Affinity maturation of antibodies assisted by in silico modeling.

Rational engineering methods can be applied with reasonable success to optimize physicochemical characteristics of proteins, in particular, antibodies. Here, we describe a combined CDR3 walking randomization and rational design-based approach to enhance the affinity of the human anti-gastrin TA4 scFv. The application of this methodology to TA4 scFv, displaying only a weak overall affinity for gastrin17 (K(D) = 6 microM), resulted in a set of nine affinity-matured scFv variants with near-nanomolar affinity (K(D) = 13.2 nM for scFv TA4.112). First, CDR-H3 and CDR-L3 randomization resulted in three scFvs with an overall affinity improvement of 15- to 35-fold over the parental. Then, the modeling of two scFv constructs selected from the previous step (TA4.11 and TA4.13) was followed by a combination of manual and molecular dynamics-based docking of gastrin17 into the respective binding sites, analysis of apparent packing defects, and selection of residues for mutagenesis through phage display. Nine scFv mutants were obtained from the second maturation step. A final 454-fold improvement in affinity compared with TA4 was obtained. These scFvs showed an enhanced potency to inhibit gastrin-induced proliferation in Colo 320 WT and BxPc3 tumoral cells. In conclusion, we propose a structure-based rational method to accelerate the development of affinity-matured antibody constructs with enhanced potential for therapeutic use.