bioRxivBiochemistryPreprint
Computational design of pH-sensitive binders
Green AhniD, Brian CoventryiD, Ella HaefneriD, Shayan SadreiD, Jenny Hu, Mimosa Van, Buwei HuangiD, Isaac SappingtoniD, Adam J. BroermaniD, Mauriz A. LichtensteiniD, Matthias GlögliD, Inna GoreshnikiD, Dionne K. VafeadosiD, David A. BakeriD
Abstract
pH gradients are central to physiology, from vesicle acidification to the acidic tumor microenvironment. While therapeutics have been developed to exploit these pH changes to modulate activity across different physiological environments, current approaches for generating pH-dependent binders, such as combinatorial histidine scanning and display-based selections, are largely empirical and often labor-intensive. Here we describe two complementary principles and associated computational methods for designing pH-dependent binders: (i) introducing histidine residues adjacent to positively charged residues at binder-target interfaces to induce electrostatic repulsion and weaken binding at low pH, and (ii) introducing buried histidine-containing charged hydrogen-bonding networks in the binder core such that the protein is destabilized under acidic conditions. Using these methods, we designed binders that dissociate at acidic pH against ephrin type-A receptor 2, tumor necrosis factor receptor 2, interleukin-6, proprotein convertase subtilisin/kexin type 9, and the interleukin-2 mimic Neo2. Fusions of the designs to pH-independent binders of lysosomal trafficking receptors function as catalytic degraders, inducing target degradation at substoichiometric levels. Our methods should be broadly useful for designing pH-sensitive protein therapeutics.
- assay: protein structure
- research focus: drug response / drug discovery
- approach: deep learning
- approach: statistical model
- Citations
- 7
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