Description: Preface. Combination of molecular similarity measures using data fusion; C.M.R. Ginn, et al. Optimization of the drug-likeness of chemical libraries; J. Sadowski. Generating consistent sets of thermodynamic and structural data form analysis of protein-ligand interactions; T. Davies, et al. Multiple molecular superpositioning as an effective tool for virtual database screening; C. Lemmen, et al. A recursive algorithm for efficient combinatorial library docking; M. Rarey, T. Lengauer. Modifications of the scoring function in FlexX for virtual screening applications; M. Stahl. A knowledge-based scoring function for protein-ligand interactions: Probing the reference state; I. Muegge. Predicting binding modes, binding affinities and 'hot spots' for protein-ligand complexes using a knowledge-based scoring function; H. Gohlke, et al. Hydrophobicity maps and docking of molecular fragments with solvation; N. Majeux, et al. Virtual screening with solvation and ligand-induced complementarity; V. Schnecke, L.A. Kuhn. Similarity versus docking in 3 D virtual screening; J. Mestres, R.M.A. Knegtel. Discovering high-affinity ligands from the computationally predicted structures and affinities of small molecules bound to a target: A virtual screening approach; T.J. Marrone, et al. In vitro and in silico affinity fingerprints: Finding similarities beyond structural classes; H. Briem, U.F. Lessel. Computer-assisted synthesis and reaction planning in combinatorial chemistry; J. Gasteiger, et al. Evaluation of reactant-based and product-based approaches to the design of combinatorial libraries; V.J. Gillet, O. Nicolotti.

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