Computational design of N-linked glycans for high throughput epitope profiling

Area of Science:

• Biochemistry
• Computational Biology
• Drug Discovery

Background:

• Epitope identification is vital for drug discovery, antibody development, and understanding binding interfaces.
• Traditional methods like X-ray crystallography are accurate but slow and limited in scope.
• A need exists for faster, more scalable epitope mapping techniques.

Purpose of the Study:

• To develop and validate a rapid computational method for epitope identification using N-linked glycans.
• To demonstrate the method's efficacy in mapping epitopes on human coagulation factor IXa (fIXa).
• To accelerate the process of epitope selection and antibody diversity expansion in drug discovery.

Main Methods:

• Computational screening of N-linked glycan insertion sites to mask epitopes.
• Experimental validation using ELISA and high-throughput yeast surface display assays.
• X-ray crystallography to confirm the coarse-grained epitope mapping.

Main Results:

• Successfully delineated epitopes rapidly and reliably by site-selective disruption of binding with N-linked glycans.
• Computational screening identified 158 potential positions, with 98 variants tested experimentally.
• The N-linked glycan method provided a coarse-grained mapping of the epitope, validated by crystallography.

Conclusions:

• The developed N-linked glycan-based computational method offers a rapid and reliable approach for epitope mapping.
• This technique significantly enhances efficiency in drug discovery and antibody design.
• The method overcomes limitations of traditional techniques, enabling faster lead optimization.