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Evaluation of the EVA Descriptor for QSAR Studies: 3. The use of a Genetic Algorithm to Search for Models with Enhanced Predictive Properties (EVA_GA)

Turner, D.B. and Willett, P. (2000) Evaluation of the EVA Descriptor for QSAR Studies: 3. The use of a Genetic Algorithm to Search for Models with Enhanced Predictive Properties (EVA_GA). Journal of Computer-Aided Molecular Design, 14 (1). pp. 1-21. ISSN 1573-4951

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The EVA structural descriptor, based upon calculated fundamental molecular vibrational frequencies, has proved to be an effective descriptor for both QSAR and database similarity calculations. The descriptor is sensitive to 3D structure but has an advantage over field-based 3D-QSAR methods inasmuch as structural superposition is not required. The original technique involves a standardisation method wherein uniform Gaussians of fixed standard deviation (σ) are used to smear out frequencies projected onto a linear scale. This smearing function permits the overlap of proximal frequencies and thence the extraction of a fixed dimensional descriptor regardless of the number and precise values of the frequencies. It is proposed here that there exist optimal localised values of σ in different spectral regions; that is, the overlap of frequencies using uniform Gaussians may, at certain points in the spectrum, either be insufficient to pick up relationships where they exist or mix up information to such an extent that significant correlations are obscured by noise. A genetic algorithm is used to search for optimal localised σ values using crossvalidated PLS regression scores as the fitness score to be optimised. The resultant models are then validated against a previously unseen test set of compounds. The performance of EVA_GA is compared to that of EVA and analogous CoMFA studies.

Item Type: Article
Copyright, Publisher and Additional Information: © 2000 Kluwer Academic Publishers. This is an author produced version of a paper published in Journal of Computer-Aided Molecular Design.
Keywords: AM1, CoMFA, GA, MM3, molecular vibration, variable modification
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield)
The University of Sheffield > University of Sheffield Research Centres and Institutes > The Krebs Institute for Biomolecular Research (Sheffield)
Depositing User: Repository Officer
Date Deposited: 15 Aug 2006
Last Modified: 05 Jun 2014 12:05
Published Version: http://dx.doi.org/10.1023/A:1008180020974
Status: Published
Publisher: Springer Netherlands
Refereed: Yes
Identification Number: 10.1023/A:1008180020974
URI: http://eprints.whiterose.ac.uk/id/eprint/175

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