Open Access

In silico pharmacology: drug design and discovery’s gate to the future

In Silico Pharmacology20131:1

DOI: 10.1186/2193-9616-1-1

Received: 4 December 2012

Accepted: 4 December 2012

Published: 12 February 2013

Introduction of new drugs and novel therapeutic solutions is a long and costly process (Myers and Baker2001; DiMasi et al.,2003). Traditionally, pharmacologists strive to optimize and accelerate this process by developing new in vivo and in vitro investigation strategies.

However, the last decades have been witnessing the rise of alternative research models, the so-called in silico approaches, using computational environments as their experimental laboratories.

Imitating the common biological terms in vivo and in vitro, the term in silico refers to performing experiments using computers. Although the historical origin of this term is not clear, it is safe to assume that silico is a reference to the chemical element Silicon (Si), a key component of computer chips.

The majority of the in silico methods are primarily used in parallel with the generation of in vivo and in vitro data for accurate modeling and validation of a wide range of applications from the ligand design and optimization to the characterization of fundamental pharmacological properties of molecules such as absorption, distribution, metabolism, excretion and toxicity (Ekins et al.,2007). The diversity of the developed mathematical and biophysical models in this field resembles the manifoldness of the pharmacological problems uniquely.

While the seminal work of Hansch and Fujita (1964) on the statistical relationships between the molecular structure and a specific chemical or biological property (Quantitative structure-activity relationships) initiated the application of modern data mining and statistical techniques such as the virtual ligand screening ( Oprea and Matter,2004) and the virtual affinity profiling (O'Connor and Roth,2005; Paolini et al.,2006), biophysical (Jones and Woodhall,2005; Graupner and Gutkin,2009) and neurochemical network models (Noori and Jäger,2010; Noori,2012; Noori et al.,2012) mainly apply deterministic dynamical systems to identify drug-induced alterations of electrophysiological and/or neurochemical network characteristics.

In light of the rapid progress of in silico approaches, it could be expected that biomedical investigations in virtual reality ultimately lead to rigorous changes in the pharmaceutical research landscape by optimizing the drug development process, reducing the number of animal experiments and smoothing the path to personalized medicine.

Despite the increasing interest in this field of research, publication platforms with dedicated agenda to in silico pharmacology are missing. With the launch of our journal, we aim to fill this gap and provide a forum for interdisciplinary research articles that specifically address computational approaches in drug-design and multi-scale analysis of bioactive substances from the cellular up to behavioral level.

Authors’ Affiliations

(1)
Institute of Psychopharmacology, Central Institute for Mental Health, Medical Faculty Mannheim, University of Heidelberg

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Copyright

© Noori and Spanagel; licensee Springer. 2013

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.