Prediction of hERG inhibition of drug discovery compounds using biomimetic HPLC measurements

The major causes of failure of drug discovery compounds in clinics are the lack of efficacy and toxicity. To reduce late-stage failures in the drug discovery process, it is essential to estimate early the probability of adverse effects and potential toxicity. Cardiotoxicity is one of the most often...

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Main Authors: Chrysanthos Stergiopoulos, Fotios Tsopelas, Klara Valko
Format: Article
Language:English
Published: International Association of Physical Chemists (IAPC) 2021-06-01
Series:ADMET and DMPK
Online Access:https://www.pub.iapchem.org/ojs/index.php/admet/article/view/995
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author Chrysanthos Stergiopoulos
Fotios Tsopelas
Klara Valko
author_facet Chrysanthos Stergiopoulos
Fotios Tsopelas
Klara Valko
author_sort Chrysanthos Stergiopoulos
collection DOAJ
description The major causes of failure of drug discovery compounds in clinics are the lack of efficacy and toxicity. To reduce late-stage failures in the drug discovery process, it is essential to estimate early the probability of adverse effects and potential toxicity. Cardiotoxicity is one of the most often observed problems related to a compound's inhibition of the hERG channel responsible for the potassium cation flux. Biomimetic HPLC methods can be used for the early screening of a compound's lipophilicity, protein binding and phospholipid partition. Based on the published hERG pIC50 data of 90 marketed drugs and their measured biomimetic properties, a model has been developed to predict the hERG inhibition using the measured binding of compounds to alpha-1-acid-glycoprotein (AGP) and immobilised artificial membrane (IAM). A representative test set of 16 compounds was carefully selected. The training set, involving the remaining compounds, served to establish the linear model. The mechanistic model supports the hypothesis that compounds have to traverse the cell membrane and bind to the hERG ion channel to cause the inhibition. The AGP and the hERG ion channel show structural similarity, as both bind positively charged compounds with strong shape selectivity. In contrast, a good IAM partition is a prerequisite for cell membrane traversal. For reasons of comparison, a corresponding model was derived by replacing the measured biomimetic properties with calculated physicochemical properties. The model established with the measured biomimetic binding properties proved to be superior and can explain over 70% of the variance of the hERG pIC50 values. ©2021 by the authors. This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
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spelling doaj.art-d07bafccc3124de690a5920e9e7eb1ac2022-12-21T23:13:27ZengInternational Association of Physical Chemists (IAPC)ADMET and DMPK1848-77182021-06-0110.5599/admet.995Prediction of hERG inhibition of drug discovery compounds using biomimetic HPLC measurementsChrysanthos Stergiopoulos0Fotios Tsopelas1Klara Valko2Laboratory of Inorganic and Analytical Chemistry, School of Chemical Engineering, National Technical University of AthensLaboratory of Inorganic and Analytical Chemistry, School of Chemical Engineering, National Technical University of AthensBio-Mimetic Chromatography Ltd. Stevenage, Herts, United KingdomThe major causes of failure of drug discovery compounds in clinics are the lack of efficacy and toxicity. To reduce late-stage failures in the drug discovery process, it is essential to estimate early the probability of adverse effects and potential toxicity. Cardiotoxicity is one of the most often observed problems related to a compound's inhibition of the hERG channel responsible for the potassium cation flux. Biomimetic HPLC methods can be used for the early screening of a compound's lipophilicity, protein binding and phospholipid partition. Based on the published hERG pIC50 data of 90 marketed drugs and their measured biomimetic properties, a model has been developed to predict the hERG inhibition using the measured binding of compounds to alpha-1-acid-glycoprotein (AGP) and immobilised artificial membrane (IAM). A representative test set of 16 compounds was carefully selected. The training set, involving the remaining compounds, served to establish the linear model. The mechanistic model supports the hypothesis that compounds have to traverse the cell membrane and bind to the hERG ion channel to cause the inhibition. The AGP and the hERG ion channel show structural similarity, as both bind positively charged compounds with strong shape selectivity. In contrast, a good IAM partition is a prerequisite for cell membrane traversal. For reasons of comparison, a corresponding model was derived by replacing the measured biomimetic properties with calculated physicochemical properties. The model established with the measured biomimetic binding properties proved to be superior and can explain over 70% of the variance of the hERG pIC50 values. ©2021 by the authors. This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).https://www.pub.iapchem.org/ojs/index.php/admet/article/view/995
spellingShingle Chrysanthos Stergiopoulos
Fotios Tsopelas
Klara Valko
Prediction of hERG inhibition of drug discovery compounds using biomimetic HPLC measurements
ADMET and DMPK
title Prediction of hERG inhibition of drug discovery compounds using biomimetic HPLC measurements
title_full Prediction of hERG inhibition of drug discovery compounds using biomimetic HPLC measurements
title_fullStr Prediction of hERG inhibition of drug discovery compounds using biomimetic HPLC measurements
title_full_unstemmed Prediction of hERG inhibition of drug discovery compounds using biomimetic HPLC measurements
title_short Prediction of hERG inhibition of drug discovery compounds using biomimetic HPLC measurements
title_sort prediction of herg inhibition of drug discovery compounds using biomimetic hplc measurements
url https://www.pub.iapchem.org/ojs/index.php/admet/article/view/995
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