ABSTRACT
Carbohydrates are ubiquitous and critical in many biochemical and disease pathways. They regulate many
pathological processes, such as cancer metastasis, microbial and viral infections, and inflammation, and are
biomarkers for pathogens (e.g. HIV), and a range of cancers (e.g. breast, ovarian, prostate, lung and colon).
Therefore, carbohydrates hold a great promise for health-related diagnostic, detection, therapeutic and
research applications. Yet, they are among the most difficult targets for molecular recognition, due to their
immense variety, and subtle, but consequential structural differences. These include anomers, ring-closure
isomers, many stereocenters, branching points, and chemical modifications, resulting in remarkably high
similarities between species. Thus, a major obstacle for further development of effective receptors is
selectivity.
Despite an intense experimental effort, designing sugar receptors with high affinity and selectivity still poses a
serious challenge. We propose to develop an approach for computationally aided design of foldamer receptors
with high selectivity, based on specifically tailored non-covalent interactions and tight shape fit. The approach
combines rational, combinatorial and iterative optimization design components. It is to be general, applicable to
a variety of carbohydrate targets. Furthermore, it will rapidly generate optimal lead sequences for synthesis,
and thus result in a transformative increase in efficiency and speed of producing carbohydrate receptors.
The goal of the proposal is to establish a computer-aided strategy for designing receptors that selectively
recognize carbohydrate targets based on the position and orientation of sugar's OH groups, their hydrophobic
patches, and molecular shapes. Chemical entities particularly amenable for such a receptor design are
foldamers, oligomers that fold into stable secondary structures. Their attractiveness for the proposed combined
rational and combinatorial design stems from their modularity, stability, general structure predictability and
ease of synthesis. We focus on arylamide foldamer based receptors as they have been recently shown to have
unprecedented selectivity towards tested sugars. In the past several years, we have been developing
computational approaches for predicting foldamer structure, dynamics and ligand binding modes, and are thus
in a unique position to advance the proposed idea using arylamide foldamers as the chemical basis for
receptor design. An additional value of the proposed work is that it will be adaptable to other modular
supramolecular scaffolds and targets.
