Inhibitors of HCV NS5B polymerase. Part 2: Evaluation of the northern region of (2Z)-2-benzoylamino-3-(4-phenoxy-phenyl)-acrylic acid.
ABSTRACT A novel series of non-nucleoside HCV NS5B polymerase inhibitors was prepared from a (2Z)-2-benzoylamino-3-(4-phenoxy-phenyl)-acrylic acid template. Solution and solid phase analog synthesis focused on the northern region of the template combined with structure based design led to the discovery of several potent and orally bioavailable lead compounds.
- Annual Reports in Medicinal Chemistry - ANNU REP MED CHEM. 01/2007; 42:281-300.
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ABSTRACT: A valid quantitative structure–activity relationship (QSAR) model was applied to predict IC50 value of pyridazinone derivatives as HCV NS5B protease inhibitors. Various chemical descriptors were calculated by E-Dragon. Six character variables were selected though stepwise multiple linear regression (stepwise-MLR), which included MATS6m, RDF055e, Mor31u, G3m, R1m and R4v +. In addition, twenty-three molecular descriptors were obtained via uninformative variable elimination by partial least squares (UVE-PLS). The selected descriptors using two approaches were basically the same type of molecular descriptors. Subsequently, Partial least squares (PLS) and particle swarm optimization support vector machine (PSO-SVM) were utilized to establish the linear and nonlinear models by two set of descriptors and their activity data, respectively. The predictive performance of the proposed models was evaluated by the strict criteria. The results showed that the predictive power of the PSO-SVM models were better than the corresponding PLS models. Thus, it can be inferred that the PSO-SVM models were robust and satisfactory, and could provide some feasible and effective information to design and synthesis of highly potent HCV NS5B polymerase inhibitors.Chemometrics and Intelligent Laboratory Systems 05/2014; · 2.38 Impact Factor
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ABSTRACT: The introduction of new anti-HCV drugs in the therapy is an imperative need and is necessary with a view to develop an interferon-free therapy. Thus, the discovery and the development of novel small molecule inhibitors of the viral NS5B polymerase represent an exciting area of research for many pharmaceutical companies and academic groups. This study represents a contribution to this field, and relies on the identification of the best NS5B model(s) to be used in structure-based computational approaches aimed at identifying novel non nucleoside inhibitors of one of the protein allosteric sites, namely palm site I. Firstly, the NS5B inhibitors at palm site I were classified as Water-Mediated or Non Water-Mediated ligands depending on their ability to interact with or displace a specific water molecule. Then, we took advantage of the available X-ray structures of NS5B/ligand complexes to build different models of protein/water combinations, which were used to investigate the influence on docking studies of solvent sites as well as of the influence of the protein conformations. As overall trend, we observed improved performance in the docking results of Water-Mediated Inhibitors by inclusion of explicit water molecules, with an opposite behavior generally happening for the Non Water-Mediated Inhibitors. The best performing target structures for the two ligand sets were then used for virtual screening simulations of a library containing the known NS5B inhibitors along with related decoys to assess the best performing targets ensembles on the basis of their ability to discriminate active and inactive compounds as well as to generate the correct binding modes. The parallel use of different protein structures/water sets outperformed the use of a single target structure, with the two-protein 3H98/2W-2FVC/7W and 3HKY/NoW-3SKE/NoW models resulting the best performing ensembles for Water-Mediated Inhibitors and Non Water-Mediated Inhibitors, respectively. The information gathered from this work confirms the primary role of water molecules and protein flexibility in docking-based studies, and can be exploited to aid NS5B-directed HCV drug discovery efforts.Journal of Chemical Information and Modeling 08/2013; · 4.30 Impact Factor