Understanding hERG inhibition with QSAR models based on a one-dimensional molecular representation

Abstract

Blockage of the potassium channel encoded by the human ether-a-go-go related gene (hERG) is well understood to be the root cause of the cardio-toxicity of numerous approved and investigational drugs. As such, a cascade of in vitro and in vivo assays have been developed to filter compounds with hERG inhibitory activity. Quantitative structure activity relationship (QSAR) models are used at the very earliest part of this cascade to eliminate compounds that are likely to have this undesirable activity prior to synthesis. Here a new QSAR technique based on the one-dimensional representation is described in the context of the development of a model to predict hERG inhibition. The model is shown to perform close to the limits of the quality of the data used for model building. In order to make optimal use of the available data, a general robust mathematical scheme was developed and is described to simultaneously incorporate quantitative data, such as IC50 = 50 nM, and qualitative data, such as inactive or IC50 > 30 microM into QSAR models without discarding any experimental information.

hERG K+Channels: Structure, Function, and Clinical Significance

“…One explanation is that structurally diverse compounds may preferentially bind to the channel during distinct gating states (open or inactivated). A rigid pharmacophore model may therefore not be the best solution, despite the apparent homogenous nature of the binding site (146,320,336,617,703). Recent studies have attempted to address the problem of multiple binding modes for different drugs (146,320,336,617,703).…”

“…A rigid pharmacophore model may therefore not be the best solution, despite the apparent homogenous nature of the binding site (146,320,336,617,703). Recent studies have attempted to address the problem of multiple binding modes for different drugs (146,320,336,617,703). One approach taken by Kramer et al (336) was to produce a composite model of two pharmacophores for high-affinity Kv11.1 blockers, as well as a third model for compounds that did not fit either of the first two pharmacophores (labeled nonspecific).…”

Collation, assessment and analysis of literature in vitro data on hERG receptor blocking potency for subsequent modeling of drugs' cardiotoxic properties

“…Recent studies have involved homology modeling, docking studies, classical or hologram 2D-QSAR (two-dimensional quantitative structure-activity relationships) and 3D-QSAR (Aptula and Cronon, 2004;Aronov, 2005;Cavalli et al, 2002;Cianchetta et al, 2005;Coi et al, 2006;Diller and Hobbs, 2007;Du et al, 2004Du et al, , 2007Ekins et al, 2002Ekins et al, , 2006Fioravanzo et al, 2004;Guth, 2007;Johnson et al, 2007;Keserü, 2003;Pearlstein et al, 2003;Seierstad and Agrafiotis, 2006;Thai and Ecker, 2008) or classification methods (Aronov and Goldman, 2004;Aronov, 2005;Dubus et al, 2006;Gepp and Hutter, 2006;Guth, 2007;Leong, 2007;Li et al, 2008;Song and Clark, 2006;Sun, 2006;Tobita et al, 2005;Waring and Johnstone, 2007). The data quality and consistency is the crucial issue for the in silico models' quality and performance.…”

On the interpretation and interpretability of quantitative structure–activity relationship models

“…Indeed, it is highly probable that there is no 'best' solution to set composition, feature selection and modeling technique. Given these observations, it is all the more important to extract as much as we can from a QSAR model, though it is also true that all QSAR models are not designed to provide insight into the underlying SARs (such as filtering [12,18,25,55,87,109] models). In these cases, the underlying structureactivity relationship is usually well known.…”

“…The answer to this depends on the planned use of the model. For example, many QSAR models are built for filtering purposes [12,18,25,55,87,109], where the goal is to predict some property rapidly. Such models are generally used as screening tools, allowing one to prioritize molecules from large libraries.…”