College of Food Science and Technology, Henan Agricultural University, 450002 Zhengzhou, People's Republic of China.
Beijing Key Laboratory of Detection Technology for Animal-Derived Food Safety, Beijing Laboratory of Food Quality and Safety, College of Veterinary Medicine, China Agricultural University, Beijing 100193, China.
J Hazard Mater. 2023 Mar 5;445:130615. doi: 10.1016/j.jhazmat.2022.130615. Epub 2022 Dec 15.
Antibody is the key biomolecule that governing the sensitivity and specificity of an immunoassay for chemical compound, also named hapten molecule. Obviously, predication of hapten effectiveness before chemical synthesis is beneficial to boost success, save cost and improve controllability. Here, we proposed and evaluated an epitopephore based rational hapten design (ERHD) to assist antibody production to chemical compound, combining theoretical evidence and then experimental validation by using dinitrocarbanilide (DNC) as a model analyte. Briefly, epitopephores of DNC were firstly generated by HipHop algorithm after features mapping. A homemade drug database also containing reported fragment haptens (HFR) and new designed full hapten (HFU) were constructed, and then was virtually screened by using generated epitopephore followed by structural analysis and visual inspection. The DNC haptens based on the selected hits were further identified by Density Functional Theory before total synthesis. To prove and clarify the usability of the ERHD, two retrieved HFU haptens, one non-retrieved HFU hapten and three non-retrieved HFR haptens were all selected to produce monoclonal antibodies (mAbs) for comparison purpose. A maximal 6000-fold increased affinity of mAb from retrieved HFU than HFR was observed, while, non-retrieved HFU failed to produce antibody to DNC. More importantly, mAbs from HFU haptens provided highly specificity to DNC, while, mAbs from HFR haptens could recognize 15 others analogues. We then constructed antibody structure and investigated molecular recognition of the mAbs to DNC, well supporting the rationality of the ERHD. Lastly, an icELISA was developed for DNC with an IC value as low as 0.19 ng mL with high specificity, which has never achieved before.
抗体是控制化学化合物免疫分析的灵敏度和特异性的关键生物分子，也称为半抗原分子。显然，在化学合成之前预测半抗原的有效性有助于提高成功率、降低成本和提高可控性。在这里，我们提出并评估了一种基于表位的合理半抗原设计（ERHD），以辅助针对化学化合物的抗体产生，结合理论证据，然后通过使用二硝基甲酰苯胺（DNC）作为模型分析物进行实验验证。简而言之，首先通过特征映射后的 HipHop 算法生成 DNC 的表位肽。构建了一个自制的药物数据库，其中包含报道的片段半抗原（HFR）和新设计的完整半抗原（HFU），然后通过生成的表位肽进行虚拟筛选，随后进行结构分析和目视检查。基于所选命中物的 DNC 半抗原进一步通过密度泛函理论进行鉴定，然后再进行全合成。为了证明和阐明 ERHD 的可用性，选择了两种检索到的 HFU 半抗原、一种未检索到的 HFU 半抗原和三种未检索到的 HFR 半抗原用于产生单克隆抗体（mAb）进行比较。从检索到的 HFU 获得的 mAb 的亲和力比 HFR 最大增加了 6000 倍，而未检索到的 HFU 未能产生针对 DNC 的抗体。更重要的是，HFU 半抗原的 mAb 对半抗原 DNC 具有高度特异性，而 HFR 半抗原的 mAb 可以识别 15 种其他类似物。然后，我们构建了抗体结构并研究了 mAb 对半抗原 DNC 的分子识别，这很好地支持了 ERHD 的合理性。最后，开发了一种用于 DNC 的 icELISA，其 IC 值低至 0.19ng/mL，具有很高的特异性，这是以前从未达到过的。
