QSAR analysis of immune recognition for triazine herbicides based on immunoassay data for polyclonal and monoclonal antibodies

Andrey A Buglak, Anatoly V Zherdev, Hong-Tao Lei and Boris B Dzantiev

PLOS ONE, 2019, vol. 14, issue 4, 1-19

Abstract: A common task in the immunodetection of structurally close compounds is to analyze the selectivity of immune recognition; it is required to understand the regularities of immune recognition and to elucidate the basic structural elements which provide it. Triazines are compounds of particular interest for such research due to their high variability and the necessity of their monitoring to provide safety for agricultural products and foodstuffs. We evaluated the binding of 20 triazines with polyclonal (pAb) and monoclonal (mAb) antibodies obtained using atrazine as the immunogenic hapten. A total of over 3000 descriptors were used in the quantitative structure-activity relationship (QSAR) analysis of binding activities (pIC50). A comparison of the two enzyme immunoassay systems showed that the system with pAb is much easier to describe using 2D QSAR methodology, while the system with mAb can be described using the 3D QSAR CoMFA. Thus, for the 3D QSAR model of the polyclonal antibodies, the main statistical parameter q2 (‘leave-many-out’) is equal to 0.498, and for monoclonal antibodies, q2 is equal to 0.566. Obviously, in the case of pAb, we deal with several targets, while in the case of mAb the target is one, and therefore it is easier to describe it using specific fields of molecular interactions distributed in space.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0214879

DOI: 10.1371/journal.pone.0214879

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