Let’s start with the “popular” version: Scientists Create Chemical ‘Brain’: Giant Network Links All Known Compounds and Reactions
From the post:
Northwestern University scientists have connected 250 years of organic chemical knowledge into one giant computer network — a chemical Google on steroids. This “immortal chemist” will never retire and take away its knowledge but instead will continue to learn, grow and share.
A decade in the making, the software optimizes syntheses of drug molecules and other important compounds, combines long (and expensive) syntheses of compounds into shorter and more economical routes and identifies suspicious chemical recipes that could lead to chemical weapons.
“I realized that if we could link all the known chemical compounds and reactions between them into one giant network, we could create not only a new repository of chemical methods but an entirely new knowledge platform where each chemical reaction ever performed and each compound ever made would give rise to a collective ‘chemical brain,’” said Bartosz A. Grzybowski, who led the work. “The brain then could be searched and analyzed with algorithms akin to those used in Google or telecom networks.”
Called Chematica, the network comprises some seven million chemicals connected by a similar number of reactions. A family of algorithms that searches and analyzes the network allows the chemist at his or her computer to easily tap into this vast compendium of chemical knowledge. And the system learns from experience, as more data and algorithms are added to its knowledge base.
Details and demonstrations of the system are published in three back-to-back papers in the Aug. 6 issue of the journal Angewandte Chemie.
Well, true enough, except for the “share” part. Chematica is in the process of being commercialized.
If you are interested in the non-”popular” version:
Rewiring Chemistry: Algorithmic Discovery and Experimental Validation of One-Pot Reactions in the Network of Organic Chemistry (pages 7922–7927) by Dr. Chris M. Gothard, Dr. Siowling Soh, Nosheen A. Gothard, Dr. Bartlomiej Kowalczyk, Dr. Yanhu Wei, Dr. Bilge Baytekin and Prof. Bartosz A. Grzybowski. Article first published online: 13 JUL 2012 | DOI: 10.1002/anie.201202155.
Computational algorithms are used to identify sequences of reactions that can be performed in one pot. These predictions are based on over 86 000 chemical criteria by which the putative sequences are evaluated. The “raw” algorithmic output is then validated experimentally by performing multiple two-, three-, and even four-step sequences. These sequences “rewire” synthetic pathways around popular and/or important small molecules.
Parallel Optimization of Synthetic Pathways within the Network of Organic Chemistry (pages 7928–7932) by Dr. Mikołaj Kowalik, Dr. Chris M. Gothard, Aaron M. Drews, Nosheen A. Gothard, Alex Weckiewicz, Patrick E. Fuller, Prof. Bartosz A. Grzybowski and Prof. Kyle J. M. Bishop. Article first published online: 13 JUL 2012 | DOI: 10.1002/anie.201202209.
Finding a needle in a haystack: The number of possible synthetic pathways leading to the desired target of a synthesis can be astronomical (1019 within five synthetic steps). Algorithms are described that navigate through the entire known chemical-synthetic knowledge to identify optimal synthetic pathways. Examples are provided to illustrate single-target optimization and parallel optimization of syntheses leading to multiple targets.
Chemical Network Algorithms for the Risk Assessment and Management of Chemical Threats (pages 7933–7937) by Patrick E. Fuller, Dr. Chris M. Gothard, Nosheen A. Gothard, Alex Weckiewicz and Prof. Bartosz A. Grzybowski. Article first published online: 13 JUL 2012 | DOI: 10.1002/anie.201202210.
A network of chemical threats: Current regulatory protocols are insufficient to monitor and block many short-route syntheses of chemical weapons, including those that start from household products. Network searches combined with game-theory algorithms provide an effective means of identifying and eliminating chemical threats. (Picture: an algorithm-detected pathway that yields sarin (bright red node) in three steps from unregulated substances.)
Do you see any potential semantic issues in such a network? Arising as our understanding of reactions changes?
Recalling that semantics isn’t simply a question of yesterday, today and tomorrow but also of tomorrows, 10, 50, or 100 or more years from now.
We may fancy our present understanding as definitive, but it is just a fancy.