In silico design of stable single-domain antibodies with high affinity

Area of Science:

• Biotechnology
• Immunology
• Structural Biology

Background:

• Antibody design is complex and resource-intensive.
• Deep learning and generative methods show promise but face challenges in achieving high affinity and stability.
• Developing effective antibody therapeutics requires overcoming these design limitations.

Purpose of the Study:

• Introduce EvolveX, a structure-based antibody design pipeline.
• Demonstrate EvolveX's capability to enhance antibody stability and affinity.
• Redesign a VHH antibody for high affinity to human Vsig4.

Main Methods:

• Utilized EvolveX, a pipeline leveraging the FoldX empirical force field.
• Designed complementarity-determining regions (CDRs) of single-domain antibodies (VHHs).
• Applied EvolveX to redesign a VHH targeting mouse Vsig4 (mVsig4).

Main Results:

• EvolveX successfully enhanced stability and affinity of VHHs for mVsig4.
• Achieved over 1,000-fold improvement in binding affinity to human Vsig4.
• X-ray crystallography confirmed design accuracy; NGS analysis validated pipeline efficiency.

Conclusions:

• EvolveX overcomes current limitations in antibody design.
• Offers a powerful tool for developing therapeutics with enhanced specificity, stability, and efficacy.
• Highlights the potential of structure-based design using empirical force fields.