Document Type
Article
Publication Date
3-28-2016
Abstract
© 2016 American Chemical Society. The risk of serious bleeding is a major liability of anticoagulant drugs that are active-site competitive inhibitors targeting the Factor Xa (FXa) prothrombin (PT) binding site. The present work identifies several new classes of small molecule anticoagulants that can act as nonactive site inhibitors of the prothrombinase (PTase) complex composed of FXa and Factor Va (FVa). These new classes of anticoagulants were identified, using a novel agnostic computational approach to identify previously unrecognized binding pockets at the FXa-FVa interface. From about three million docking calculations of 281 128 compounds in a conformational ensemble of FXa heavy chains identified by molecular dynamics (MD) simulations, 97 compounds and their structural analogues were selected for experimental validation, through a series of inhibition assays. The compound selection was based on their predicted binding affinities to FXa and their ability to successfully bind to multiple protein conformations while showing selectivity for particular binding sites at the FXa/FVa interface. From these, thirty-one (31) compounds were experimentally identified as nonactive site inhibitors. Concentration-based assays further identified 10 compounds represented by four small-molecule families of inhibitors that achieve dose-independent partial inhibition of PTase activity in a nonactive site-dependent and self-limiting mechanism. Several compounds were identified for their ability to bind to protein conformations only seen during MD, highlighting the importance of accounting for protein flexibility in structure-based drug discovery approaches.
Publication Source (Journal or Book title)
Journal of Chemical Information and Modeling
First Page
535
Last Page
547
Recommended Citation
Kapoor, K., McGill, N., Peterson, C., Meyers, H., Blackburn, M., & Baudry, J. (2016). Discovery of Novel Nonactive Site Inhibitors of the Prothrombinase Enzyme Complex. Journal of Chemical Information and Modeling, 56 (3), 535-547. https://doi.org/10.1021/acs.jcim.5b00596