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Summary: Research Article
A QSAR Model of hERG Binding Using a Large,
Diverse, and Internally Consistent Training Set
Mark Seierstad* and Dimitris K.
Agrafiotis
Johnson & Johnson Pharmaceutical Research & Development,
L.L.C., 3210 Merryfield Row, San Diego, CA 92121, USA
*Corresponding author: Mark Seierstad, mseierst@prdus.jnj.com
Present address: Johnson & Johnson Pharmaceutical Research &
Development, L.L.C., 665 Stockton Drive, Exton, PA 19341, USA.
Over the past decade, the pharmaceutical industry
has begun to address an addition to ADME/Tox
profiling the ability of a compound to bind to
and inhibit the human ether-a-go-go-related gene
(hERG)-encoded cardiac potassium channel. With
the compilation of a large and diverse set of com-
pounds measured in a single, consistent hERG
channel inhibition assay, we recognized a unique
opportunity to attempt to construct predictive
QSAR models. Early efforts with classification
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