I was recently asked about what the core tasks and competences are for bioinformatics in the discovery of microRNA targeted drugs. Based on my 5 years with bioinformatics at Santaris Pharma, I will give my opinion on what constitutes a successful and productive bioinformatics team in this area.
Most importantly, but also most generally and vaguely, a drug discovery bioinformatics team should understand and appreciate biology and the drug discovery process. This includes the pragmatism, short cuts, time constraints and inconsistencies that are inherent in the process. We can and should push for the systematic approaches that we like, but we must accept that no experiment will ever be perfect and that we have to deal with incomplete data. It will not work to become too absorbed in the beauty of algorithms or ubuntu-distributions. We should always ask how the time we spent in front of our computers adds value to the discovery and development of our drugs.
Specifically for bioinformatics in cialis vs viagra dosage antimiR drug discovery, the core tasks that we are performing are:
- Systematic oligonucleotide design
- Realize, quantify and enumerate the entire design space (Peter Hagedorn has written a nice post on this)
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thousands of oligos (as opposed to one-at-a-time) for properties such as:
- putative off-targets
- fold-back structures
- dimerization potential
- and quite a few more…
- Predict targets for miRNAs. Utilize a range of published methods and databases. Roll our own simple methods, which can be applied on any of the many and changing sequence sets that we are dealing with.
- Sequence handling. Required for most of the other tasks. E.g. we are able to very quickly acquire all annotated 3’UTRs of whatever organism
- Analyze global expression mRNA expression data for what we call miRsignatures: evidence that (predicted) targets of a microRNA are either derepressed (in the case of successful antimiR-treatment) or repressed (in the case miR-overexpression or replacement).
The above tasks are production tasks: the applications of state-of-the-art methods and knowledge to defined problems with defined deliverables.
Apart from the production, bioinformatics is also essential in the continuous research to improve the process of discovering potent and safe oligonucleotides. To facilitate this we work with our lab-based colleagues to make reporting, data-collection and data-storage systematic and machine-readable (the typical biologist excel spreadsheet is full of colors, merged cells and other partially obscure layers of information that a script cannot read). Working closely with biologists and chemists this enables us to do meta-analysis of both in vitro and in vivo experiments to find’features’ that correlate with or influence desirable properties of our oligonucleotides. ‘Features’ is meant very broadly to including things such as oligo-length, chemistry, sequence-motifs, batch-purity, cell-type, sildenafil online mouse strain, dosing regime and many others. The desirable properties are typically potency and safety, but extenze and cialis together could also be biodistribution. These analyses enables us to deliver value in three ways:
- Discover and formulate hypotheses about the basic biology of the fate of oligonucleotides in mammalian cells and bodies.
- Construct in silico filters that reduce (but never ever eliminate!) the need and cost of physical screening experiments.
- Provide quantitative data usable for optimizing the whole drug discovery chain.