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Keywords
- antibody structure, Fab fragment, antibody binding sites, structural clusters, antibody flexibility, antibody engineering
- MeSH terms
- Animals, Antibodies, Haptens, Humans, Immunoglobulin Variable Region, Immunoglobulin Light Chains, Models, Molecular, Protein Conformation, Consensus Sequence, Computational Biology, Mice, Rats
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
