Antibody–drug conjugates (ADCs) combine the high specificity of antibodies with cytotoxic payloads. However, the present strategies for the synthesis of ADCs either yield unstable or heterogeneous products or involve complex processes. Here, we report a computational approach that leverages molecular docking and molecular dynamics simulations to design ADCs that self-assemble through the non-covalent binding of the antibody to a payload that we designed to act as an affinity ligand for specific conserved amino acid residues in the antibody. This method does not require modifications to the antibody structure and yields homogenous ADCs that form in less than 8 min. We show that two conjugates, which consist of hydrophilic and hydrophobic payloads conjugated to two different antibodies, retain the structure and binding properties of the antibody and its biological specificity, are stable in plasma and improve anti-tumour efficacy in mice with non-small cell lung tumour xenografts. The relative simplicity of the approach may facilitate the production of ADCs for the targeted delivery of cytotoxic payloads.
This is a preview of subscription content, access via your institution
Open Access articles citing this article.
Nature Communications Open Access 02 October 2020
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$99.00 per year
only $8.25 per issue
Rent or buy this article
Prices vary by article type
Prices may be subject to local taxes which are calculated during checkout
The main data supporting the results in this study are available within the paper and its Supplementary Information. The raw and analysed datasets generated during the study are available from the corresponding authors on reasonable request.
Beck, A. et al. Strategies and challenges for the next generation of antibody drug conjugates. Nat. Rev. Drug Discov. 16, 315–337 (2017).
Gordon, M. R. et al. Field guide to challenges and opportunities in antibody-drug conjugates for chemists. Bioconjug. Chem. 26, 2198–2215 (2015).
Axup, J. Y. et al. Synthesis of site-specific antibody-drug conjugates using unnatural amino acids. Proc. Natl Acad. Sci. USA 109, 16101–16106 (2012).
Junutula, J. R. et al. Site-specific conjugation of a cytotoxic drug to an antibody improves the therapeutic index. Nat. Biotechnol. 26, 925–932 (2008).
Jeger, S. et al. Site-specific and stoichiometric modification of antibodies by bacterial transglutaminase. Angew. Chemie Int. Ed. 49, 9995–9997 (2010).
Badescu, G. et al. Bridging disulfides for stable and defined antibody drug conjugates. Bioconjug. Chem. 25, 1124–1136 (2014).
Lyon, R. P. et al. Self-hydrolyzing maleimides improve the stability and pharmacological properties of antibody–drug conjugates. Nat. Biotechnol. 32, 1059–1062 (2014).
Hui, J. Z. & Tsourkas, A. Optimization of photoactive protein Z for fast and efficient site-specific conjugation of native IgG. Bioconjug. Chem. 25, 1709–1719 (2014).
Jain, N., Smith, S. W., Ghone, S. & Tomczuk, B. Current ADC linker chemistry. Pharm. Res. 32, 3526–3540 (2015).
Li, R., Dowd, V., Stewart, D. J., Burton, S. J. & Lowe, C. R. Design, synthesis, and application of a protein A mimetic. Nat. Biotechnol. 16, 190–195 (1998).
Arakawa, T., Tsumoto, K. & Ejima, D. Alternative downstream processes for production of antibodies and antibody fragments. Biochim. Biophys. Acta 1844, 2032–2040 (2014).
Lyon, R. P. et al. Reducing hydrophobicity of homogeneous antibody–drug conjugates improves pharmacokinetics and therapeutic index. Nat. Biotechnol. 33, 733–735 (2015).
Zhang, L. & Sun, Y. Effect of ligand chain length on hydrophobic charge induction chromatography revealed by molecular dynamics simulations. Front. Chem. Sci. Eng. 7, 456–463 (2013).
Ducry, L. & Stump, B. Antibody-drug conjugates: linking cytotoxic payloads to monoclonal antibodies. Bioconjug. Chem. 21, 5–13 (2010).
Lund, L. N. et al. Novel peptide ligand with high binding capacity for antibody purification. J. Chromatogr. A 1225, 158–167 (2012).
Kabsch, W. & Sander, C. Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers 22, 2577–2637 (1983).
Lin, D., Tong, H., Wang, H. & Yao, S. Molecular insight into the ligand–IgG interactions for 4-mercaptoethyl-pyridine based hydrophobic charge-induction chromatography. J. Phys. Chem. B 116, 1393–1400 (2012).
Bak, H. & Thomas, O. R. T. Evaluation of commercial chromatographic adsorbents for the direct capture of polyclonal rabbit antibodies from clarified antiserum. J. Chromatogr. B 848, 116–130 (2007).
Bronowska, A. in Thermodynamics—Interaction Studies—Solids, Liquids and Gases (InTech, 2011).
Cheng, F., Li, M. M.-Y., Wang, H.-Q. H., Lin, D.-Q. & Qu, J. J.-P. Antibody–ligand interactions for hydrophobic charge-induction chromatography: a surface plasmon resonance study. Langmuir 31, 3422–3430 (2015).
Hamblett, K. J. et al. Effects of drug loading on the antitumour activity of a monoclonal antibody drug conjugate. Clin. Cancer Res. 10, 7063–7070 (2004).
Yuan, X.-M., Lin, D.-Q., Zhang, Q.-L., Gao, D. & Yao, S.-J. A microcalorimetric study of molecular interactions between immunoglobulin G and hydrophobic charge-induction ligand. J. Chromatogr. A 1443, 145–151 (2016).
Storniolo, A. M., Allerheiligen, S. R. & Pearce, H. L. Preclinical, pharmacologic, and phase I studies of gemcitabine. Semin. Oncol. 24, S7-2–S7-7 (1997).
Senter, P. D. & Sievers, E. L. The discovery and development of brentuximab vedotin for use in relapsed Hodgkin lymphoma and systemic anaplastic large cell lymphoma. Nat. Biotechnol. 30, 631–637 (2012).
Strop., P. et al. Site-specific conjugation improves therapeutic index of antibody drug conjugates with high drug loading. Nat. Biotechnol. 33, 694–696 (2015).
Kruljec, N. & Bratkovič, T. Alternative affinity ligands for immunoglobulins. Bioconjug. Chem. 28, 2009–2030 (2017).
Yang, H. et al. Binding site on human immunoglobulin G for the affinity ligand HWRGWV. J. Mol. Recognit. 23, 271–282 (2009).
DeLano, W. L., Ultsch, M. H., de Vos, A. M. & Wells, J. A. Convergent solutions to binding at a protein-protein interface. Science 287, 1279–1283 (2000).
Frisch, M. J. et al. Gaussian 09, Revision A. 02 https://gaussian.com/ (Gaussian Inc, 2009).
Becke, A. D. Density‐functional thermochemistry III: the role of exact exchange. J. Chem. Phys. 98, 5648–5652 (1993).
Vosko, S. H., Wilk, L. & Nusair, M. Accurate spin-dependent electron liquid correlation energies for local spin density calculations: a critical analysis. Can. J. Phys. 58, 1200–1211 (1980).
Francl, M. M. et al. Self‐consistent molecular orbital methods XXIII: a polarization‐type basis set for second‐row elements. J. Chem. Phys. 77, 3654–3665 (1982).
Binning, R. C. & Curtiss, L. A. Compact contracted basis sets for third-row atoms: Ga-Kr. J. Comput. Chem. 11, 1206–1216 (1990).
Vanommeslaeghe, K. et al. CHARMM general force field: a force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields. J. Comput. Chem. 31, 671–690 (2009).
Singh, U. C. & Kollman, P. A. An approach to computing electrostatic charges for molecules. J. Comput. Chem. 5, 129–145 (1984).
Hess, B., Kutzner, C., van der Spoel, D. & Lindahl, E. GROMACS 4: algorithms for highly efficient, load-balanced, and scalable molecular simulation. J. Chem. Theory Comput. 4, 435–447 (2008).
Deisenhofer, J. Crystallographic refinement and atomic models of a human Fc fragment and its complex with fragment B of protein A from Staphylococcus aureus at 2.9- and 2.8-Å resolution. Biochemistry 20, 2361–2370 (1981).
Donaldson, J. M. et al. Identification and grafting of a unique peptide-binding site in the Fab framework of monoclonal antibodies. Proc. Natl Acad. Sci. USA 110, 17456–17461 (2013).
Li, S. et al. Structural basis for inhibition of the epidermal growth factor receptor by cetuximab. Cancer Cell 7, 301–311 (2005).
Sanner, M. F. Python: a programming language for software integration and development. J. Mol. Graph. Model. 17, 57–61 (1999).
Gasteiger, J. & Marsili, M. A new model for calculating atomic charges in molecules. Tetrahedron Lett. 19, 3181–3184 (1978).
Trott, O. & Olson, A. J. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J. Comput. Chem. 31, 455–461 (2010).
Price, D. J. & Brooks, C. L. A modified TIP3P water potential for simulation with Ewald summation. J. Chem. Phys. 121, 10096–10103 (2004).
Huang, J. & MacKerell, A. D. CHARMM36 all-atom additive protein force field: Validation based on comparison to NMR data. J. Comput. Chem. 34, 2135–2145 (2013).
Hess, B., Bekker, H., Berendsen, H. J. C. & Fraaije, J. G. E. M. LINCS: A linear constraint solver for molecular simulations. J. Comput. Chem. 18, 1463–1472 (1997).
Essmann, U. et al. A smooth particle mesh Ewald method. J. Chem. Phys. 103, 8577–8593 (1995).
Verlet, L. Computer ‘Experiments’ on Classical Fluids. I. Thermodynamical Properties of Lennard-Jones Molecules. Phys. Rev. 159, 98–103 (1967).
Parrinello, M. & Rahman, A. Polymorphic transitions in single crystals: A new molecular dynamics method. J. Appl. Phys. 52, 7182–7190 (1981).
Bussi, G., Donadio, D. & Parrinello, M. Canonical sampling through velocity rescaling. J. Chem. Phys. 126, 14101 (2007).
Humphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. 14, 33–38 (1996).
Torrie, G. M. & Valleau, J. P. Nonphysical sampling distributions in Monte Carlo free-energy estimation: umbrella sampling. J. Comput. Phys. 23, 187–199 (1977).
Souaille, M. & Roux, B. Extension to the weighted histogram analysis method: combining umbrella sampling with free energy calculations. Comput. Phys. Commun. 135, 40–57 (2001).
We thank staff at the Advanced Instrumentation Research Facility at Jawaharlal Nehru University, Delhi and DBT grant (no. BT/PR3130/INF/22/139/2011) for use of their confocal microscopy facility.
N.G., A.Sarkar, A.Sengupta and M.R. are employees of Akamara Therapeutics and own equity. S.S. is a cofounder and board member of Akamara Therapeutics and owns equity in Akamara Therapeutics. N.G., S.S. and M.R. are listed as inventors on a patent on this technology (US Patent App. 15/124,058; WO2015148126A1).
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Gupta, N., Ansari, A., Dhoke, G.V. et al. Computationally designed antibody–drug conjugates self-assembled via affinity ligands. Nat Biomed Eng 3, 917–929 (2019). https://doi.org/10.1038/s41551-019-0470-8
This article is cited by
Nature Communications (2020)
Nature Biomedical Engineering (2019)