Broadening The Substrate Scope of Aldolases Through Metagenomic Enzyme Discovery.

Bio-processes based on enzymatic catalysis play a major role in the development of green, sustainable processes, and the discovery of new enzymes is key to this approach. In this work, we analysed ten metagenomes and retrieved 48 genes coding for deoxyribose-5-phosphate aldolases (DERAs, EC 4.1.2.4) using a sequence-based approach. These sequences were recombinantly expressed in Escherichia coli and screened for activity towards a range of aldol additions. Among these, one enzyme, DERA-61, proved to be particularly interesting and catalysed the aldol addition of furfural or benzaldehyde with acetone, butanone and cyclobutanone with unprecedented activity. The product of these reactions, aldols, can find applications as building blocks in the synthesis of biologically active compounds. Screening was carried out to identify optimized reaction conditions targeting temperature, pH, and salt concentrations. Lastly, the kinetics and the stereochemistry of the products were investigated, revealing that DERA-61 and other metagenomic DERAs have superior activity and stereoselectivity when they are provided with non-natural substrates, compared to well-known DERAs.

An Evaluation of the Potential of NMR Spectroscopy and Computational Modelling Methods to Inform Biopharmaceutical Formulations.

Protein-based therapeutics are considered to be one of the most important classes of pharmaceuticals on the market. The growing need to prolong stability of high protein concentrations in liquid form has proven to be challenging. Therefore, significant effort is being made to design formulations which can enable the storage of these highly concentrated protein therapies for up to 2 years. Currently, the excipient selection approach involves empirical high-throughput screening, but does not reveal details on aggregation mechanisms or the molecular-level effects of the formulations under storage conditions. Computational modelling approaches have the potential to elucidate such mechanisms, and rapidly screen in silico prior to experimental testing. Nuclear Magnetic Resonance (NMR) spectroscopy can also provide complementary insights into excipient⁻protein interactions. This review will highlight the underpinning principles of molecular modelling and NMR spectroscopy. It will also discuss the advancements in the applications of computational and NMR approaches in investigating excipient⁻protein interactions.