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

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

doi:10.1097/FTD.0b013e31819c1b83

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

Journal article

Open access

Peer reviewed

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

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

Therapeutic drug monitoring, Vol.31(3), pp.337-344

06/2009

DOI: 10.1097/FTD.0b013e31819c1b83

PMCID: PMC2846282

PMID: 19333148

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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.

Cross Reactions

Immunoassay

Predictive Value of Tests

Models, Molecular

Molecular Structure

Drug Monitoring

Databases, Factual

Details

Title: Subtitle: Molecular similarity methods for predicting cross-reactivity with therapeutic drug monitoring immunoassays
Creators: Matthew D Krasowski - Department of Pathology, University of Pittsburgh, Scaife Hall S-737, 3550 Terrace Street, Pittsburgh, PA 15261, USA. mdk24@pitt.edu
Mohamed G Siam
Manisha Iyer
Sean Ekins
Resource Type: Journal article
Publication Details: Therapeutic drug monitoring, Vol.31(3), pp.337-344
DOI: 10.1097/FTD.0b013e31819c1b83
PMID: 19333148
PMCID: PMC2846282
NLM abbreviation: Ther Drug Monit
ISSN: 0163-4356
eISSN: 1536-3694
Publisher: United States
Grant note: K08 GM074238 / NIGMS NIH HHS K08 GM074238-03 / NIGMS NIH HHS K08 GM074238-02 / NIGMS NIH HHS K08-GM074238 / NIGMS NIH HHS
Language: English
Date published: 06/2009
Academic Unit: Pathology
Record Identifier: 9984047750402771

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