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Shape complementarity and hydrogen bond preferences in protein–protein interfaces: implications for antibody modeling and protein–protein docking

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Sampling and scoring: A marriage made in heaven

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Natural and man-made V-gene repertoires for antibody discovery

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Location and length distribution of somatic hypermutation-associated DNA insertions and deletions reveals regions of antibody structural plasticity

Briney, B. S., Willis, J. R., & Crowe, J. E. (2012) · Genes and Immunity · doi:10.1038/gene.2012.28 · Cited by 75 · see citing works

Computational design of a symmetric homodimer using β-strand assembly

Stranges, P. B., Machius, M., Miley, M. J., Tripathy, A., & Kuhlman, B. A. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1115124108 · Cited by 70 · see citing works

Engineering a protein–protein interface using a computationally designed library

Guntas, G., Purbeck, C., & Kuhlman, B. A. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1006528107 · Cited by 67 · see citing works

What Makes Ras an Efficient Molecular Switch: A Computational, Biophysical, and Structural Study of Ras-GDP Interactions with Mutants of Raf

Filchtinski, D., Sharabi, O., Rueppel, A., Vetter, I. R., Herrmann, C., & Shifman, J. M. (2010) · Journal of Molecular Biology · doi:10.1016/j.jmb.2010.03.046 · Cited by 66 · see citing works

SIDEpro: A novel machine learning approach for the fast and accurate prediction of side‐chain conformations

Nagata, K., Randall, A. Z., & Baldi, P. (2011) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.23170 · Cited by 66 · see citing works

RASP: rapid modeling of protein side chain conformations

Miao, Z., Cao, Y., & Jiang, T. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr538 · Cited by 59 · see citing works

Thermodynamics of antibody–antigen interaction revealed by mutation analysis of antibody variable regions

Akiba, H., & Tsumoto, K. (2015) · The Journal of Biochemistry · doi:10.1093/jb/mvv049 · Cited by 57 · see citing works

Fast and accurate prediction of protein side-chain conformations

Liang, S., Zheng, D., Zhang, C., & Standley, D. M. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr482 · Cited by 57 · see citing works

Systematic classification of CDR‐L3 in antibodies: Implications of the light chain subtypes and the VL–VH interface

Kuroda, D., Shirai, H., Kobori, M., & Nakamura, H. (2008) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22230 · Cited by 56 · see citing works

Blind prediction of interfacial water positions in CAPRI

Lensink, M. F., Moal, I. H., Bates, P. A., Kastritis, P. L., Melquiond, A. S. J., Karaca, E., Schmitz, C., van Dijk, M., Bonvin, A. M. J. J., Eisenstein, M., et al. (2013) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.24439 · Cited by 54 · see citing works

Redesigning an Antibody Fragment for Faster Association with Its Antigen

Marvin, J. S., & Lowman, H. B. (2003) · Biochemistry · doi:10.1021/bi026947q · Cited by 52 · see citing works

Animal‐friendly affinity reagents: replacing the needless in the haystack

Gray, A. C., Sidhu, S. S., Chandrasekera, P. C., Hendriksen, C. F. M., & Borrebaeck, C. A. K. (2016) · Trends in Biotechnology · doi:10.1016/j.tibtech.2016.05.017 · Cited by 52 · see citing works

An integrated approach to extreme thermostabilization and affinity maturation of an antibody

McConnell, A. D., Spasojevich, V., Macomber, J. L., Krapf, I. P., Chen, A., Sheffer, J. C., Berkebile, A. D., Horlick, R. A., Neben, S., King, D. J., et al. (2012) · Protein Engineering Design and Selection · doi:10.1093/protein/gzs090 · Cited by 51 · see citing works

Improving the species cross-reactivity of an antibody using computational design

Farady, C. J., Sellers, B. D., Jacobson, M. P., & Craik, C. S. (2009) · Bioorganic & Medicinal Chemistry Letters · doi:10.1016/j.bmcl.2009.05.005 · Cited by 50 · see citing works

Computational Design of the Sequence and Structure of a Protein-Binding Peptide

Sammond, D. W., Bosch, D. E., Butterfoss, G. L., Purbeck, C., Machius, M., Siderovski, D. P., & Kuhlman, B. A. (2011) · Journal of the American Chemical Society · doi:10.1021/ja110296z · Cited by 48 · see citing works

Large‐scale analysis of somatic hypermutations in antibodies reveals which structural regions, positions and amino acids are modified to improve affinity

Burkovitz, A., Sela‐Culang, I., & Ofran, Y. (2013) · FEBS Journal · doi:10.1111/febs.12597 · Cited by 48 · see citing works

Effects of somatic mutations on CDR loop flexibility during affinity maturation

Wong, S., Sellers, B. D., & Jacobson, M. P. (2010) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22920 · Cited by 47 · see citing works

Rigidity Emerges during Antibody Evolution in Three Distinct Antibody Systems: Evidence from QSFR Analysis of Fab Fragments

Li, T., Tracka, M. B., Uddin, S., Casas‐Finet, J. R., Jacobs, D. J., & Livesay, D. R. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004327 · Cited by 46 · see citing works

A Role of the Third Complementarity-determining Region in the Affinity Maturation of an Antibody

Furukawa, K., Shirai, H., Azuma, T., & Nakamura, H. (2001) · Journal of Biological Chemistry · doi:10.1074/jbc.m102714200 · Cited by 45 · see citing works

Flexible Backbone Sampling Methods to Model and Design Protein Alternative Conformations

Ollikainen, N., Smith, C. A., Fraser, J. S., & Kortemme, T. (2013) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/b978-0-12-394292-0.00004-7 · Cited by 44 · see citing works

The Iterative Protein Redesign and Optimization (IPRO) suite of programs

Pantazes, R. J., Grisewood, M. J., Li, T., Gifford, N. P., & Maranas, C. D. (2014) · Journal of Computational Chemistry · doi:10.1002/jcc.23796 · Cited by 40 · see citing works

Genome-wide prediction and validation of peptides that bind human prosurvival Bcl-2 proteins

DeBartolo, J., Taipale, M., & Keating, A. E. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003693 · Cited by 39 · see citing works

Tabhu: tools for antibody humanization

Olimpieri, P. P., Marcatili, P., & Tramontano, A. L. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu667 · Cited by 38 · see citing works

Improving the affinity of an antibody for its antigen via long-range electrostatic interactions

Fukunaga, A., & Tsumoto, K. (2013) · Protein Engineering Design and Selection · doi:10.1093/protein/gzt053 · Cited by 36 · see citing works

Computational de novo design of antibodies binding to a peptide with high affinity

Poosarla, V. G., Li, T., Goh, B. C., Schulten, K. J., Wood, T. K., & Maranas, C. D. (2017) · Biotechnology and Bioengineering · doi:10.1002/bit.26244 · Cited by 35 · see citing works

De novo design of antibody complementarity determining regions binding a FLAG tetra-peptide

Entzminger, K. C., Hyun, J., Pantazes, R. J., Patterson-Orazem, A. C., Qerqez, A. N., Frye, Z., Hughes, R. A., Ellington, A. D., Lieberman, R. L., Maranas, C. D., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-10737-9 · Cited by 35 · see citing works

The PyRosetta Toolkit: A Graphical User Interface for the Rosetta Software Suite

Adolf‐Bryfogle, J., & Dunbrack, R. L. (2013) · PLoS ONE · doi:10.1371/journal.pone.0066856 · Cited by 34 · see citing works

Antibody humanization by molecular dynamics simulations—in‐silico guided selection of critical backmutations

Margreitter, C., Mayrhofer, P., Kunert, R., & Oostenbrink, C. (2016) · Journal of Molecular Recognition · doi:10.1002/jmr.2527 · Cited by 34 · see citing works

Redesigned HIV antibodies exhibit enhanced neutralizing potency and breadth

Willis, J. R., Sapparapu, G., Murrell, S., Julien, J., Singh, V., King, H. G., Xia, Y., Pickens, J. A., LaBranche, C. C., Slaughter, J. C., et al. (2015) · Journal of Clinical Investigation · doi:10.1172/jci80693 · Cited by 32 · see citing works

A Novel Antibody Humanization Method Based on Epitopes Scanning and Molecular Dynamics Simulation

Zhang, D., Chen, C., Zhao, B., Gong, L., Jin, W.-J., Liu, J., Wang, J., Wang, T., Yuan, X., & He, Y.-W. (2013) · PLoS ONE · doi:10.1371/journal.pone.0080636 · Cited by 30 · see citing works

Maximum-Entropy Models of Sequenced Immune Repertoires Predict Antigen-Antibody Affinity

Asti, L., Uguzzoni, G., Marcatili, P., & Pagnani, A. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004870 · Cited by 30 · see citing works

Assessment of flexible backbone protein design methods for sequence library prediction in the therapeutic antibody Herceptin–HER2 interface

Babor, M., Mandell, D. J., & Kortemme, T. (2011) · Protein Science · doi:10.1002/pro.632 · Cited by 29 · see citing works

Assessment of Solvated Interaction Energy Function for Ranking Antibody–Antigen Binding Affinities

Sulea, T. I., Vivcharuk, V., Corbeil, C. R., Deprez, C., & Purisima, E. O. (2016) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.6b00043 · Cited by 29 · 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

Antibody humanization by redesign of complementarity-determining region residues proximate to the acceptor framework

Hanf, K. J. M., Arndt, J. W., Chen, L. L., Jarpe, M. B., Boriack‐Sjodin, P. A., Li, Y., van Vlijmen, H., Pepinsky, R. B., Simon, K. J., & Lugovskoy, A. A. (2013) · Methods · doi:10.1016/j.ymeth.2013.06.024 · Cited by 25 · see citing works

Development of scoring functions for antibody sequence assessment and optimization

Seeliger, D. (2013) · PLoS ONE · doi:10.1371/journal.pone.0076909 · Cited by 24 · see citing works

The Protein-Protein Interface Evolution Acts in a Similar Way to Antibody Affinity Maturation

Li, B., Zhao, L., Wang, C., Guo, H., Wu, L., Zhang, X., Qian, W., Wang, H., & Guo, Y. (2009) · Journal of Biological Chemistry · doi:10.1074/jbc.m109.076547 · Cited by 23 · see citing works

Computationally driven antibody engineering enables simultaneous humanization and thermostabilization

Choi, Y., Ndong, C., Griswold, K. E., & Bailey‐Kellogg, C. (2016) · Protein Engineering Design and Selection · doi:10.1093/protein/gzw024 · Cited by 20 · see citing works

Canonical structures of short CDR‐L3 in antibodies

Teplyakov, A., & Gilliland, G. L. (2014) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.24559 · Cited by 19 · see citing works

Elucidation of potential sites for antibody engineering by fluctuation editing

Yanaka, S., Moriwaki, Y., Tsumoto, K., & Sugase, K. (2017) · Scientific Reports · doi:10.1038/s41598-017-10246-9 · Cited by 19 · see citing works

Amino-acid site variability among natural and designed proteins

Jackson, E. L., Ollikainen, N., Covert, A. W., Kortemme, T., & Wilke, C. O. (2013) · PeerJ · doi:10.7717/peerj.211 · Cited by 15 · see citing works

Enhancement of canonical sampling by virtual-state transitions

Higo, J., Kasahara, K., Dasgupta, B., & Nakamura, H. (2017) · The Journal of Chemical Physics · doi:10.1063/1.4974087 · Cited by 14 · see citing works

Repertoire sequencing and the statistical ensemble approach to adaptive immunity

Callan, C. G., Mora, T., & Walczak, A. M. (2016) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2016.12.014 · Cited by 9 · see citing works

Engineering Protein Therapeutics: Predictive Performances of a Structure-Based Virtual Affinity Maturation Protocol

Oberlin, M., Kroemer, R. T., Mikol, V., Minoux, H., Tastan, E., & Baurin, N. (2012) · Journal of Chemical Information and Modeling · doi:10.1021/ci3001474 · Cited by 8 · see citing works

Table_of_Contents

(2013) · Toxicological Sciences · doi:10.1093/toxsci/kft065 · Cited by 1 · 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

Current Advancements in Addressing Key Challenges of Therapeutic Antibody Design, Manufacture, and Formulation

Sifniotis, V., Cruz, E., Eroglu, B., & Kayser, V. (2019) · Antibodies · doi:10.3390/antib8020036 · Cited by 99 · see citing works

T-Cell Engagers in Solid Cancers—Current Landscape and Future Directions

Shanshal, M., Caimi, P. F., Adjei, A. A., & Ma, W. W. (2023) · Cancers · doi:10.3390/cancers15102824 · Cited by 73 · see citing works

Discovery-stage identification of drug-like antibodies using emerging experimental and computational methods

Makowski, E. K., Wu, L., Gupta, P., & Tessier, P. M. (2021) · mAbs · doi:10.1080/19420862.2021.1895540 · Cited by 60 · see citing works

Engineering Stability, Viscosity, and Immunogenicity of Antibodies by Computational Design

Kuroda, D., & Tsumoto, K. (2020) · Journal of Pharmaceutical Sciences · doi:10.1016/j.xphs.2020.01.011 · Cited by 58 · see citing works

Delicate balance among thermal stability, binding affinity, and conformational space explored by single-domain VHH antibodies

Ikeuchi, E., Kuroda, D., Nakakido, M., Murakami, A., & Tsumoto, K. (2021) · Scientific Reports · doi:10.1038/s41598-021-98977-8 · Cited by 32 · see citing works

Affinity maturation of antibodies by combinatorial codon mutagenesis versus error-prone PCR

Simons, J. F., Lim, Y. W., Carter, K. P., Wagner, E. K., Wayham, N. P., Adler, A. S., & Johnson, D. S. (2020) · mAbs · doi:10.1080/19420862.2020.1803646 · Cited by 30 · see citing works

Accelerating antibody discovery and optimization with high-throughput experimentation and machine learning

Matsunaga, R., & Tsumoto, K. (2025) · Journal of Biomedical Science · doi:10.1186/s12929-025-01141-x · Cited by 30 · see citing works

Progress toward improved understanding of antibody maturation

Vajda, S., Porter, K. A., & Kozakov, D. (2021) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2020.11.008 · Cited by 25 · see citing works

High-throughput analysis system of interaction kinetics for data-driven antibody design

Matsunaga, R., Ujiie, K., Inagaki, M., Pérez, J. F., Yasuda, Y., Mimasu, S., Soga, S., & Tsumoto, K. (2023) · Scientific Reports · doi:10.1038/s41598-023-46756-y · Cited by 23 · see citing works

Integrating Computational Design and Experimental Approaches for Next-Generation Biologics

Son, A., Park, J., Kim, W., Lee, W., Yoon, Y., Ji, J., & Kim, H. (2024) · Biomolecules · doi:10.3390/biom14091073 · Cited by 29 · see citing works

Development of a potent high-affinity human therapeutic antibody via novel application of recombination signal sequence–based affinity maturation

Kielczewska, A., D’Angelo, I., Amador, M. S., Wang, T., Sudom, A. M., Min, X., Rathanaswami, P., Pigott, C. R., & Foltz, I. N. (2021) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2021.101533 · Cited by 11 · see citing works

FASTIA : A rapid and accessible platform for protein variant interaction analysis demonstrated with a single‐domain antibody

Matsunaga, R., & Tsumoto, K. (2025) · Protein Science · doi:10.1002/pro.70065 · 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

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

Effects of a remote mutation from the contact paratope on the structure of CDR-H3 in the anti-HIV neutralizing antibody PG16

KONDO, H. X., Kiribayashi, R., Kuroda, D., Kohda, J., Kugimiya, A., Nakano, Y., Tsumoto, K., & Takano, Y. (2019) · Scientific Reports · doi:10.1038/s41598-019-56154-y · Cited by 8 · see citing works

Anion solvation enhanced by positive supercharging mutations preserves thermal stability of an antibody in a wide pH range

Kasahara, K., Kuroda, D., Tanabe, A., Kawade, R., Nagatoishi, S., & Tsumoto, K. (2021) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2021.05.053 · Cited by 8 · see citing works

Structure-based design and discovery of novel anti-tissue factor antibodies with cooperative double-point mutations, using interaction analysis

Chiba, S., Tanabe, A., Nakakido, M., Okuno, Y., Tsumoto, K., & Ohta, M. (2020) · Scientific Reports · doi:10.1038/s41598-020-74545-4 · Cited by 8 · see citing works

Computational and Rational Design of Single-Chain Antibody against Tick-Borne Encephalitis Virus for Modifying Its Specificity

Константинович, Б. И., Desyukevich, P., Mikhaylova, E. E., Kurchenko, O. M., & Викторовна, Т. Н. (2021) · Viruses · doi:10.3390/v13081494 · Cited by 6 · see citing works

Computational approaches for drug discovery against COVID-19

Sharma, P., Joshi, T., Mathpal, S., Tamta, S., & Chandra, S. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-91794-0.00024-x · Cited by 4 · see citing works

Impact of single-residue mutations on protein thermal stability: The case of threonine 83 of BC2L-CN lectin

Hoya, M., Matsunaga, R., Nagatoishi, S., Ide, T., Kuroda, D., & Tsumoto, K. (2024) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2024.132682 · Cited by 4 · see citing works

Navigating the landscape: A comprehensive overview of computational approaches in therapeutic antibody design and analysis

Yadav, A. J., Bhagat, K., Sharma, A., & Padhi, A. K. (2025) · Advances in protein chemistry and structural biology · doi:10.1016/bs.apcsb.2024.10.011 · Cited by 3 · see citing works

Optimizing the breadth of SARS-CoV-2-neutralizing antibodies in vivo and in silico

Kuroda, D., Moriyama, S., Sasaki, H., & Takahashi, Y. (2025) · Human Vaccines & Immunotherapeutics · doi:10.1080/21645515.2025.2526873 · Cited by 3 · see citing works

Unveiling the affinity–stability relationship in anti-measles virus antibodies: a computational approach for hotspots prediction

Paul, R., Kasahara, K., Sasaki, J., Pérez, J. F., Matsunaga, R., Hashiguchi, T., Kuroda, D., & Tsumoto, K. (2024) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2023.1302737 · Cited by 3 · see citing works

Affinity maturation of TCR-like antibodies using phage display guided by structural modeling

Frick, R., Høydahl, L. S., Hodnebrug, I., Vik, E. S., Dalhus, B., Sollid, L. M., Gray, J. J., Sandlie, I., & Løset, G. Å. (2022) · Protein Engineering Design and Selection · doi:10.1093/protein/gzac005 · Cited by 4 · see citing works

Monoclonal Antibody-Directed Therapy

Kayser, V., & Datta‐Mannan, A. (2022) · MDPI eBooks · doi:10.3390/books978-3-0365-2872-4 · Cited by 1 · see citing works

Computational design of antibody-affinity improvement beyond in vivo maturation

Lippow, S. M., Wittrup, K. D., & Tidor, B. (2007) · Nature Biotechnology · doi:10.1038/nbt1336 · Cited by 342 · see citing works

Structural Considerations in Affinity Maturation of Antibody-Based Biotherapeutic Candidates

Comeau, S. R., Thorsteinson, N., & Kumar, S. (2022) · Methods in molecular biology · doi:10.1007/978-1-0716-2609-2_17 · Cited by 3 · see citing works

Development and experimental validation of computational methods for human antibody affinity enhancement

Li, J., Liao, L., Zhang, C., Huang, K., Zhang, P., Zhang, J. Z. H., Wan, X., & Zhang, H. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae488 · Cited by 13 · see citing works

OrthoRep-driven rapid evolution of antibody fragments

Yu, Y. (2026) · eScholarship (California Digital Library)

Experimentally guided computational antibody affinity maturation with de novo docking, modelling and rational design

Cannon, D. A., Shan, L., Du, Q., Shirinian, L., Rickert, K. W., Rosenthal, K. L., Korade, M., van Vlerken-Ysla, L. E., Buchanan, A. G., Vaughan, T. J., et al. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006980 · Cited by 54 · see citing works