免疫分析中异源竞争模式被普遍认为可以提高方法灵敏度，但目前对异源竞争原的设计大多凭借经验，偶然性比较大，很难确保设计到最佳竞争原。本课题拟在前期获得的抗喹诺酮类兽药单克隆抗体基础上，选取32种不同结构的氟喹诺酮类小分子作为竞争原，重点开展以下三个方面的研究；1，利用计算机辅助分子设计对32种竞争原进行分子描述符计算，明确影响竞争原异源度的关键因素，对异源度进行量化和排序。2，利用生物膜层干涉技术测定抗体与各竞争原之间的亲和力常数，探究异源度与亲和常数之间的关系，预判最佳竞争原。3，应用酶联免疫吸附法测定在不同竞争原下抗体的亲和力和特异性作为最佳竞争原的选定依据，检验最佳竞争原。通过本课题研究，可以基本明确竞争原异源度和亲和常数之间的相互影响机制，进一步解释异源竞争模式提高免疫分析灵敏度的原理，有效避免设计异源竞争原设计时的盲目性，为最佳竞争原的筛选提供科学指导依据。

Heterogeneous competition pattern was widely considered as a means of improving the sensitivity of immunoassay. However, the design of heterogeneous antigen was empirical and occasional so as to difficult to obtain the best heterogeneous antigen. Based on the monoclonal antibody against quinolone drugs in early, we select 32 different structure of quinolone drugs as antigens. The project intend to calculate the molecular descriptors of heterogeneous antigens through computer aided molecular design, find out the key factors influencing heterogeneous degree of antigens with some quantifying and sorting. Besides, the affinity of antibody in different competition are tested by Bio-layer interferometry, the relationship between affinity constants and the heterogeneous degree are explored and the optimal hapten in theory is predicted which will be verified by enzyme linked immunosorbent assay subsequently. This project further explain the principle of heterogeneous competition pattern, effectively avoid the blindness in the design of heterogeneous antigen, provide scientific guidance of screening the best screening heterogeneous antigen.