Self-organizing neural networks for modeling robust 3D and 4D QSAR: application to dihydrofolate reductase inhibitors.

We have used SOM and grid 3D and 4D QSAR schemes for modeling the activity of a series of dihydrofolate reductase inhibitors. Careful analysis of the performance and external predictivities proves that this method can provide an efficient inhibition model.

[1]  Jaroslaw Polanski,et al.  Modeling Steric and Electronic Effects in 3D- and 4D-QSAR Schemes: Predicting Benzoic pKa Values and Steroid CBG Binding Affinities , 2003, J. Chem. Inf. Comput. Sci..

[2]  Nenad Trinajstic,et al.  Nonlinear Multivariate Regression Outperforms Several Concisely Designed Neural Networks on Three QSPR Data Sets , 2000, J. Chem. Inf. Comput. Sci..

[3]  Jaroslaw Polanski,et al.  The Comparative Molecular Surface Analysis (CoMSA) with Modified Uniformative Variable Elimination-PLS (UVE-PLS) Method: Application to the Steroids Binding the Aromatase Enzyme , 2003, J. Chem. Inf. Comput. Sci..

[4]  Nenad Trinajstic,et al.  Multivariate Regression Outperforms Several Robust Architectures of Neural Networks in QSAR Modeling , 1999, J. Chem. Inf. Comput. Sci..

[5]  Jaroslaw Polanski,et al.  Self-organizing neural networks for pharmacophore mapping. , 2003, Advanced drug delivery reviews.

[6]  Jaroslaw Polanski,et al.  Comparative molecular surface analysis: A novel tool for drug design and molecular diversity studies , 2004, Molecular Diversity.

[7]  M. G. Finn,et al.  Click Chemistry: Diverse Chemical Function from a Few Good Reactions. , 2001, Angewandte Chemie.

[8]  Alan R. Katritzky,et al.  A New Efficient Approach for Variable Selection Based on Multiregression: Prediction of Gas Chromatographic Retention Times and Response Factors , 1999, J. Chem. Inf. Comput. Sci..

[9]  Jens Sadowski,et al.  The Use of Self-organizing Neural Networks in Drug Design , 2002 .

[10]  Teuvo Kohonen,et al.  Self-Organization and Associative Memory , 1988 .

[11]  Jaroslaw Polanski,et al.  Mapping dye pharmacophores by the Comparative Molecular Surface Analysis (CoMSA): application to heterocyclic monoazo dyes , 2004 .

[12]  Jaroslaw Polanski,et al.  GRID Formalism for the Comparative Molecular Surface Analysis: Application to the CoMFA Benchmark Steroids, Azo Dyes, and HEPT Derivatives , 2004, J. Chem. Inf. Model..

[13]  Nenad Trinajstic,et al.  Use of Variable Selection in Modeling the Secondary Structural Content of Proteins from Their Composition of Amino Acid Residues , 2004, J. Chem. Inf. Model..

[14]  Johann Gasteiger,et al.  Neural networks in chemistry and drug design , 1999 .

[15]  Desire L. Massart,et al.  Detection of inhomogeneities in sets of NIR spectra , 1996 .

[16]  D. Massart,et al.  Elimination of uninformative variables for multivariate calibration. , 1996, Analytical chemistry.

[17]  Teuvo Kohonen,et al.  The self-organizing map , 1990, Neurocomputing.

[18]  G Schneider,et al.  Artificial neural networks for computer-based molecular design. , 1998, Progress in biophysics and molecular biology.

[19]  F. Burden,et al.  Robust QSAR models using Bayesian regularized neural networks. , 1999, Journal of medicinal chemistry.

[20]  Jaroslaw Polanski,et al.  The Comparative Molecular Surface Analysis (COMSA): A Novel Tool for Molecular Design , 2000, Comput. Chem..

[21]  Jaroslaw Polanski,et al.  The Comparative Molecular Surface Analysis (COMSA) — A Nongrid 3D QSAR Method by a Coupled Neural Network and PLS System: Predicting pKa Values of Benzoic and Alkanoic Acids. , 2002 .

[22]  Gerrit Kateman,et al.  USING ARTIFICIAL NEURAL NETWORKS FOR SOLVING CHEMICAL PROBLEMS .2. KOHONEN SELF-ORGANIZING FEATURE MAPS AND HOPFIELD NETWORKS , 1994 .

[23]  Jaroslaw Polanski,et al.  The Comparative Molecular Surface Analysis (COMSA) - A Nongrid 3D QSAR Method by a Coupled Neural Network and PLS System: Predicting pKa Values of Benzoic and Alkanoic Acids , 2002, J. Chem. Inf. Comput. Sci..

[24]  J Polanski,et al.  Self-organizing neural networks for screening and development of novel artificial sweetener candidates. , 2000, Combinatorial chemistry & high throughput screening.

[25]  Jaroslaw Polanski,et al.  Comparative Molecular Surface Analysis (CoMSA) for Modeling Dye-Fiber Affinities of the Azo and Anthraquinone Dyes , 2003, J. Chem. Inf. Comput. Sci..

[26]  Teuvo Kohonen,et al.  Self-organization and associative memory: 3rd edition , 1989 .

[27]  A. Hopfinger,et al.  Construction of 3D-QSAR Models Using the 4D-QSAR Analysis Formalism , 1997 .

[28]  Jaroslaw Polanski,et al.  Probability issues in molecular design: predictive and modeling ability in 3D-QSAR schemes. , 2004, Combinatorial chemistry & high throughput screening.