What is the issue?
- In recent years, a number of drugs have been withdrawn from the market because of reports of sudden cardiac death.
- In all cases, long QT syndrome an abnormality of cardiac muscle repolarization that is characterized by the prolongation of the QT interval in the electrocardiogram, was implicated as inducing ventricular tachycardia that can spontaneously degenerate to ventricular fibrillation and cause sudden death.
- Virtually every case of a prolonged duration of cardiac action potential related to drug exposure can be traced to one specific mechanism: blockade of IKr current in the heart.
- Blockade of hERG channels is widely regarded as the predominant cause of drug-induced QT prolongation.
- If drug levels of even a modest affinity hERG ligand rise, due to inhibition of a co-administered CYP inhibitor, QT prolongation may be observed
Pharmacophore model consists of a basic nitrogen center flanked by aromatic or hydrophobic groups attached with flexible linkers, receptor modeling and mutagenesis studies highlight interactions between ligand (MK-499) and V625, G648, Y652 and F656. PNAS 97, 12329 (2000) are consistent with the pharmacophore model.
Empirical observations
- Zwitterions very rarely cause problems
- Almost all models include cLogP, a reduction of 1 logP unit in logP often leads to a 0.8 log unit in hERG activity
- Modify pi-Stacking interactions to reduce affinity
- Attenuation of pKa of basic amines, or steric blocking
- Do both, beta-alkoxy/hydroxy reduce pKa and LogP
- Acids less of an issue except for lipophilic acids.
What level of selectivity is needed?
In vitro binding affinity does not always correlate with observed in vivo activity
Need to check early in programme
Better to focus in vivo, on a window (10-100 fold) over the observed plasma Cmax at the likely clinical dose.
Updated:- Given the issues that many drug discovery programs have had with off-target activity at the hERG channel I've started to compile a database of literature binding data. To date I have information on over 1100 compounds, my aim is to use the data to develop predictive models that I will make freely available, together with the complete data-set which I hope can be used to test novel models.
The plot below (created using Vortex)shows pIC50 calculated from the literature IC50 data versus calculated logP determined using alogPS, the colour coding shows the overall general tend of increasing hERG activity as logP increases, it also highlights the reduced liability seen with acids (green) and zwitterions (red).
Whilst the majority of data is derived from radioligand binding experiments (using either Dofetilide or MK-499), there is a substantial amount of data from patch clamp experiments, I collated enough data now (covering 4 orders of magnitude) to give an idea of how the assays compare. As you can see there is a reasonable correlation between the assays, but there are one or two outliers. Which is more predictive of in vivo activity is an excellent question that I don’t have the data to answer yet.
I still need to increase the size of the data-set, and if anyone can direct me to any publicly available data, or to publications that contain data I'd much appreciate it.
Worth reading, Medicinal Chemistry of hERG Optimizations: Highlights and Hang-Ups, Jamieson, Journal of Medicinal Chemistry, 2006, 5029
Last Update 11 Sept 2009
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