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Superposition of three-dimensional chemical structures allowing for conformational flexibility by a hybrid method.

Superposition of three-dimensional chemical structures allowing for conformational flexibility by... The superposition of three-dimensional structures is the first task in the evaluation of the largest common three-dimensional substructure of a set of molecules. This is an important step in the identification of a pharmacophoric pattern for molecules that bind to the same receptor. The superposition method described here combines a genetic algorithm with a numerical optimization method. A major goal is to adequately address the conformational flexibility of ligand molecules. The genetic algorithm optimizes in a nondeterministic process the size and the geometric fit of the substructures. The geometric fit is further improved by changing torsional angles combining the genetic algorithm and the directed tweak method. This directed tweak method is based on a numerical quasi-Newton optimization method. Only one starting conformation per molecule is necessary. Molecules having several rotatable bonds and quite different initial conformations are modified to find large structural similarities. A set of angiotensin II antagonists is investigated to illustrate the performance of the method. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Chemical Information and Computer Sciences Pubmed

Superposition of three-dimensional chemical structures allowing for conformational flexibility by a hybrid method.

Journal of Chemical Information and Computer Sciences , Volume 38 (2): 13 – Apr 28, 1998

Superposition of three-dimensional chemical structures allowing for conformational flexibility by a hybrid method.


Abstract

The superposition of three-dimensional structures is the first task in the evaluation of the largest common three-dimensional substructure of a set of molecules. This is an important step in the identification of a pharmacophoric pattern for molecules that bind to the same receptor. The superposition method described here combines a genetic algorithm with a numerical optimization method. A major goal is to adequately address the conformational flexibility of ligand molecules. The genetic algorithm optimizes in a nondeterministic process the size and the geometric fit of the substructures. The geometric fit is further improved by changing torsional angles combining the genetic algorithm and the directed tweak method. This directed tweak method is based on a numerical quasi-Newton optimization method. Only one starting conformation per molecule is necessary. Molecules having several rotatable bonds and quite different initial conformations are modified to find large structural similarities. A set of angiotensin II antagonists is investigated to illustrate the performance of the method.

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ISSN
0095-2338
DOI
10.1021/ci970438r
pmid
9538519

Abstract

The superposition of three-dimensional structures is the first task in the evaluation of the largest common three-dimensional substructure of a set of molecules. This is an important step in the identification of a pharmacophoric pattern for molecules that bind to the same receptor. The superposition method described here combines a genetic algorithm with a numerical optimization method. A major goal is to adequately address the conformational flexibility of ligand molecules. The genetic algorithm optimizes in a nondeterministic process the size and the geometric fit of the substructures. The geometric fit is further improved by changing torsional angles combining the genetic algorithm and the directed tweak method. This directed tweak method is based on a numerical quasi-Newton optimization method. Only one starting conformation per molecule is necessary. Molecules having several rotatable bonds and quite different initial conformations are modified to find large structural similarities. A set of angiotensin II antagonists is investigated to illustrate the performance of the method.

Journal

Journal of Chemical Information and Computer SciencesPubmed

Published: Apr 28, 1998

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