Document Detail


In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling.
MedLine Citation:
PMID:  17549047     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Pharmacology over the past 100 years has had a rich tradition of scientists with the ability to form qualitative or semi-quantitative relations between molecular structure and activity in cerebro. To test these hypotheses they have consistently used traditional pharmacology tools such as in vivo and in vitro models. Increasingly over the last decade however we have seen that computational (in silico) methods have been developed and applied to pharmacology hypothesis development and testing. These in silico methods include databases, quantitative structure-activity relationships, pharmacophores, homology models and other molecular modeling approaches, machine learning, data mining, network analysis tools and data analysis tools that use a computer. In silico methods are primarily used alongside the generation of in vitro data both to create the model and to test it. Such models have seen frequent use in the discovery and optimization of novel molecules with affinity to a target, the clarification of absorption, distribution, metabolism, excretion and toxicity properties as well as physicochemical characterization. The aim of this review is to illustrate some of the in silico methods for pharmacology that are used in drug discovery. Further applications of these methods to specific targets and their limitations will be discussed in the second accompanying part of this review.
Authors:
S Ekins; J Mestres; B Testa
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Publication Detail:
Type:  Historical Article; Journal Article; Research Support, Non-U.S. Gov't; Review     Date:  2007-06-04
Journal Detail:
Title:  British journal of pharmacology     Volume:  152     ISSN:  0007-1188     ISO Abbreviation:  Br. J. Pharmacol.     Publication Date:  2007 Sep 
Date Detail:
Created Date:  2007-08-28     Completed Date:  2007-10-18     Revised Date:  2013-06-06    
Medline Journal Info:
Nlm Unique ID:  7502536     Medline TA:  Br J Pharmacol     Country:  England    
Other Details:
Languages:  eng     Pagination:  9-20     Citation Subset:  IM    
Affiliation:
ACT LLC, 1 Penn Plaza, New York, NY 10119, USA. ekinssean@yahoo.com
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MeSH Terms
Descriptor/Qualifier:
Animals
Computer Graphics
Computer-Aided Design* / history
Databases as Topic*
Drug Design*
Gene Regulatory Networks
History, 19th Century
History, 20th Century
Humans
Ligands*
Metabolic Networks and Pathways
Models, Biological
Models, Molecular
Molecular Structure
Pharmacokinetics
Protein Conformation
Quantitative Structure-Activity Relationship
Signal Transduction
Systems Biology*
User-Computer Interface*
Chemical
Reg. No./Substance:
0/Ligands
Comments/Corrections

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