Automatic generation of alignments for 3D QSAR analyses.

Many 3D QSAR methods require the alignment of the molecules in a dataset, which can require a fair amount of manual effort in deciding upon a rational basis for the superposition. This paper describes the use of FBSS, a program for field-based similarity searching in chemical databases, for generating such alignments automatically. The CoMFA and CoMSIA experiments with several literature datasets show that the QSAR models resulting from the FBSS alignments are broadly comparable in predictive performance with the models resulting from manual alignments.

[1]  C. Lemmen,et al.  FLEXS: a method for fast flexible ligand superposition. , 1998, Journal of medicinal chemistry.

[2]  G. Klebe,et al.  Molecular similarity indices in a comparative analysis (CoMSIA) of drug molecules to correlate and predict their biological activity. , 1994, Journal of medicinal chemistry.

[3]  Simon K. Kearsley,et al.  An alternative method for the alignment of molecular structures: Maximizing electrostatic and steric overlap , 1990 .

[4]  G Klebe,et al.  Three-dimensional quantitative structure-activity relationship analyses using comparative molecular field analysis and comparative molecular similarity indices analysis to elucidate selectivity differences of inhibitors binding to trypsin, thrombin, and factor Xa. , 1999, Journal of medicinal chemistry.

[5]  Jordi Mestres,et al.  MIMIC: A molecular‐field matching program. Exploiting applicability of molecular similarity approaches , 1997 .

[6]  A. Tasker,et al.  2,4-Diarylpyrrolidine-3-carboxylic acids--potent ETA selective endothelin receptor antagonists. 1. Discovery of A-127722. , 1996, Journal of medicinal chemistry.

[7]  Eugene A. Coats,et al.  The CoMFA Steroids as a Benchmark Dataset for Development of 3D QSAR Methods , 1998 .

[8]  M. Langlois,et al.  Three-dimensional quantitative structure-activity relationship of melatonin receptor ligands: a comparative molecular field analysis study. , 1997, Journal of medicinal chemistry.

[9]  Peter Willett,et al.  Similarity Searching in Files of Three-Dimensional Chemical Structures: Analysis of the BIOSTER Database Using Two-Dimensional Fingerprints and Molecular Field Descriptors , 2000, J. Chem. Inf. Comput. Sci..

[10]  W. G. Richards,et al.  Rapid evaluation of shape similarity using Gaussian functions , 1993, J. Chem. Inf. Comput. Sci..

[11]  Ramon Carbo,et al.  How similar is a molecule to another? An electron density measure of similarity between two molecular structures , 1980 .

[12]  Andrew C. Good,et al.  Utilization of Gaussian functions for the rapid evaluation of molecular similarity , 1992, J. Chem. Inf. Comput. Sci..

[13]  Bruce L. Bush,et al.  Sample-distance partial least squares: PLS optimized for many variables, with application to CoMFA , 1993, J. Comput. Aided Mol. Des..

[14]  J. Gasteiger,et al.  Autocorrelation of Molecular Surface Properties for Modeling Corticosteroid Binding Globulin and Cytosolic Ah Receptor Activity by Neural Networks , 1995 .

[15]  R. Cramer,et al.  Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. , 1988, Journal of the American Chemical Society.

[16]  Peter Willett,et al.  Similarity Searching in Files of Three-Dimensional Chemical Structures. Alignment of Molecular Electrostatic Potential Fields with a Genetic Algorithm , 1996, J. Chem. Inf. Comput. Sci..

[17]  Gerhard Klebe,et al.  Comparative Molecular Similarity Indices Analysis: CoMSIA , 1998 .

[18]  W. Graham Richards,et al.  Alignment of molecules by the Monte Carlo optimization of molecular similarity indices , 1997 .

[19]  Patrick Gaillard,et al.  Molecular Lipophilicity Potential, a tool in 3D QSAR: Method and applications , 1994, J. Comput. Aided Mol. Des..

[20]  J. V. van Lier,et al.  Quantitative structure-activity relationships/comparative molecular field analysis (QSAR/CoMFA) for receptor-binding properties of halogenated estradiol derivatives. , 1994, Journal of medicinal chemistry.

[21]  H. Kubinyi,et al.  3D QSAR in drug design. , 2002 .

[22]  Peter Willett,et al.  Effect of Parameter Variations on the Effectiveness of HQSAR Analyses , 1999 .

[23]  V. Kulkarni,et al.  Three-dimensional quantitative structure-activity relationship of interleukin 1-beta converting enzyme inhibitors: A comparative molecular field analysis study. , 1999, Journal of medicinal chemistry.

[24]  R E Wilcox,et al.  CoMFA-based prediction of agonist affinities at recombinant D1 vs D2 dopamine receptors. , 1998, Journal of medicinal chemistry.

[25]  J. D. Petke Cumulative and discrete similarity analysis of electrostatic potentials and fields , 1993, J. Comput. Chem..

[26]  Matthew Clark,et al.  Comparative molecular field analysis (CoMFA). 2. Toward its use with 3D-structural databases , 1990 .

[27]  Thomas G. Dietterich,et al.  Compass: A shape-based machine learning tool for drug design , 1994, J. Comput. Aided Mol. Des..

[28]  S. Wold,et al.  Comparative molecular field analysis , 1991 .

[29]  A. M. Doweyko,et al.  The hypothetical active site lattice — in vitro and in vivo explorations using a three-dimensional QSAR technique , 1991 .

[30]  Peter Willett,et al.  Similarity Searching in Files of Three-Dimensional Chemical Structures: Flexible Field-Based Searching of Molecular Electrostatic Potentials , 1996, J. Chem. Inf. Comput. Sci..