Literature DB >> 16935748

Applying computational modeling to drug discovery and development.

Neil Kumar1, Bart S Hendriks, Kevin A Janes, David de Graaf, Douglas A Lauffenburger.   

Abstract

Computational models of cells, tissues and organisms are necessary for increased understanding of biological systems. In particular, modeling approaches will be crucial for moving biology from a descriptive to a predictive science. Pharmaceutical companies identify molecular interventions that they predict will lead to therapies at the organism level, suggesting that computational biology can play a key role in the pharmaceutical industry. We discuss pharmaceutically-relevant computational modeling approaches currently used as predictive tools. Specific examples demonstrate how companies can employ these computational models to improve the efficiency of transforming targets into therapies.

Mesh:

Year:  2006        PMID: 16935748     DOI: 10.1016/j.drudis.2006.07.010

Source DB:  PubMed          Journal:  Drug Discov Today        ISSN: 1359-6446            Impact factor:   7.851


  30 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.  Integrated pharmacokinetics and pharmacodynamics in drug development.

Authors:  Jasper Dingemanse; Silke Appel-Dingemanse
Journal:  Clin Pharmacokinet       Date:  2007       Impact factor: 6.447

3.  Mathematical modeling based on ordinary differential equations: A promising approach to vaccinology.

Authors:  Carla Rezende Barbosa Bonin; Guilherme Cortes Fernandes; Rodrigo Weber Dos Santos; Marcelo Lobosco
Journal:  Hum Vaccin Immunother       Date:  2016-12-27       Impact factor: 3.452

Review 4.  A review of connectivity map and computational approaches in pharmacogenomics.

Authors:  Aliyu Musa; Laleh Soltan Ghoraie; Shu-Dong Zhang; Galina Glazko; Olli Yli-Harja; Matthias Dehmer; Benjamin Haibe-Kains; Frank Emmert-Streib
Journal:  Brief Bioinform       Date:  2018-05-01       Impact factor: 11.622

Review 5.  Computational drug discovery.

Authors:  Si-Sheng Ou-Yang; Jun-Yan Lu; Xiang-Qian Kong; Zhong-Jie Liang; Cheng Luo; Hualiang Jiang
Journal:  Acta Pharmacol Sin       Date:  2012-08-27       Impact factor: 6.150

6.  Phosphoproteomic studies of receptor tyrosine kinases: future perspectives.

Authors:  Paul H Huang
Journal:  Mol Biosyst       Date:  2011-12-02

7.  Perturbation biology: inferring signaling networks in cellular systems.

Authors:  Evan J Molinelli; Anil Korkut; Weiqing Wang; Martin L Miller; Nicholas P Gauthier; Xiaohong Jing; Poorvi Kaushik; Qin He; Gordon Mills; David B Solit; Christine A Pratilas; Martin Weigt; Alfredo Braunstein; Andrea Pagnani; Riccardo Zecchina; Chris Sander
Journal:  PLoS Comput Biol       Date:  2013-12-19       Impact factor: 4.475

8.  Towards a quantitative representation of the cell signaling mechanisms of hallucinogens: measurement and mathematical modeling of 5-HT1A and 5-HT2A receptor-mediated ERK1/2 activation.

Authors:  Chiung-Wen Chang; Ethan Poteet; John A Schetz; Zeynep H Gümüş; Harel Weinstein
Journal:  Neuropharmacology       Date:  2008-08-13       Impact factor: 5.250

9.  A molecular signaling model of platelet phosphoinositide and calcium regulation during homeostasis and P2Y1 activation.

Authors:  Jeremy E Purvis; Manash S Chatterjee; Lawrence F Brass; Scott L Diamond
Journal:  Blood       Date:  2008-07-02       Impact factor: 22.113

10.  Systems pharmacology and genome medicine: a future perspective.

Authors:  Aislyn D Wist; Seth I Berger; Ravi Iyengar
Journal:  Genome Med       Date:  2009-01-22       Impact factor: 11.117

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