Variant Nucleic Acid Libraries for SARS-CoV-2 Antibody Affinity

The patent applies preliminary action by pre-introducing beneficial mutations into the antibody sequence before therapeutic use. The method identifies mutations that enhance binding affinity to the SARS-CoV-2 spike protein and incorporates them into the antibody design in advance, rather than relying on random immune response or post-hoc optimization. This preliminary engineering of the antibody sequence with predicted beneficial mutations resolves the contradiction by providing high binding affinity from the start while maintaining a systematic approach to optimization.

The patent applies parameter changes by systematically modifying the antibody sequence parameters, specifically the amino acid sequence in the complementarity-determining regions (CDRs). The method evaluates multiple mutations and selects combinations that optimize binding affinity parameters. By changing the molecular parameters of the antibody (amino acid composition, sequence variants), the patent achieves enhanced binding affinity while maintaining a controllable optimization process through computational prediction and selection.

The patent reduces design complexity by performing preliminary computational analysis to predict beneficial mutations before laboratory experimentation. The method uses in-silico evaluation to identify promising antibody variants, allowing researchers to focus experimental resources on a smaller set of pre-validated candidates. This preliminary computational screening step simplifies the overall design process while maintaining high therapeutic efficacy potential.

The patent applies copying by creating multiple variant sequences based on a parent antibody sequence. Instead of designing entirely new antibodies, the method generates copies with specific mutations introduced at key positions. These copied variants are then evaluated and selected for enhanced binding affinity. This copying approach reduces design complexity by building upon an existing functional template rather than creating de novo designs.

The patent applies local quality by introducing mutations specifically in the complementarity-determining regions (CDRs) of the antibody, which are the local regions responsible for antigen binding. Rather than randomly mutating the entire antibody sequence, the method focuses mutations locally at the CDR positions that directly contact the SARS-CoV-2 spike protein. This localized approach enhances binding affinity while maintaining control over specificity, as the framework regions remain unchanged and preserve overall antibody structure and selectivity.

The patent applies feedback by using computational prediction models to evaluate the impact of mutations before implementation. The method predicts how each mutation will affect binding affinity and selects mutations with favorable predictions. This feedback loop between computational prediction and sequence design allows the patent to introduce multiple mutations while monitoring and controlling their cumulative effect on specificity. The feedback mechanism prevents introduction of mutations that might compromise off-target binding characteristics.