Literature DB >> 24981486

Pharmacophore definition and 3D searches.

T Langer1, G Wolber2.   

Abstract

The most common pharmacophore building concepts based on either 3D structure of the target or ligand information are discussed together with the application of such models as queries for 3D database search. An overview of the key techniques available on the market is given and differences with respect to algorithms used and performance obtained are highlighted. Pharmacophore modelling and 3D database search are shown to be successful tools for enriching screening experiments aimed at the discovery of novel bio-active compounds.:
© 2004 Elsevier Ltd . All rights reserved.

Year:  2004        PMID: 24981486     DOI: 10.1016/j.ddtec.2004.11.015

Source DB:  PubMed          Journal:  Drug Discov Today Technol        ISSN: 1740-6749


  12 in total

1.  Development of pharmacophore models for small molecules targeting RNA: Application to the RNA repeat expansion in myotonic dystrophy type 1.

Authors:  Alicia J Angelbello; Àlex L González; Suzanne G Rzuczek; Matthew D Disney
Journal:  Bioorg Med Chem Lett       Date:  2016-10-13       Impact factor: 2.823

2.  Dynamic structure-based pharmacophore model development: a new and effective addition in the histone deacetylase 8 (HDAC8) inhibitor discovery.

Authors:  Sundarapandian Thangapandian; Shalini John; Yuno Lee; Songmi Kim; Keun Woo Lee
Journal:  Int J Mol Sci       Date:  2011-12-19       Impact factor: 5.923

3.  Molecular dynamics simulation study and hybrid pharmacophore model development in human LTA4H inhibitor design.

Authors:  Sundarapandian Thangapandian; Shalini John; Mahreen Arooj; Keun Woo Lee
Journal:  PLoS One       Date:  2012-04-05       Impact factor: 3.240

4.  Pharmacophore modeling, in silico screening, molecular docking and molecular dynamics approaches for potential alpha-delta bungarotoxin-4 inhibitors discovery.

Authors:  R Barani Kumar; M Xavier Suresh; B Shanmuga Priya
Journal:  Pharmacogn Mag       Date:  2015-05       Impact factor: 1.085

5.  Ligand Based Pharmacophore Modeling and Virtual Screening Studies to Design Novel HDAC2 Inhibitors.

Authors:  Naresh Kandakatla; Geetha Ramakrishnan
Journal:  Adv Bioinformatics       Date:  2014-11-26

6.  Discriminating agonist and antagonist ligands of the nuclear receptors using 3D-pharmacophores.

Authors:  Nathalie Lagarde; Solenne Delahaye; Jean-François Zagury; Matthieu Montes
Journal:  J Cheminform       Date:  2016-09-06       Impact factor: 5.514

7.  The discovery of a novel compound with potent antitumor activity: virtual screening, synthesis, biological evaluation and preliminary mechanism study.

Authors:  Yuanyuan Jin; Linhu Li; Zhaoyong Yang; Mingliang Liu; Huiyuan Guo; Weiyi Shen
Journal:  Oncotarget       Date:  2017-04-11

Review 8.  Predictive Power of In Silico Approach to Evaluate Chemicals against M. tuberculosis: A Systematic Review.

Authors:  Giulia Oliveira Timo; Rodrigo Souza Silva Valle Dos Reis; Adriana Françozo de Melo; Thales Viana Labourdette Costa; Pérola de Oliveira Magalhães; Mauricio Homem-de-Mello
Journal:  Pharmaceuticals (Basel)       Date:  2019-09-16

9.  Ligity: A Non-Superpositional, Knowledge-Based Approach to Virtual Screening.

Authors:  Jean-Paul Ebejer; Paul W Finn; Wing Ki Wong; Charlotte M Deane; Garrett M Morris
Journal:  J Chem Inf Model       Date:  2019-06-04       Impact factor: 4.956

Review 10.  Current computational methods for predicting protein interactions of natural products.

Authors:  Aurélien F A Moumbock; Jianyu Li; Pankaj Mishra; Mingjie Gao; Stefan Günther
Journal:  Comput Struct Biotechnol J       Date:  2019-10-28       Impact factor: 7.271

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