Identification of Compounds with Nanomolar Binding Affinity for Checkpoint Kinase-1 Using Knowledge-Based Virtual Screening

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Abstract
A virtual screen of a subsection of the AstraZeneca compound collection was performed for checkpoint kinase-1 (Chk-1 kinase) using a knowledge-based strategy. This involved initial filtering of the compound collection by application of generic physical properties followed by removal of compounds with undesirable chemical functionality. Subsequently, a 3-D pharmacophore screen for compounds with kinase binding motifs was applied. A database of approximately 200K compounds remained for docking into the active site of Chk-1 kinase, using the FlexX-Pharm program. For each compound that docked successfully into the binding site, up to 100 poses were saved. These poses were then postfiltered using a customized consensus scoring scheme for a kinase, followed by visual inspection of a selection of the docked compounds. This resulted in 103 compounds being ordered for testing in the project assay, and 36 of these (corresponding to four chemical classes) were found to inhibit the enzyme in a dose−response fashion with IC50 values ranging from 110 nM to 68 μM.