计算研究 hERG 通道阻滞剂：新见解和当前预测模型。

Computational investigations of hERG channel blockers: New insights and current predictive models.

机构信息

Molecules Therapeutiques in silico (MTi), Sorbonne Paris Cité, Universite Paris-Diderot, UMR-S 973, 75205 Paris Cedex 13, France; Molecules Therapeutiques in silico (MTi), Sorbonne Paris Cité, INSERM, UMR-S 973, 75205 Paris Cedex 13, France.

出版信息

Adv Drug Deliv Rev. 2015 Jun 23;86:72-82. doi: 10.1016/j.addr.2015.03.003. Epub 2015 Mar 12.

DOI:10.1016/j.addr.2015.03.003

PMID:25770776

Abstract

Identification of potential human Ether-a-go-go Related-Gene (hERG) potassium channel blockers is an essential part of the drug development and drug safety process in pharmaceutical industries or academic drug discovery centers, as they may lead to drug-induced QT prolongation, arrhythmia and Torsade de Pointes. Recent reports also suggest starting to address such issues at the hit selection stage. In order to prioritize molecules during the early drug discovery phase and to reduce the risk of drug attrition due to cardiotoxicity during pre-clinical and clinical stages, computational approaches have been developed to predict the potential hERG blockage of new drug candidates. In this review, we will describe the current in silico methods developed and applied to predict and to understand the mechanism of actions of hERG blockers, including ligand-based and structure-based approaches. We then discuss ongoing research on other ion channels and hERG polymorphism susceptible to be involved in LQTS and how systemic approaches can help in the drug safety decision.

摘要

鉴定潜在的人 Ether-a-go-go 相关基因（hERG）钾通道阻滞剂是制药行业或学术药物发现中心药物开发和药物安全过程的重要组成部分，因为它们可能导致药物诱导的 QT 延长、心律失常和尖端扭转型室性心动过速。最近的报告还表明，在命中选择阶段就开始解决这些问题。为了在早期药物发现阶段对分子进行优先级排序，并降低由于临床前和临床阶段的心脏毒性而导致药物淘汰的风险，已经开发了计算方法来预测新候选药物的潜在 hERG 阻断作用。在这篇综述中，我们将描述为预测和理解 hERG 阻滞剂的作用机制而开发和应用的当前计算方法，包括基于配体和基于结构的方法。然后，我们讨论了其他离子通道和 hERG 多态性的研究进展，这些多态性容易涉及长 QT 综合征，以及系统方法如何有助于药物安全决策。