Literature DB >> 16600388

Computational neuropharmacology: dynamical approaches in drug discovery.

Ildiko Aradi1, Péter Erdi.   

Abstract

Computational approaches that adopt dynamical models are widely accepted in basic and clinical neuroscience research as indispensable tools with which to understand normal and pathological neuronal mechanisms. Although computer-aided techniques have been used in pharmaceutical research (e.g. in structure- and ligand-based drug design), the power of dynamical models has not yet been exploited in drug discovery. We suggest that dynamical system theory and computational neuroscience--integrated with well-established, conventional molecular and electrophysiological methods--offer a broad perspective in drug discovery and in the search for novel targets and strategies for the treatment of neurological and psychiatric diseases.

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Year:  2006        PMID: 16600388     DOI: 10.1016/j.tips.2006.03.004

Source DB:  PubMed          Journal:  Trends Pharmacol Sci        ISSN: 0165-6147            Impact factor:   14.819


  7 in total

Review 1.  In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling.

Authors:  S Ekins; J Mestres; B Testa
Journal:  Br J Pharmacol       Date:  2007-06-04       Impact factor: 8.739

Review 2.  Computational models of neuronal biophysics and the characterization of potential neuropharmacological targets.

Authors:  Michele Ferrante; Kim T Blackwell; Michele Migliore; Giorgio A Ascoli
Journal:  Curr Med Chem       Date:  2008       Impact factor: 4.530

3.  The diversity and antimicrobial activity of Preussia sp. endophytes isolated from Australian dry rainforests.

Authors:  Rachel R Mapperson; Michael Kotiw; Rohan A Davis; John D W Dearnaley
Journal:  Curr Microbiol       Date:  2013-08-23       Impact factor: 2.188

4.  Impaired associative learning in schizophrenia: behavioral and computational studies.

Authors:  Vaibhav A Diwadkar; Brad Flaugher; Trevor Jones; László Zalányi; Balázs Ujfalussy; Matcheri S Keshavan; Péter Erdi
Journal:  Cogn Neurodyn       Date:  2008-06-16       Impact factor: 5.082

5.  Population based models of cortical drug response: insights from anaesthesia.

Authors:  Brett L Foster; Ingo Bojak; David T J Liley
Journal:  Cogn Neurodyn       Date:  2008-09-23       Impact factor: 5.082

6.  Engineering a thalamo-cortico-thalamic circuit on SpiNNaker: a preliminary study toward modeling sleep and wakefulness.

Authors:  Basabdatta S Bhattacharya; Cameron Patterson; Francesco Galluppi; Simon J Durrant; Steve Furber
Journal:  Front Neural Circuits       Date:  2014-05-20       Impact factor: 3.492

7.  Implementing the cellular mechanisms of synaptic transmission in a neural mass model of the thalamo-cortical circuitry.

Authors:  Basabdatta S Bhattacharya
Journal:  Front Comput Neurosci       Date:  2013-07-04       Impact factor: 2.380

  7 in total

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