LABORATORY INFORMATICS
Drug compound binding with the target site.
stop the virus replicating without having unwanted effects on the host’s own cells.’
Finding the key Most drug development is still centred on organic chemical molecules. A small molecule drug can be thought of as a key – or ligand – that structurally fits a specific lock – the drug target – for example an overactive enzyme, or another protein that is involved in the disease process, and so deactivate it. Finding drug molecules that are specific to the desired target can be carried out through traditional experimentation in the lab, or through virtual structure-based screening approaches. ‘One of the drawbacks of traditional,
wet-lab approaches is that this type of work is expensive and time consuming, and you can’t test that many compounds quickly – perhaps a few hundred thousand in a high-throughput screen, but not much more,’ stated Gorgulla, who is now a postdoctoral fellow in the Wagner Lab at Harvard Medical School, and also associated to the Department of Physics at Harvard University. ‘In fact, this number is relatively tiny when you consider that the total chemical space of small organic molecules suitable for drug discovery may encompass some 1,060 structures.’ Contrasting with experimental
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“One of the drawbacks of traditional, wet-lab approaches is that this type of work is expensive and time consuming – you can’t test that many compounds quickly”
approaches to finding drug candidates, virtual screening approaches that use computational power now commonly available to labs, are now becoming increasingly routine. ‘The binding of a molecule to a particular protein is driven by energetics, and standard equations of thermodynamics, so we can approach this computationally,’ Arthanari noted. ‘If we have a high-resolution structure of a protein generated, say, by x-ray crystallography, NMR or cryo-electron microscopy techniques, we can use computational methods to screen huge libraries of virtual compounds for which structural data is available, to more accurately calculate if a drug candidate will bind in a particular pocket of the target protein.’ Until now, these computational
platforms have been capable of screening libraries containing perhaps 106 or 107
molecules for which the structure is known, but this is still a relatively small number given that overall chemical space, Gorgulla noted. As Arthanari pointed out, ‘The more molecules you can screen, the more likely you are to find the ideal compound … It’s like throwing darts at a dartboard. You may not be a good shot, but the more darts you have, the more likely you will be to hit the bullseye.’
Democratising virtual screening The VirtualFlow software developed by Gorgulla allows researchers or companies with access to sufficient computing power – which might typically be available to universities or even relatively small pharma companies – via the Cloud – to improve on virtual screening throughput by orders of magnitude. ‘It pretty much democratises virtual screening at a previously impossible scale,’ Arthanari suggested. Putting it into context, he continued, ‘… if one CPU takes about 15 seconds to screen a single molecule docking with the target protein, then it would take about 475 years to do a billion molecules. With VirtualFlow it’s now possible to screen billions of compounds in just days, by harnessing potentially hundreds of thousands of CPUs in parallel.’ The researchers published a paper describing the Virtual Platform
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