bioRxivBioengineering
Computational design of non-porous, pH-responsive antibody nanoparticles
E. C. Yang, R. Divine, M. C. Miranda, A. J. Borst, W. Sheffler, J. Z. Zhang, J. Decarreau, A. Sarajovi, M. Abedi, N. Goldbach, M. Ahlrichs, C. Dobbins, A. Hand, S. Cheng, M. Lamb, P. M. Levine, S. Chan, R. Skotheim, J. Fallas, G. Ueda, J. Lubner, M. Somiya, A. Khmelinskaia, N. P. King, D. Baker
Abstract
Programming protein nanomaterials to respond to changes in environmental conditions is a current challenge for protein design and important for targeted delivery of biologics. We describe the design of octahedral non-porous nanoparticles with the three symmetry axes (four-fold, three-fold, and two-fold) occupied by three distinct protein homooligomers: a de novo designed tetramer, an antibody of interest, and a designed trimer programmed to disassemble below a tunable pH transition point. The nanoparticles assemble cooperatively from independently purified components, and a cryo-EM density map reveals that the structure is very close to the computational design model. The designed nanoparticles can package a variety of molecular payloads, are endocytosed following antibody-mediated targeting of cell surface receptors, and undergo tunable pH-dependent disassembly at pH values ranging between to 5.9-6.7. To our knowledge, these are the first designed nanoparticles with more than two structural components and with finely tunable environmental sensitivity, and they provide new routes to antibody-directed targeted delivery.
- assay: protein structure
- research focus: drug response / drug discovery
- approach: deep learning
- approach: experimental assay
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