This Perspective summarizes progress in the development of O ₂ -selective metal–organic frameworks for adsorptive air separations and identifies key metrics and design considerations toward optimizing material performance for practical applications.

Understanding the structure–activity relationships (SARs) of small molecules is important for developing probes and novel therapeutic agents in chemical biology and drug discovery. Increasingly, multiplexed small-molecule profiling assays allow simultaneous measurement of many biological response parameters for the same compound (e.g., expression levels for many genes or binding constants against many proteins). Although such methods promise to capture SARs with high granularity, few computational methods are available to support SAR analyses of high-dimensional compound activity profiles. Many of these methods are not generally applicable or reduce the activity space to scalar summary statistics before establishing SARs. In this article, we present a versatile computational method that automatically extracts interpretable SAR rules from high-dimensional profiling data. The rules connect chemical structural features of compounds to patterns in their biological activity profiles. We applied our method to data from novel cell-based gene-expression and imaging assays collected on more than 30,000 small molecules. Based on the rules identified for this data set, we prioritized groups of compounds for further study, including a novel set of putative histone deacetylase inhibitors.

Early detection of pathogens requires methods that are fast, selective, sensitive and affordable. We report the development of a biosensor with high sensitivity and selectivity based on the low-cost preparation of organosiloxane (OSX) polymers imprinted with E. coli-GFP (green fluorescent protein). OSX polymers with high optical transparency, no cracking, and no shrinkage were prepared by varying several parameters of the sol–gel reaction. The unique shape and chemical fingerprint of the targeted inactivated E. coli-GFP were imprinted into bulk polymers by replication imprinting where the polymer solution was dropcast onto a bacteria template that produced a replica of the bacterial shape and chemistry on the polymer surface upon removal of the template. Capture performances were studied under non-laminar flow conditions with samples containing inactivated E. coli-GFP and compared to inactivated S. typhimurium-GFP. Capture selectivity ratios are dependent on the type of alkoxysilanes used, the H₂O:silane molar ratio, and the polymerization temperature. The bacteria concentration in suspension ranged from ~6 × 10⁵ to 1.6 × 10⁹ cells/mL. E. coli-imprinted OSX polymers with polyethylene glycol (PEG) differentiated between the targeted bacterium E. coli, and non-targeted bacteria S. typhimurium and native E. coli-GFP, achieving selectivity ratios up to 4.5 times higher than polydimethylsiloxane (PDMS) and OSX polymers without PEG.