Probing Chemical Space with Alkaloid-Inspired Libraries

Screening of small molecule libraries is an important aspect of probe and drug discovery science. Numerous authors have suggested that bioactive natural products are attractive starting points for such libraries, due to their structural complexity and sp3-rich character. Here, we describe the construction of a screening library based on representative members of four families of biologically active alkaloids (Stemonaceae, the structurally related cyclindricine and lepadiformine families, lupin, and Amaryllidaceae). In each case, scaffolds were based on structures of the naturally occurring compounds or a close derivative. Scaffold preparation was pursued following the development of appropriate enabling chemical methods. Diversification provided 686 new compounds suitable for screening. The libraries thus prepared had structural characteristics, including sp3 content, comparable to a basis set of representative natural products and were highly rule-of-five compliant

Functional and informatics analysis enables glycosyltransferase activity prediction

The elucidation and prediction of how changes in a protein result in altered activities and selectivities remain a major challenge in chemistry. Two hurdles have prevented accurate family-wide models: obtaining (i) diverse datasets and (ii) suitable parameter frameworks that encapsulate activities in large sets. Here, we show that a relatively small but broad activity dataset is sufficient to train algorithms for functional prediction over the entire glycosyltransferase superfamily 1 (GT1) of the plant Arabidopsis thaliana. Whereas sequence analysis alone failed for GT1 substrate utilization patterns, our chemical–bioinformatic model, GT-Predict, succeeded by coupling physicochemical features with isozyme-recognition patterns over the family. GT-Predict identified GT1 biocatalysts for novel substrates and enabled functional annotation of uncharacterized GT1s. Finally, analyses of GT-Predict decision pathways revealed structural modulators of substrate recognition, thus providing information on mechanisms. This multifaceted approach to enzyme prediction may guide the streamlined utilization (and design) of biocatalysts and the discovery of other family-wide protein functions

Chromopynones are pseudo natural product glucose uptake inhibitors targeting glucose transporters GLUT-1 and -3

The principles guiding the design and synthesis of bioactive compounds based on natural product (NP) structure, such as biology-oriented synthesis (BIOS), are limited by their partial coverage of the NP-like chemical space of existing NPs and retainment of bioactivity in the corresponding compound collections. Here we propose and validate a concept to overcome these limitations by de novo combination of NP-derived fragments to structurally unprecedented ‘pseudo natural products’. Pseudo NPs inherit characteristic elements of NP structure yet enable the efficient exploration of areas of chemical space not covered by NP-derived chemotypes, and may possess novel bioactivities. We provide a proof of principle by designing, synthesizing and investigating the biological properties of chromopynone pseudo NPs that combine biosynthetically unrelated chromane- and tetrahydropyrimidinone NP fragments. We show that chromopynones define a glucose uptake inhibitor chemotype that selectively targets glucose transporters GLUT-1 and -3, inhibits cancer cell growth and promises to inspire new drug discovery programmes aimed at tumour metabolism