Pharmaceutical bioinformatics

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Pharmaceutical Bioinformatics is a research field related to bioinformatics but with the focus on studying biological and chemical processes in the pharmaceutical area; to understand how xenobiotics interact with the human body and the drug discovery process.

Introduction[edit]

Whereas traditional bioinformatics is a wide subject it has a large focus on molecular biology, pharmaceutical bioinformatics more specifically targets chemical-biological interaction and exploratory focus of chemical and biological interactors using e.g. cheminformatics and chemometrics methods. Methods include, apart from many general bioinformatics methods, ligand-based modeling such as Quantitative structure–activity relationship (QSAR) and proteochemometrics, computer-aided molecular design, chembioinformatics databases, algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery.

In silico metabolism prediction[edit]

One of the major fields within pharmaceutical bioinformatics is the in silico metabolism prediction of drug candidates. This field is in turn divided into three tasks;

  • Predicting the occurrence of an interaction between a compound and an enzyme,
  • Predicting the location in the compound that takes part in the interaction, i.e. the site of metabolism (SOM),
  • Predicting the outcome from the interaction, i.e. the resulting metabolite product.

There are several existing tools trying to solve these tasks, e.g. SMARTCyp[1] and MetaPrint2D[2] predicts the SOM for chemical compounds.

Software and tools[edit]

There are many software tools for pharmaceutical bioinformatics. An example of an open source tool is the Bioclipse workbench.

Conferences[edit]

One conference specific to Pharmaceutical Bioinformatics is "International Conference on Pharmaceutical Bioinformatics" (ICPB) (http://www.icpb.net)

References[edit]

  1. ^ Rydberg, Patrik; Gloriam, David E.; Zaretzki, Jed; Breneman, Curt; Olsen, Lars (2010-06-10). "SMARTCyp: A 2D Method for Prediction of Cytochrome P450-Mediated Drug Metabolism". ACS Medicinal Chemistry Letters. 1 (3): 96–100. doi:10.1021/ml100016x. PMC 4055970. PMID 24936230.
  2. ^ Carlsson, Lars; Spjuth, Ola; Adams, Samuel; Glen, Robert C.; Boyer, Scott (2010-07-01). "Use of historic metabolic biotransformation data as a means of anticipating metabolic sites using MetaPrint2D and Bioclipse". BMC Bioinformatics. 11: 362. doi:10.1186/1471-2105-11-362. ISSN 1471-2105. PMC 2912884. PMID 20594327.

Further reading[edit]