Using a genetic algorithm to identify common structural features in sets of ligands.

This article describes a program for pharmacophore mapping, called MPHIL (Mapping Pharmacophores in Ligands). Given as input a set of molecules that exhibit some common biological activity, MPHIL identifies the smallest 3D pattern of pharmacophore points that has at least m (a user-defined parameter) points in common with each of the input molecules. The program thus differs from existing programs for pharmacophore mapping in that it does not require all of the molecules to share exactly the same pattern of points, although it will find such a common pattern if it does, indeed, exist. MPHIL uses a genetic algorithm (GA) approach in which an initial, and very rapid, GA is used to suggest possible combinations of points that are then processed by the second GA to yield the final 3D pattern.

[1]  Peter Willett,et al.  Algorithms for the identification of three-dimensional maximal common substructures , 1987, J. Chem. Inf. Comput. Sci..

[2]  Tad Hurst,et al.  Flexible 3D searching: The directed tweak technique , 1994, J. Chem. Inf. Comput. Sci..

[3]  Ronan Bureau,et al.  Comparative molecular field analysis of CCK-A antagonists using field-fit as an alignment technique. A convenient guide to design new CCK-A ligands , 1992, J. Comput. Aided Mol. Des..

[4]  G J Williams,et al.  The Protein Data Bank: a computer-based archival file for macromolecular structures. , 1977, Journal of molecular biology.

[5]  C. Bron,et al.  Algorithm 457: finding all cliques of an undirected graph , 1973 .

[6]  Thomas E. Moock,et al.  Conformational searching in ISIS/3D databases , 1994, J. Chem. Inf. Comput. Sci..

[7]  D. Livingstone,et al.  Structure-activity relationships of antifilarial antimycin analogues: a multivariate pattern recognition study. , 1990, Journal of medicinal chemistry.

[8]  P. Willett.  Genetic algorithms in molecular recognition and design. , 1995, Trends in biotechnology.

[9]  Peter Willett,et al.  Hyperstructure model for chemical structure handling: generation and atom-by-atom searching of hyperstructures , 1992, J. Chem. Inf. Comput. Sci..

[10]  David E. Clark,et al.  Evolutionary algorithms in computer-aided molecular design , 1996, J. Comput. Aided Mol. Des..

[11]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[12]  Yvonne C. Martin,et al.  A fast new approach to pharmacophore mapping and its application to dopaminergic and benzodiazepine agonists , 1993, J. Comput. Aided Mol. Des..

[13]  Andrew Smellie,et al.  Identification of Common Functional Configurations Among Molecules , 1996, J. Chem. Inf. Comput. Sci..

[14]  Garland R. Marshall,et al.  3D-QSAR of angiotensin-converting enzyme and thermolysin inhibitors: A comparison of CoMFA models based on deduced and experimentally determined active site geometries , 1993 .

[15]  C. Humblet,et al.  Generation of N-methyl-D-aspartate agonist and competitive antagonist pharmacophore models. Design and synthesis of phosphonoalkyl-substituted tetrahydroisoquinolines as novel antagonists. , 1992, Journal of medicinal chemistry.