Personalised drug treatment using SNP's

99.9% of our genes are identical to anyone else's. The other 0.1% that makes us unique is made up of 3 million single nucleotide polymorphisms (SNPs) that occur one in every 1000 bases. A SNP is a variation of one nucleotide between the DNA sequences of individuals. Ten pharmaceutical companies and the Wellcome Trust have set up the SNP consortium to compile a SNP map of 300,000 SNPs. The rationale behind this giant venture is that the SNP map can be used in the mapping of disease associations and can also be used to unravel an individuals response to various medications. The most interesting SNPs from a pharmaceutical point of view are the coding-SNPs (cSNPs).

These occur in coding regions and are therefore themselves either directly responsible for the disease or a different drug response when they cause a non-synonymous change to a protein. Pharmacogenetics is the study of the genetic basis for the difference between individuals in response to drugs in order to tailor drug prescriptions to individual genotypes. SNPs can be used to distinguish between patients who will benefit from a particular drug against those who will not. This ability to divide the population into drug responders and non responders makes it possible to target a specific population that would benefit from a new drug more effectively. The result will probably be a significant increase in the chance of getting a new drug through to market. This new approach defines a new discovery paradigm that moves beyond genomics to personalised drug treatment. The information obtained from these polymorphic studies could be used in target validation. If a target is determined to be highly polymorphic, it could be abandoned.

Drugs that were abandoned because they caused severe side effects in a minority of people, could be revived. It is believed that in the future doctors will use "SNP-chips", tiny microarrays studded with the DNA sequences that bind to different SNPs. A patient's DNA would be washed over the chip and fragments that matched the sequence would bind to the chip and light up. With computer analysis, doctors would know which gene variations each person carried. Given this head start, they could intervene, long before the disease began to manifest or they could determine which medication would besr suit that individuals genetic makeup.

Bioinformatics and drug discovery

In recent years, we have seen an explosion in the amount of biological information that is available. Various databases are doubling in size every 15 months and we now have the complete genome sequences of more than 100 organisms. It appears that the ability to generate vast quantities of data has surpassed the ability to use this data meaningfully. The pharmaceutical industry has embraced genomics as a source of drug targets. It also recognises that the field of bioinformatics is crucial for validating these potential drug targets and for determining which ones are the most suitable for entering the drug development pipeline.

Recently, there has been a change in the way that medicines are being developed due to our increased understanding of molecular biology. In the past, new synthetic organic molecules were tested in animals or in whole organ preparations. This has been replaced with a molecular target approach in which in-vitro screening of compounds against purified, recombinant proteins or genetically modified cell lines is carried out with a high throughput. This change has come about as a consequence of better and ever improving knowledge of the molecular basis of disease.

All marketed drugs today target only about 500 gene products. The elucidation of the human genome which has an estimated 30,000 to 40,000 genes, presents immense new opportunities for drug discovery and simultaneously creates a potential bottleneck regarding the choice of targets to support the drug discovery pipeline. The major advances in genomics and sequencing means that finding an attractive target is no longer a problem but finding the targets that are most likely to succeed has become the challenge. The focus of bioinformatics in the drug discovery process has therefore shifted from target identification to target validation.A lot of factors need to be taken into account concerning a candidate target from a multitude of heterogeneous resources.

The types of information that one needs to gather about potential targets include nucleotide and protein sequencing information, homologues, mapping information, function prediction, pathway information, disease associations, variants, structural information, gene and protein expression data and species/taxonomic distribution among others. Different bioinformatics tools can be used to gather this information. The accumulation of this information into databases about potential targets means that the pharmaceutical companies can save themselves much time, effort and expense exerting bench efforts on targets that will ultimately fail. The information that is gathered helps to characterise the different targets into families and subfamilies.

It also classifies the behaviour of the different molecules in a biochemical and cellular context. Decisions about which families provide the best potential targets is guided by a number of criteria. It is important that the potential target has a suitable structure for interacting with drug molecules. Structural genomics helps to prioritise the families in terms of their 3D structures.