Pharmacogenomics
From Biomatics.org
From Wikipedia
Pharmacogenomics is the branch of pharmaceutics which deals with the influence of genetic variation on drug response in patients by correlating gene expression or single-nucleotide polymorphisms with a drug's efficacy or toxicity. By doing so, pharmacogenomics aims to develop rational means to optimise drug therapy, with respect to the patients' genotype, to ensure maximum efficacy with minimal adverse effects. Such approaches promise the advent of "personalized medicine", in which drugs and drug combinations are optimised for each individual's unique genetic makeup.
Pharmacogenomics is the whole genome application of pharmacogenetics, which examines the single gene interactions with drugs.
Rational drug design
As it relates to Biomatics then perhaps Pharmacoepigenomics is a better term. It deals with the interaction of drugs with biomatically described systems.
Epigenomic mechanisms play a critical role in controlling gene expression and thus drug responsiveness. The epigenome is composed of chromatin and its methylation, acetylation etc.modifications. Chromatin structure dynamics are involved in the pathology of cancer and in normal aging. This field will address the epigenomic basis of individual differences in drug responsiveness, identification of side effects of drugs and the discovery of novel drug targets. The control of epigenetic states presents therapeutic and prophylactic opportunities, which requires the development of drugs that target the epigenomic machinery.
Biomatics describes the dynamics of gene clusters and the proteins they produce and coordinate. The biomatic model provides a snapshot of the ideal or goal “state” as well as the actual state. The opportunity for the pharmaceutical industry is to engineer therapies to restore the healthy state. A good place to start is by studying the various types of Histone modifying reactions.
DNA Microarray technology can yield time series data of the entire genome, thus giving pictures of the different stages of diseases. Clustering algorithms in many experiments have yielded precisely eight clusters of genes in Asthma, various cancers and other areas of interest. While clustering algorithms may not be entirely reliable, this may not be a mere coincidence and could be evidence of the models proposed elsewhere in this WIKI. If this is true then these rich models may help to understand the underlying processes and aid development of treatment plans.
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The following "cellular automaton" courtesy of wikipedia shows what a time series of DNA microarray data could look like. Note that 32,000 genes could be represented by an array of approximate dimensions of 178 by 178 whereas the following cellular automaton has dimensions 199 by 175.
The following classes of chromatin modifying reactions represent seperate pathways that drugs may influence in the dynamics of various medically relevant situations.
Methylation
Methyltransferase inhibitors
Acetylation
Acetyltransferases
Histone deacetylase inhibitors
Phosphorylation
DNA topoisomerase I and II
Ubiquitination
Sumoylation
Combinations of these agents could theoretically be used to affect the Histone-DNA machinery to bring tissue back to healthier states.
