Novel application of the CORAL software to model cytotoxicity of metal oxide nanoparticles to bacteria Escherichia coli.
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Jerzy Leszczynski | Emilio Benfenati | Giuseppina Gini | Tomasz Puzyn | Danuta Leszczynska | Andrey A Toropov | Alla P Toropova | T. Puzyn | G. Gini | E. Benfenati | J. Leszczynski | D. Leszczyńska | A. Toropova | A. Toropov
[1] J C Madden,et al. An evaluation of global QSAR models for the prediction of the toxicity of phenols to Tetrahymena pyriformis. , 2008, Chemosphere.
[2] Igor V Tetko,et al. Calculation of lipophilicity for Pt(II) complexes: experimental comparison of several methods , 2008, Chemistry Central Journal.
[3] Jerzy Leszczynski,et al. Bionanoscience: Nano meets bio at the interface. , 2010, Nature nanotechnology.
[4] Jerzy Leszczynski,et al. QSAR modeling of measured binding affinity for fullerene-based HIV-1 PR inhibitors by CORAL , 2010 .
[5] Douglas J. Klein,et al. Modeling the bioconcentration factors and bioaccumulation factors of polychlorinated biphenyls with posetic quantitative super-structure/activity relationships (QSSAR) , 2006, Molecular Diversity.
[6] Jerzy Leszczynski,et al. CORAL: QSPR models for solubility of [C60] and [C70] fullerene derivatives , 2011, Molecular Diversity.
[7] I. Gutman,et al. Relation between second and third geometric–arithmetic indices of trees , 2011 .
[8] K. Roy,et al. Exploring quantitative structure–activity relationship studies of antioxidant phenolic compounds obtained from traditional Chinese medicinal plants , 2010 .
[9] V. I. Yukalov,et al. Extrapolation and interpolation of asymptotic series by self-similar approximants , 2010, 1004.1041.
[10] Iva B. Stoyanova-Slavova,et al. QSAR modeling, synthesis and bioassay of diverse leukemia RPMI-8226 cell line active agents. , 2010, European journal of medicinal chemistry.
[11] M. Randic. Novel graph theoretical approach to heteroatoms in quantitative structure—activity relationships , 1991 .
[12] Mamta Thakur,et al. Study on supramolecular complexing ability vis-à-vis estimation of pKa of substituted sulfonamides: dominating role of Balaban index (J). , 2005, Bioorganic & medicinal chemistry letters.
[13] S. Basak. Role of mathematical chemodescriptors and proteomics‐based biodescriptors in drug discovery , 2011 .
[14] Paola Gramatica,et al. Are Mechanistic and Statistical QSAR Approaches Really Different? MLR Studies on 158 Cycloalkyl‐Pyranones , 2010, Molecular informatics.
[15] N. Trinajstic,et al. Comparison between first geometric–arithmetic index and atom-bond connectivity index , 2010 .
[16] A combined use of global and local approaches in 3D-QSAR , 2000 .
[17] Jerzy Leszczynski,et al. Using nano-QSAR to predict the cytotoxicity of metal oxide nanoparticles. , 2011, Nature nanotechnology.
[18] Jerzy Leszczynski,et al. SMILES‐based optimal descriptors: QSAR analysis of fullerene‐based HIV‐1 PR inhibitors by means of balance of correlations , 2009, J. Comput. Chem..
[19] George Kollias,et al. Ligand-based virtual screening procedure for the prediction and the identification of novel β-amyloid aggregation inhibitors using Kohonen maps and Counterpropagation Artificial Neural Networks. , 2011, European journal of medicinal chemistry.
[20] Jerzy Leszczynski,et al. InChI-based optimal descriptors: QSAR analysis of fullerene[C60]-based HIV-1 PR inhibitors by correlation balance. , 2010, European journal of medicinal chemistry.
[21] E. Castro,et al. Quantitative structure–spectral property relationships for functional groups of novel 1,2,5-thiadiazole compounds , 2011 .