Literature DB >> 8690757

Identification of common functional configurations among molecules.

D Barnum1, J Greene, A Smellie, P Sprague.   

Abstract

A new algorithm for identifying three-dimensional configurations of chemical features common to a set of molecules is described. The algorithm scores each configuration based both on the degree to which it is common to the input set and its estimated rarity. The algorithm can be applied to molecules with large (several hundred) conformational models. Results from the application of this algorithm to three data sets are discussed: PAF antagonists, HIV reverse transcriptase inhibitors, and HIV protease inhibitors. Of particular interest is a common configuration identified for a set of HIV reverse transcriptase inhibitors; this configuration is shared by two new, potent inhibitors that were recently described in the literature.

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Year:  1996        PMID: 8690757     DOI: 10.1021/ci950273r

Source DB:  PubMed          Journal:  J Chem Inf Comput Sci        ISSN: 0095-2338


  59 in total

1.  Neuronal nicotinic receptor agonists: a multi-approach development of the pharmacophore.

Authors:  O Nicolotti; M Pellegrini-Calace; A Carrieri; C Altomare; N B Centeno; F Sanz; A Carotti
Journal:  J Comput Aided Mol Des       Date:  2001-09       Impact factor: 3.686

2.  A comparison of the pharmacophore identification programs: Catalyst, DISCO and GASP.

Authors:  Yogendra Patel; Valerie J Gillet; Gianpaolo Bravi; Andrew R Leach
Journal:  J Comput Aided Mol Des       Date:  2002 Aug-Sep       Impact factor: 3.686

3.  Internally defined distances in 3D-quantitative structure-activity relationships.

Authors:  Christian Th Klein; Norbert Kaiblinger; Peter Wolschann
Journal:  J Comput Aided Mol Des       Date:  2002-02       Impact factor: 3.686

4.  Chemical space: missing pieces in cheminformatics.

Authors:  Sean Ekins; Rishi R Gupta; Eric Gifford; Barry A Bunin; Chris L Waller
Journal:  Pharm Res       Date:  2010-08-04       Impact factor: 4.200

5.  Generation of multiple pharmacophore hypotheses using multiobjective optimisation techniques.

Authors:  Simon J Cottrell; Valerie J Gillet; Robin Taylor; David J Wilton
Journal:  J Comput Aided Mol Des       Date:  2004-11       Impact factor: 3.686

6.  PHASE: a new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results.

Authors:  Steven L Dixon; Alexander M Smondyrev; Eric H Knoll; Shashidhar N Rao; David E Shaw; Richard A Friesner
Journal:  J Comput Aided Mol Des       Date:  2006-11-24       Impact factor: 3.686

7.  Incorporating partial matches within multi-objective pharmacophore identification.

Authors:  Simon J Cottrell; Valerie J Gillet; Robin Taylor
Journal:  J Comput Aided Mol Des       Date:  2007-01-04       Impact factor: 3.686

Review 8.  Pharmacophore-based discovery of ligands for drug transporters.

Authors:  Cheng Chang; Sean Ekins; Praveen Bahadduri; Peter W Swaan
Journal:  Adv Drug Deliv Rev       Date:  2006-09-26       Impact factor: 15.470

9.  Common pharmacophore identification using frequent clique detection algorithm.

Authors:  Yevgeniy Podolyan; George Karypis
Journal:  J Chem Inf Model       Date:  2009-01       Impact factor: 4.956

10.  Deterministic pharmacophore detection via multiple flexible alignment of drug-like molecules.

Authors:  Dina Schneidman-Duhovny; Oranit Dror; Yuval Inbar; Ruth Nussinov; Haim J Wolfson
Journal:  J Comput Biol       Date:  2008-09       Impact factor: 1.479

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