Drug discovery is a time consuming business and ah don’t mean those Friday nights searchin’ for Berkeley frat parties. Now some Frenchmen have found a new way to do it that don’t involve no dealers, middle men or rolled up $20 notes.<\/p>\n
For decades now, drug companies have tried the suck it ‘n’ see approach to drug discovery. But the alarming number of failures are forcing the industry to adopt a less lethal method.<\/p>\n
Enter “in silico” chemistry: the process of discovering drugs by sheer number crunchin’ computer power. The task boils down to finding molecules that bind to particular proteins such as receptors, enzymes and ion channels.<\/p>\n
There are two methods. The first involves takin’ a look at the things that already bind to the target and then huntin’ for similar molecules that might also bind. That ain’t much more than a glorified Google search.<\/p>\n
The second involves modelling the 3D structure of the target and working out what kinda molecule might fit that space, like a piece in a jigsaw. That’s a much harder burden o’ work; those supercomputers get all hot ‘n’ sweaty just thinkin’ about it. And even then it don’t often work cos nobody knows the 3D structure of most receptors.<\/p>\n
But Jean-Philippe “Per” Vert at the Centre for Computational Biology in Fontainebleau , France, and his friend, Laurent, have been playin around with an impressive new approach called in silico<\/em> chemogenetics. The idea is to mine the entire chemical space — which is essentially the set of all small molecules — for interactions with the biological space, meaning the set of all proteins in a particular class of target such as receptors.<\/p>\n Per Vert has used a well-established machine learning algorithm to carry out this task in a way that gets round some of the known limitations (such as having to narrow the search manually to prevent the computer chokin’ on it). He reckons the technique shows a dramatic improvement in the way it predicts potential binding molecules for an important class of receptors known as G-protein coupled receptors. This already qualifies the technique as a valuable tool for drug discovery, he says modestly.<\/p>\n Let’s hope he’s right.<\/p>\n