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Seminar Abstract
February 2, 2005:
"Computational Approaches to Design of Metalloprotein Ligands"
Professor Stefan Balaz
Department of Pharmaceutical Sciences
North Dakota State University
The design of ligands that bind to metalloproteins with known experimental structures is complicated by two factors: structural similarities of metalloproteins and coordination bonds between the warhead metal-binding groups of ligands and the metal ions in the binding site. The first factor precludes application of virtual screening in the search for selective ligands. The second factor complicates the use of simulation methods, e.g., Monte Carlo or Molecular Dynamics (MD), for conformational sampling, due to the absence of readily available force fields for transition metals.
As a practical bypass to this problem, we use a five-tier procedure consisting of: (1) Similarity Analysis locating the selectivity hotspots in the binding sites; (2) restricted docking with the selection of poses based upon appropriate metal binding geometry; (3) quantum mechanical/molecular mechanical (QM/MM) optimization of the best docked geometries; (4) MD simulation with the metal binding group of the ligand confined in the geometry from step (2); (5) calculation of QM/MM single point energy of the time-averaged ligand-protein complex that is correlated, along with solvent-accessible surface area parametrizing desolvation, with experimental affinity.
The approach was applied to modeling of published inhibitory potencies of hydroxamate derivatives to matrix metalloproteinase 9 (MMP-9). Development of MMP inhibitors requires accurate binding affinity predictions due to structural relatedness of the MMP family, in which some members assume normal physiological roles and others are pathological, depending upon given concentration or activity. The results are satisfactory and robust.
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