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用于预测治疗药物监测免疫分析交叉反应性的分子相似性方法。

Molecular similarity methods for predicting cross-reactivity with therapeutic drug monitoring immunoassays.

作者信息

Krasowski Matthew D, Siam Mohamed G, Iyer Manisha, Ekins Sean

机构信息

Department of Pathology, University of Pittsburgh, Scaife Hall S-737, 3550 Terrace Street, Pittsburgh, PA 15261, USA.

出版信息

Ther Drug Monit. 2009 Jun;31(3):337-44. doi: 10.1097/FTD.0b013e31819c1b83.

DOI:10.1097/FTD.0b013e31819c1b83
PMID:19333148
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2846282/
Abstract

Immunoassays are used for therapeutic drug monitoring (TDM), yet may suffer from cross-reacting compounds able to bind the assay antibodies in a manner similar to the target molecule. To our knowledge, there has been no investigation using computational tools to predict cross-reactivity with TDM immunoassays. The authors used molecular similarity methods to enable calculation of structural similarity for a wide range of compounds (prescription and over-the-counter medications, illicit drugs, and clinically significant metabolites) to the target molecules of TDM immunoassays. Utilizing different molecular descriptors (MDL public keys, functional class fingerprints, and pharmacophore fingerprints) and the Tanimoto similarity coefficient, the authors compared cross-reactivity data in the package inserts of immunoassays marketed for in vitro diagnostic use. Using MDL public keys and the Tanimoto similarity coefficient showed a strong and statistically significant separation between cross-reactive and non-cross-reactive compounds. Thus, 2-dimensional shape similarity of cross-reacting molecules and the target molecules of TDM immunoassays provides a fast chemoinformatics methods for a priori prediction of potential of cross-reactivity that might be otherwise undetected. These methods could be used to reliably focus cross-reactivity testing on compounds with high similarity to the target molecule and limit testing of compounds with low similarity and ultimately with a very low probability of cross-reacting with the assay in vitro.

摘要

免疫测定法用于治疗药物监测(TDM),但可能会受到能够以与靶分子相似的方式结合测定抗体的交叉反应性化合物的影响。据我们所知,尚未有研究使用计算工具来预测与TDM免疫测定法的交叉反应性。作者使用分子相似性方法来计算各种化合物(处方药和非处方药、非法药物以及具有临床意义的代谢物)与TDM免疫测定法靶分子的结构相似性。利用不同的分子描述符(MDL公钥、功能类指纹和药效团指纹)以及Tanimoto相似系数,作者比较了用于体外诊断的市售免疫测定法包装说明书中的交叉反应性数据。使用MDL公钥和Tanimoto相似系数显示,交叉反应性化合物和非交叉反应性化合物之间存在强烈且具有统计学意义的区分。因此,TDM免疫测定法的交叉反应性分子与靶分子的二维形状相似性为潜在交叉反应性的先验预测提供了一种快速的化学信息学方法,否则这些潜在交叉反应性可能无法被检测到。这些方法可用于可靠地将交叉反应性测试集中在与靶分子高度相似的化合物上,并限制对低相似性化合物的测试,最终降低其在体外与测定法发生交叉反应的可能性。

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