Antibody Recognition Profile-Aided Hapten Design to\nModulate Antibody Generation with Anticipated Performance for Immunoassay\nDevelopment

The\nhapten design to chemical compound currently considered only\nstructural aspects of targets may suffer from the failure of antibody\ngeneration with anticipated performances, especially for broad-specific\nantibodies. To address the problem, this study proposed a novel strategy,\nnamed antibody recognition profile-aided hapten design (ARPHD), based\non clues from both reported antibodies, haptens, and targets after\nuncovering antibody recognition profiles using fluorfenicol (FF) and\nfluorfenicol amine (FFA) as model analytes in this work. Specifically,\nwe confirmed that the fluorine atom promoted the generation of antibodies\nto FFA, while the –COCHCl<sub>2</sub> moiety was unfavorable\nfor inducing broad-specific antibodies to FF and FFA. Based on the\nstructural information from ARPHD, four novel haptens without –COCHCl<sub>2</sub> and containing a fluorine atom are intentionally designed,\nthen identified by computational chemistry and animal immunization,\nsuccessfully inducing antibodies to FF and FFA with uniform IC<sub>50</sub> values of 3.09 and 3.75 ng mL<sup>–1</sup>. The explanation\nof molecular mechanisms from the obtained antibodies has supported\nthe scientific base behind ARPHD, and we also found that the light\nchain of the antibody contributed an important role in differential\nrecognition of the antibody. Finally, an indirect competitive ELISA\n(icELISA) was developed for the simultaneous detection of FF and FFA\nin river water and animal-derived food with a LOD of 2.24–14.6\nμg kg<sup>–1</sup>, which has never been achieved before.\nThe study demonstrated that the ARPHD we proposed could rationally\nguide the design of haptens that modulate the generation of antibodies\nwith appreciated performances and easily be extended to other chemical\ncompounds as a versatile platform.