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Computational design of pH-sensitive binders.

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Summary
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Scientists developed computational methods to design pH-dependent protein binders. These binders can be engineered to weaken or destabilize at acidic pH, enabling new therapeutic strategies for diseases like cancer.

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Area of Science:

  • Biochemistry and Molecular Biology
  • Protein Engineering
  • Therapeutic Development

Background:

  • Physiological pH gradients are crucial in biological processes, including vesicle transport and the tumor microenvironment.
  • Existing methods for creating pH-dependent binders are empirical, labor-intensive, and lack predictability.
  • Targeting pH changes offers a promising avenue for developing novel therapeutics.

Purpose of the Study:

  • To introduce novel computational principles for designing pH-dependent protein binders.
  • To create binders that can be modulated by pH for therapeutic applications.
  • To demonstrate the efficacy of these binders in degrading specific protein targets.

Main Methods:

  • Designed pH-dependent binders using two computational principles: electrostatic repulsion at interfaces and destabilization via buried histidine networks.
  • Introduced histidine residues adjacent to positive charges to weaken binding at low pH.
  • Incorporated buried histidine-containing hydrogen-bonding networks to destabilize protein structure under acidic conditions.

Main Results:

  • Successfully designed binders that dissociate at acidic pH against multiple targets: ephrin type-A receptor 2, tumor necrosis factor receptor 2, interleukin-6, proprotein convertase subtilisin/kexin type 9, and Neo2.
  • Engineered catalytic degraders by fusing designed binders to lysosomal trafficking receptors.
  • Achieved target degradation at substoichiometric levels using these catalytic degraders.

Conclusions:

  • The described computational methods provide a rational approach for designing pH-sensitive protein therapeutics.
  • These pH-dependent binders and catalytic degraders have broad applicability for modulating protein activity in various physiological environments.
  • The findings pave the way for developing next-generation protein-based therapies exploiting pH gradients.