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Full molecular quantum similarity matrices as QSAR descriptors

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Molecular Quantum Similarity in QSAR and Drug Design

Part of the book series: Lecture Notes in Chemistry ((LNC,volume 73))

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Abstract

In this chapter, a scheme of the application of molecular quantum similarity matrices to describe a molecular property of interest is exposed. Quantum similarity matrices need to be conveniently transformed when employed as descriptor source in QSAR procedures. In order to describe the usual transformations, dimensionality reduction and variable selection techniques will be discussed. Combination of different quantum similarity matrices, constituting the Tuned QSAR model, is also discussed. Since the only relevant test for the procedure protocol is its application on real cases, quantum similarity matrices will be used to study three different molecular sets in order to provide the reader with reliable quantitative equations for activity prediction.

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Authors and Affiliations

  1. Institute of Computational Chemistry, Campus Montilivi, University of Girona, 1071, Girona, Spain

    Ramon Carbó-Dorca, David Robert, Lluís Amat, Xavier Gironés & Emili Besalú

Authors
  1. Ramon Carbó-Dorca
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  2. David Robert
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  3. Lluís Amat
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  4. Xavier Gironés
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  5. Emili Besalú
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© 2000 Springer-Verlag Berlin Heidelberg

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Carbó-Dorca, R., Robert, D., Amat, L., Gironés, X., Besalú, E. (2000). Full molecular quantum similarity matrices as QSAR descriptors. In: Molecular Quantum Similarity in QSAR and Drug Design. Lecture Notes in Chemistry, vol 73. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-57273-9_4

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  • DOI: https://doi.org/10.1007/978-3-642-57273-9_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67581-5

  • Online ISBN: 978-3-642-57273-9

  • eBook Packages: Springer Book Archive

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