Computationally designed antibody-drug conjugates self-assembled via affinity ligands

Area of Science:

• Bioconjugation chemistry
• Computational drug design
• Antibody-drug conjugates (ADCs)

Background:

• Current antibody-drug conjugate (ADC) synthesis methods often result in unstable or heterogeneous products, or involve complex procedures.
• There is a need for simpler, more efficient methods to produce homogeneous and stable ADCs.

Purpose of the Study:

• To develop a computational approach for designing self-assembling antibody-drug conjugates (ADCs).
• To create ADCs with non-covalent binding between antibody and payload, avoiding antibody modification.
• To assess the stability, specificity, and anti-tumor efficacy of computationally designed ADCs.

Main Methods:

• Utilized molecular docking and molecular dynamics simulations to design ADCs.
• Engineered a payload with an affinity ligand for conserved antibody residues for non-covalent self-assembly.
• Evaluated ADC stability in plasma and anti-tumor efficacy in mouse models.

Main Results:

• Developed a computational method enabling rapid (<8 min) self-assembly of homogeneous ADCs.
• Designed ADCs (hydrophilic and hydrophobic payloads) retained antibody structure, binding properties, and specificity.
• Demonstrated plasma stability and improved anti-tumor efficacy in non-small cell lung cancer xenografts in mice.

Conclusions:

• A novel computational strategy facilitates the design and rapid production of homogeneous ADCs via non-covalent self-assembly.
• This simplified approach maintains ADC integrity and biological function, showing promise for targeted cytotoxic payload delivery.
• The method has the potential to streamline ADC production for various therapeutic applications.