Literature DB >> 9704300

Comparison of algorithms for dissimilarity-based compound selection.

M Snarey1, N K Terrett, P Willett, D J Wilton.   

Abstract

Dissimilarity-based compound selection has been suggested as an effective method for selecting structurally diverse subsets of chemical databases. This article reports a comparison of several maximum-dissimilarity and sphere-exclusion algorithms for dissimilarity-based selection. The effectiveness of the algorithms is quantified by the numbers of biological activity classes identified in subsets selected from the World Drugs Index database, and by the numbers of active compounds identified in feedback searches of this database. The experiments demonstrate the general effectiveness and efficiency of the MaxMin algorithm.

Mesh:

Substances:

Year:  1997        PMID: 9704300     DOI: 10.1016/s1093-3263(98)00008-4

Source DB:  PubMed          Journal:  J Mol Graph Model        ISSN: 1093-3263            Impact factor:   2.518


  13 in total

1.  Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection.

Authors:  Alexander Golbraikh; Alexander Tropsha
Journal:  J Comput Aided Mol Des       Date:  2002 May-Jun       Impact factor: 3.686

2.  Analysis of selection methodologies for combinatorial library design.

Authors:  Rosalia Pascual; José I Borrell; Jordi Teixidó
Journal:  Mol Divers       Date:  2003       Impact factor: 2.943

3.  Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection.

Authors:  Alexander Golbraikh; Alexander Tropsha
Journal:  Mol Divers       Date:  2002       Impact factor: 2.943

4.  Rational selection of training and test sets for the development of validated QSAR models.

Authors:  Alexander Golbraikh; Min Shen; Zhiyan Xiao; Yun-De Xiao; Kuo-Hsiung Lee; Alexander Tropsha
Journal:  J Comput Aided Mol Des       Date:  2003 Feb-Apr       Impact factor: 3.686

5.  ProPose: a docking engine based on a fully configurable protein-ligand interaction model.

Authors:  Markus H J Seifert; Frank Schmitt; Thomas Herz; Bernd Kramer
Journal:  J Mol Model       Date:  2004-10-08       Impact factor: 1.810

6.  Analysis and use of fragment-occurrence data in similarity-based virtual screening.

Authors:  Shereena M Arif; John D Holliday; Peter Willett
Journal:  J Comput Aided Mol Des       Date:  2009-06-18       Impact factor: 3.686

7.  The multiple roles of computational chemistry in fragment-based drug design.

Authors:  Richard Law; Oliver Barker; John J Barker; Thomas Hesterkamp; Robert Godemann; Ole Andersen; Tara Fryatt; Steve Courtney; Dave Hallett; Mark Whittaker
Journal:  J Comput Aided Mol Des       Date:  2009-06-17       Impact factor: 3.686

8.  Comparative virtual screening and novelty detection for NMDA-GlycineB antagonists.

Authors:  Bjoern A Krueger; Tanja Weil; Gisbert Schneider
Journal:  J Comput Aided Mol Des       Date:  2009-11-05       Impact factor: 3.686

9.  Antitumor agents 252. Application of validated QSAR models to database mining: discovery of novel tylophorine derivatives as potential anticancer agents.

Authors:  Shuxing Zhang; Linyi Wei; Ken Bastow; Weifan Zheng; Arnold Brossi; Kuo-Hsiung Lee; Alexander Tropsha
Journal:  J Comput Aided Mol Des       Date:  2007-03-06       Impact factor: 3.686

10.  Selecting molecules with diverse structures and properties by maximizing submodular functions of descriptors learned with graph neural networks.

Authors:  Tomohiro Nakamura; Shinsaku Sakaue; Kaito Fujii; Yu Harabuchi; Satoshi Maeda; Satoru Iwata
Journal:  Sci Rep       Date:  2022-01-21       Impact factor: 4.996

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.