In what has been described as a ‘Facebook for Molecules’, scientists have now created networks of molecular data similar to the social media site’s new ‘graph’ feature that allows users to find like-minded people in one quick search. In the case of molecules, they claim it could help scientists rapidly sift through vast chemical and biological datasets to find substances with specific properties – a valuable tool to speed the development of new drugs and designer materials.
Researchers at the US National Institute of Standards (NIST) presented their research at the American Crystallographic Association Meeting in Honolulu in July. The search language they developed is likened to Indo-European languages like Sanskrit and Latin, which use short roots to build words based on a set of common rules, they say. For example, the Sanskrit word ‘yoga’ is based on the roots ‘Y(uj)’, meaning to join, ‘O’, meaning God or brain, and ‘Ga’, meaning motion or initiation.
Scientists who know the ‘roots’ can therefore deduce the meaning of unfamiliar terms – and develop new, easily understood, terms in future.
NIST researchers have applied their new search language to the chemical structures in the PubChem compound database, to the worldwide protein data bank (PDB), and to specific NIST-based databases.
They have also developed a system to locate molecules more quickly, by a hierarchical approach similar to that used by supermarkets to locate specific food products more easily, says NIST biophysicist John Elliot. ‘First you find the grocery market section, then the next level of hierarchy is snacks, after which you go to the chips section, and then you’ll quickly know if they have Doritos or not.’
In this way, scientists can likewise home in on the desired compounds quickly and accurately. Effective graph searches could allow researchers to rapidly identify chemical structures and properties needed for the development of new drugs or advanced materials, the researchers claim. While the databases have already attracted much interest, however, they haven’t yet reached a Facebook-like following of more than a billion users.