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Abstract Controlling the formation and growth of ice is essential to successfully cryopreserve cells, tissues and biologics. Current efforts to identify materials capable of modulating ice growth are guided by iterative changes and human intuition, with a major focus on proteins and polymers. With limited data, the discovery pipeline is constrained by a poor understanding of the mechanisms and the underlying structure-activity relationships. In this work, this barrier is overcome by constructing machine learning models capable of predicting the ice recrystallisation inhibition activity of small molecules. We generate a new dataset via experimental measurements of ice growth, then harness predictive models combining state-of-the-art descriptors with domain-specific features derived from molecular simulations. The models accurately identify potent small molecule ice recrystallisation inhibitors within a commercial compound library. Identified hits can also mitigate cellular damage during transient warming events in cryopreserved red blood cells, demonstrating how data-driven approaches can be used to discover innovative cryoprotectants and enable next-generation cryopreservation solutions for the cold chain.

Abstract Glycan-mediated interactions play a crucial role in biology and medicine, influencing signalling, immune responses, and disease pathogenesis. However, the use of glycans in biosensing and diagnostics is limited by cross-reactivity, as certain glycan motifs can be recognised by multiple biologically distinct protein receptors. To address this specificity challenge, we report the enzymatic synthesis of a 150-member library of site-specifically fluorinated Lewisx analogues (‘glycofluoroforms’) using naturally occurring enzymes and fluorinated monosaccharides. Subsequent incorporation of a subset of these glycans into nanoparticles or a microarray revealed a striking spectrum of distinct binding intensities across different proteins that recognise Lewisx. Notably, we show that for two proteins with unique binding sites for Lewisx, glycofluoroforms exhibited enhanced binding to one protein, whilst reduced binding to the other, with selectivity governed by fluorination patterns. We finally showcase the potential diagnostic utility of this approach in glycofluoroform-mediated bacterial toxin detection by lateral flow.