Nature Communications· 2026Q1
Energy-guided combinatorial co-optimization of antibody affinity and stability
- 3citations
- Q1SCImago
- 2026year
Short summary
A new strategy, LAffAb, uses antibody-antigen crystallographic structures to introduce multiple mutations, achieving up to 30-fold affinity gains while simultaneously improving stability, and yielding diverse variants with high mutational loads.
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Key points
- LAffAb strategy uses crystallographic structures to guide combinatorial antibody engineering.
- Up to 30-fold affinity gains achieved with simultaneous stability co-optimization.
- Generated diverse antibody variants with high mutational loads, not a single optimal solution.
- Small-scale screening yielded order-of-magnitude affinity improvements for a drug target.
- LAffAb improved a therapeutic antibody's developability without sacrificing affinity.
AI-generated from the title and abstract; the full text is not read.
Abstract
Affinity maturation is an essential process in antibody engineering. Although powerful, it is iterative, time-consuming, and can result in trade-offs, where affinity is gained at the cost of important properties, such as specificity and stability. We present a scalable strategy, called LAffAb, that starts from a crystallographic structure of the antibody-antigen complex and introduces combinations of mutations to optimize its energy. A combinatorial library comprising 7,000 variants with up to nine mutations results in gains of up to 30-fold in affinity while co-optimizing stability. Surprisingly, the library does not converge on a single solution, instead favoring diverse variants with a high mutational load. Small-scale screening of 10 designs against a potential drug target results in an order-of-magnitude improvement in affinity while maintaining high developability. We also apply LAffAb to improve the developability of a therapeutic antibody without degrading affinity. We envision that LAffAb can be used to design stable, specific, and high-affinity binders and to improve our understanding of sequence, structure, and function relationships in antibodies.
The authors' abstract, as published at the source. Nature Communications, 2026 · DOI ↗
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ImmunologyImmunology and Microbiology