Victor Chang Cardiac Research Institute (W.L., M.J.W., M.D.P., J.I.V., A.P.H.) and St Vincent's Clinical School (W.L., M.J.W., M.D.P., J.I.V., A.P.H.), University of New South Wales, Darlinghurst, New South Wales, Australia.
Victor Chang Cardiac Research Institute (W.L., M.J.W., M.D.P., J.I.V., A.P.H.) and St Vincent's Clinical School (W.L., M.J.W., M.D.P., J.I.V., A.P.H.), University of New South Wales, Darlinghurst, New South Wales, Australia
Mol Pharmacol. 2019 May;95(5):537-550. doi: 10.1124/mol.118.115220. Epub 2019 Feb 15.
Current guidelines around preclinical screening for drug-induced arrhythmias require the measurement of the potency of block of voltage-gated potassium channel subtype 11.1 (K11.1) as a surrogate for risk. A shortcoming of this approach is that the measured IC of K11.1 block varies widely depending on the voltage protocol used in electrophysiological assays. In this study, we aimed to investigate the factors that contribute to these differences and to identify whether it is possible to make predictions about protocol-dependent block that might facilitate the comparison of potencies measured using different assays. Our data demonstrate that state preferential binding, together with drug-binding kinetics and trapping, is an important determinant of the protocol dependence of K11.1 block. We show for the first time that differences in IC measured between protocols occurs in a predictable way, such that machine-learning algorithms trained using a selection of simple voltage protocols can indeed predict protocol-dependent potency. Furthermore, we also show that the preference of a drug for binding to the open versus the inactivated state of K11.1 can also be inferred from differences in IC values measured between protocols. Our work therefore identifies how state preferential drug binding is a major determinant of the protocol dependence of IC values measured in preclinical K11.1 assays. It also provides a novel method for quantifying the state dependence of K11.1 drug binding that will facilitate the development of more complete models of drug binding to K11.1 and improve our understanding of proarrhythmic risk associated with compounds that block K11.1.
目前，药物诱导心律失常的临床前筛选指南要求测量电压门控钾通道亚型 11.1（K11.1）的阻断效力，作为风险的替代指标。这种方法的一个缺点是，所测量的 K11.1 阻断 IC 值因电生理学测定中使用的电压方案而异。在这项研究中，我们旨在研究导致这些差异的因素，并确定是否有可能对依赖方案的阻断做出预测，从而有助于比较使用不同测定法测量的效力。我们的数据表明，状态优先结合以及药物结合动力学和捕获是 K11.1 阻断的依赖方案的重要决定因素。我们首次表明，在不同方案之间测量的 IC 差异以可预测的方式发生，使得使用选择的简单电压方案训练的机器学习算法确实可以预测依赖方案的效力。此外，我们还表明，药物对 K11.1 的开放态与失活态的结合偏好也可以从不同方案之间测量的 IC 值差异中推断出来。因此，我们的工作确定了状态优先药物结合如何成为临床前 K11.1 测定中 IC 值依赖方案的主要决定因素。它还提供了一种量化 K11.1 药物结合状态依赖性的新方法，将有助于开发更完整的 K11.1 药物结合模型，并提高我们对阻断 K11.1 的化合物与心律失常风险相关的理解。
