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V. Kasam, M. Zimmermann, A. Maass, H. Schwichtenberg, A. Wolf, N. Jacq, V. Breton and M. Hofmann- Apitius, “Design of New Plasmepsin Inhibitors: A Virtual High throughput Screening Approach on the EGEE Grid,” Journal of Chemical Information and Modelling, Vol. 47, No. 5, 2007, pp. 1818-1828. doi:10.1021/ci600451t

has been cited by the following article:

• TITLE: BEAR, a Molecular Docking Refinement and Rescoring Method

  AUTHORS: Andrew Anighoro, Giulio Rastelli

  KEYWORDS: Virtual Screening; Bear; Structure-Based Drug Design

  JOURNAL NAME: Computational Molecular Bioscience, Vol.3 No.2, June 10, 2013

  ABSTRACT: BEAR (Binding Estimation After Refinement) is a computational method for structure-based virtual screening. It was set up as a post-docking processing tool for the refinement of ligand binding modes predicted by molecular docking programs and the accurate evaluation of free energies of binding. BEAR has been validated in a number of computational drug discovery applications. It performed well in discriminating active ligands with respect to molecular decoys of biological targets belonging to different protein families as well as in discovering biologically active hits. Recently, it has also been validated in the emerging field of G-protein coupled receptors structure based virtual screening.