Antibody recruiting molecules (ARMs) are an innovative class of chimeric molecules, consisting of an antibody-binding ligand (ABL) and a target-binding ligand (TBL). ARMs mediate ternary complex formation between a target cell of interest for elimination and endogenous antibodies that are present in human serum. Clustering of fragment crystallizable (Fc) domains on the surface of antibody-bound cells mediate destruction of the target cell by innate immune effector mechanisms. ARMs are typically designed by conjugating small molecule haptens to a (macro)molecular scaffold, without considering the structure of the respective anti-hapten antibody. Here we report on a computational molecular modeling methodology that allows for studying the close contacts between ARMs and the anti-hapten antibody, considering (1) the spacer length between ABL and TBL; (2) the number of ABL and TBL, and (3) the molecular scaffold onto which these are positioned. Our model predicts the difference in binding modes of the ternary complex and predicts which ARMs are optimal recruiters. Avidity measurements of the ARM-antibody complex and ARM-mediated antibody recruitment to cell surfaces in vitro confirmed these computational modeling predictions. This kind of multiscale molecular modelling holds potential for design of drug molecules that rely on antibody binding for their mechanism of action.
Keywords: antibodies; immunology; in silico; modelling; ternary complex.
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