Although automated machines are growing more versatile, teaching a computer to devise its own synthesis remains a massive problem, says Yuichi Tateno, an automation researcher at pharmaceutical company GlaxoSmithKline in Stevenage, UK, and a member of the Dial-a-Molecule collaboration. “The hardware has always been there, but the software and data have let it down,” he says. Human chemists planning a synthesis tend to use a technique called retrosynthetic analysis. They draw the finished molecule and then pick it apart, erasing bonds that would be easy to form and leaving fragments of molecule that are stable or readily available. This allows them to identify the chemical jigsaw pieces they need as their raw materials, and to devise a strategy for connecting the pieces in the lab. If need be, they can seek inspiration from a commercial database such as SciFinder — an interface to the American Chemical Societys Chemical Abstracts Service — or its main rival Reaxys, offered by publishing giant Elsevier. Entering a molecular structure or a reaction into these databases yields examples in the literature. But even with online help, says Tateno, humans often fail at synthesis. “With the amount of chemistry thats out there, theres nobody who can know it all.” The hope is that a synthesis machine could one day do much better, says Whitby, not least because computers are so much faster at scanning through terabytes of chemical data to find a specific reaction. The bigger challenge, he adds, is that computers have a much harder time figuring out whether that reaction will actually work in a synthesis, particularly if the target has never been made before. That problem bedevilled Elias Corey, a chemist at Harvard University in Cambridge, Massachusetts, who formalized the rules of retrosynthesis in the 1960s. The following decade, Corey created software called LHASA (Logic and Heuristics Applied to Synthetic Analysis), which could use these rules to suggest sequences of steps towards a synthesis2. But LHASA and its successors have never taken off, says Grzybowski: either the databases have included too few reactions and too many errors, or the algorithms have not properly assessed whether proposed reactions are compatible with all functional groups in the molecule. “If we could just make one chemical bond at a time, in isolation, chemistry would be trivial,” he says. Grzybowski has spent the past decade building a system called Chematica to address those problems. He started by creating a searchable network of about 6 million organic compounds, connected by a similar number of reactions, drawn from one of the main databases behind Reaxys. His team then spent years cleaning up the data — identifying entries that lack crucial information about reagent compatibility or reaction conditions. Without that kind of clean-up, Chematica would be like a computer chef surveying a gigantic recipe book for dishes that use ice cream, stumbling on baked Alaska, and concluding that ice cream can withstand very high temperatures — missing the fact that cooking ice cream in an oven only works with an insulating shield of meringue. Chematica includes such crucial information, so its proposed syntheses of novel molecules — based on about 30,000 retrosynthetic rules — can be much more trustworthy. The team also designed Chematica to take a holistic view of synthesis: it not only hunts for the best reaction to use at each step, but also considers the efficiency of every possible synthetic route as a whole. This means that a poor yield in one step can be counterbalanced by a succession of high-yielding reactions elsewhere in the sequence. “In 5 seconds we can screen 2 billion possible synthetic routes,” says Grzybowski.
Posted on: Thu, 07 Aug 2014 03:43:11 +0000
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