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      Reproducing the conformations of protein-bound ligands: a critical evaluation of several popular conformational searching tools.

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      Journal of computer-aided molecular design
      Springer Science and Business Media LLC

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          Abstract

          Several programs (Catalyst, Confort, Flo99, MacroModel, and Omega) that are commonly used to generate conformational ensembles have been tested for their ability to reproduce bioactive conformations. The ligands from thirty-two different ligand-protein complexes determined by high-resolution (< 2.0 A) X-ray crystallography have been analyzed. The Low-Mode Conformational Search method (with AMBER* and the GB/SA hydration model), as implemented in MacroModel, was found to perform better than the other algorithms. The rule-based method Omega, which is orders of magnitude faster than the other methods, also gave reasonable results but were found to be dependent on the input structure. The methods supporting diverse sampling (Catalyst, Confort) performed least well. For the seven ligands in the set having eight or more rotatable bonds, none of the bioactive conformations were ever found, save for one exception (Flo99). These ligands do not bind in a local minimum conformation according to AMBER*\GB/SA. Taking these last two observations together, it is clear that geometrically similar structures should be collected in order to increase the probability of finding the bioactive conformation among the generated ensembles. Factors influencing bioactive conformational retrieval have been identified and are discussed.

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          Author and article information

          Journal
          J Comput Aided Mol Des
          Journal of computer-aided molecular design
          Springer Science and Business Media LLC
          0920-654X
          0920-654X
          Dec 2001
          : 15
          : 12
          Affiliations
          [1 ] Department of Medicinal Chemistry, AstraZeneca R & D Mölndal, Sweden. jonas.bostrom@astrazeneca.com
          Article
          10.1023/a:1015930826903
          12160095
          f728e7d2-aa63-491b-8bf8-4380e4737afa
          History

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