Literature DB >> 16995724

Assessment of molecular similarity from the analysis of randomly generated structural fragment populations.

José Batista1, Jeffrey W Godden, Jürgen Bajorath.   

Abstract

A novel method termed MolBlaster is introduced for the evaluation of molecular similarity relationships on the basis of randomly generated fragment populations. Our motivation has been to develop a similarity method that does not depend on the use of predefined structural or property descriptors. Fragment profiles of molecules are generated by random deletion of bonds in connectivity tables and quantitatively compared using entropy-based metrics. In test calculations, MolBlaster accurately reproduced a structural key-based similarity ranking of druglike molecules.

Mesh:

Year:  2006        PMID: 16995724     DOI: 10.1021/ci0601261

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  3 in total

1.  Distribution of randomly generated activity class characteristic substructures in diverse active and database compounds.

Authors:  José Batista; Jürgen Bajorath
Journal:  Mol Divers       Date:  2008-05-28       Impact factor: 2.943

2.  Data mining using template-based molecular docking on tetrahydroimidazo-[4,5,1-jk][1,4]-benzodiazepinone (TIBO) derivatives as HIV-1RT inhibitors.

Authors:  Nitin S Sapre; Swagata Gupta; Nilanjana Pancholi; Neelima Sapre
Journal:  J Mol Model       Date:  2008-07-19       Impact factor: 1.810

3.  A visual approach for analysis and inference of molecular activity spaces.

Authors:  Samina Kausar; Andre O Falcao
Journal:  J Cheminform       Date:  2019-10-22       Impact factor: 5.514

  3 in total

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