Abstract
Multicomponent reactions enable the synthesis of large molecular libraries from relatively few inputs. This scalability has led to the broad adoption of these reactions by the pharmaceutical industry. Here, we employ the four-component Ugi reaction to demonstrate that multicomponent reactions can provide a basis for large-scale molecular data storage. Using this combinatorial chemistry we encode more than 1.8 million bits of art historical images, including a Cubist drawing by Picasso. Digital data is written using robotically synthesized libraries of Ugi products, and the files are read back using mass spectrometry. We combine sparse mixture mapping with supervised learning to achieve bit error rates as low as 0.11% for single reads, without library purification. In addition to improved scaling of non-biological molecular data storage, these demonstrations offer an information-centric perspective on the high-throughput synthesis and screening of small-molecule libraries.
Highlights
Multicomponent reactions enable the synthesis of large molecular libraries from relatively few inputs
We introduce a process to perform the nanoliter-scale synthesis and validation of thousands of unique Ugi products per day, without requiring purification or the use of solid supports
By combining high-resolution mass spectrometry with supervised learning, we show how to use isotopes, adducts, impurities, and chemical interactions to improve the identification of information-carrying compounds
Summary
Multicomponent reactions enable the synthesis of large molecular libraries from relatively few inputs. We employ the four-component Ugi reaction to demonstrate that multicomponent reactions can provide a basis for large-scale molecular data storage Using this combinatorial chemistry we encode more than 1.8 million bits of art historical images, including a Cubist drawing by Picasso. Rather than representing information in linear molecular sequences, we store data in locally disordered mixtures of small molecules, which can be identified by their molecular structures This approach may appear comparatively difficult to scale to large amounts of data since we cannot add more subunits, as in the case of a polymer. We introduce a process to perform the nanoliter-scale synthesis and validation of thousands of unique Ugi products per day, without requiring purification or the use of solid supports Some of these compounds are likely novel and have not been experimentally characterized before. The techniques used here can be applied to other scalable chemical libraries
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