Literature DB >> 7861411

Molecular similarity matrices and quantitative structure-activity relationships: a case study with methodological implications.

R Benigni1, M Cotta-Ramusino, F Giorgi, G Gallo.   

Abstract

Recently, statistical analysis of molecular similarity matrices has been applied to the quantitative structure-activity relationship (QSAR) analysis of a number of molecular series. This paper addresses a number of methodological issues relative to the similarity matrices. A series of halogenated aliphatic hydrocarbons, for which the mutation (aneuploidy) induction ability had previously been determined, was used as test bench. The chemical information carried by the similarity matrices was shown to overlap to a considerable extent the information carried by the classical descriptors (physical chemical and quantum mechanical parameters). A good QSAR was obtained on the basis of the similarity matrices, in analogy with that obtained with the classical descriptors; however, the similarity matrices neither complemented the classical descriptors nor were able to improve on their performance. The effect of the compound's spatial orientation on the similarity values was also investigated.

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Year:  1995        PMID: 7861411     DOI: 10.1021/jm00004a009

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  3 in total

1.  Determination of receptor-bound drug conformations by QSAR using flexible fitting to derive a molecular similarity index.

Authors:  C A Montanari; M S Tute; A E Beezer; J C Mitchell
Journal:  J Comput Aided Mol Des       Date:  1996-02       Impact factor: 3.686

2.  Similarity based SAR (SIBAR) as tool for early ADME profiling.

Authors:  Christian Klein; Dominik Kaiser; Stephan Kopp; Peter Chiba; Gerhard F Ecker
Journal:  J Comput Aided Mol Des       Date:  2002-11       Impact factor: 3.686

3.  Analysis and Comparison of Vector Space and Metric Space Representations in QSAR Modeling.

Authors:  Samina Kausar; Andre O Falcao
Journal:  Molecules       Date:  2019-04-30       Impact factor: 4.411

  3 in total

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