Literature DB >> 14754427

Predicting molecular interactions in silico: I. A guide to pharmacophore identification and its applications to drug design.

Oranit Dror1, Alexandra Shulman-Peleg, Ruth Nussinov, Haim J Wolfson.   

Abstract

A major goal in contemporary drug design is to develop new ligands with high affinity of binding toward a given protein receptor. Pharmacophore, which is the three-dimensional arrangement of essential features that enable a molecule to exert a particular biological effect, is a very useful model for achieving this goal. If the three dimensional structure of the receptor is known, pharmacophore is a complementary tool to standard techniques, such as docking. However, frequently the structure of the receptor protein is unknown and only a set of ligands together with their measured binding affinities towards the receptor is available. In such a case, a pharmacophore based strategy is one of the few applicable tools. Here we present a broad, yet concise guide to pharmacophore identification and review a sample of applications for drug design. In particular, we present the framework of the algorithms, classify their modules and point out their advantages and challenges.

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Year:  2004        PMID: 14754427     DOI: 10.2174/0929867043456287

Source DB:  PubMed          Journal:  Curr Med Chem        ISSN: 0929-8673            Impact factor:   4.530


  20 in total

Review 1.  Computer-aided drug discovery and development (CADDD): in silico-chemico-biological approach.

Authors:  I M Kapetanovic
Journal:  Chem Biol Interact       Date:  2006-12-16       Impact factor: 5.192

Review 2.  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

3.  First pharmacophore-based identification of androgen receptor down-regulating agents: discovery of potent anti-prostate cancer agents.

Authors:  Puranik Purushottamachar; Aakanksha Khandelwal; Pankaj Chopra; Neha Maheshwari; Lalji K Gediya; Tadas S Vasaitis; Robert D Bruno; Omoshile O Clement; Vincent C O Njar
Journal:  Bioorg Med Chem       Date:  2007-03-13       Impact factor: 3.641

4.  Identification of novel, less toxic PTP-LAR inhibitors using in silico strategies: pharmacophore modeling, SADMET-based virtual screening and docking.

Authors:  Dara Ajay; M Elizabeth Sobhia
Journal:  J Mol Model       Date:  2011-04-27       Impact factor: 1.810

5.  Ensemble pharmacophore meets ensemble docking: a novel screening strategy for the identification of RIPK1 inhibitors.

Authors:  S M Fayaz; G K Rajanikant
Journal:  J Comput Aided Mol Des       Date:  2014-07-01       Impact factor: 3.686

6.  An integrated approach to knowledge-driven structure-based virtual screening.

Authors:  Angela M Henzler; Sascha Urbaczek; Matthias Hilbig; Matthias Rarey
Journal:  J Comput Aided Mol Des       Date:  2014-07-04       Impact factor: 3.686

7.  In Silico Studies Targeting G-protein Coupled Receptors for Drug Research Against Parkinson's Disease.

Authors:  Agostinho Lemos; Rita Melo; Antonio Jose Preto; Jose Guilherme Almeida; Irina Sousa Moreira; Maria Natalia Dias Soeiro Cordeiro
Journal:  Curr Neuropharmacol       Date:  2018       Impact factor: 7.363

8.  Structure-based and shape-complemented pharmacophore modeling for the discovery of novel checkpoint kinase 1 inhibitors.

Authors:  Xiu-Mei Chen; Tao Lu; Shuai Lu; Hui-Fang Li; Hao-Liang Yuan; Ting Ran; Hai-Chun Liu; Ya-Dong Chen
Journal:  J Mol Model       Date:  2009-12-18       Impact factor: 1.810

9.  Discovery and identification of PIM-1 kinase inhibitors through a hybrid screening approach.

Authors:  Mingfeng Shao; Yiming Yuan; Kun Yu; Kai Lei; Guonian Zhu; Lijuan Chen; Mingli Xiang
Journal:  Mol Divers       Date:  2014-02-12       Impact factor: 2.943

10.  Structure-based in silico identification of ubiquitin-binding domains provides insights into the ALIX-V:ubiquitin complex and retrovirus budding.

Authors:  Tal Keren-Kaplan; Ilan Attali; Michael Estrin; Lillian S Kuo; Efrat Farkash; Moran Jerabek-Willemsen; Noa Blutraich; Shay Artzi; Aviyah Peri; Eric O Freed; Haim J Wolfson; Gali Prag
Journal:  EMBO J       Date:  2013-01-29       Impact factor: 11.598

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