Discovery of selective saccharide receptors via Dynamic Combinatorial Chemistry

Aleñá Rodríguez, Miguel Ángel ORCID: 0009-0003-0794-5314 (2024). Discovery of selective saccharide receptors via Dynamic Combinatorial Chemistry. University of Birmingham. Ph.D.

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Abstract

The diagnosis of various diseases and pathological conditions can be accomplished by screening and detecting glycans in cells. Certain glycans serve as excellent biomarkers, being related to cell malfunctioning, while other structurally similar glycans perform completely different functions and are naturally present in healthy cells. Despite the theoretical feasibility of using glycans as biomarkers for early disease detection, our current inability to discriminate between them limits their use.

One promising approach to distinguishing between glycans is targeting their dissimilarities in saccharide chains. However, designing selective receptors for saccharides is challenging due to the complexity of these molecules. Their vast diversity, the fact that they exist in many interconvertible forms, their lack of recognisable functional groups, or the fact that they are normally heavily solvated in aqueous environments have made the design of receptors for saccharides a challenge that has kept the scientific community busy for the last 35 years. Although there have been ground-breaking discoveries in the field, improvements are needed to enhance our disease detection and risk stratification tools.

To address this challenge, we employed a technique known as Dynamic Combinatorial Chemistry (DCC). DCC enables the self-formation and self-selection of the best possible receptor for a given target from a pool or library of potentially good ligands. DCC has been effective for creating receptors for biomolecules such as DNA, RNA, and proteins, but its use for discovering sugar receptors is less explored. In this work, we filled this gap by implementing DCC for screening common saccharides (glucose, galactose, mannose, and fructose) using small, simple, and inexpensive building blocks. Our results indicated that molecule 2DD, which consists of a benzene ring with 2 units of amino acid aspartic acid derivatives connected in positions 1 and 3, is the best receptor in a library of very similar structures for the saccharides glucose, galactose, and mannose. For fructose, molecule 1P, a benzene ring linked to just one unit of the amino acid phenylaldehyde, was appointed as the best receptor. The differential behaviour of fructose can provide insight into the relatively unknown processes behind molecular recognition of sugars.

Molecules 2DD and 1P, as well as some other library members as negative controls, were then synthesised for further testing and DCC results were then validated by Isothermal Titration Calorimetry (ITC) and NMR techniques, proving the effectiveness of DCC as a molecular recognition tool for the creation of receptors for saccharides. Moreover, molecule 1P was found to have a high binding constant (K\(_{a}\) = 1762 M\(^{-1}\)) and selectivity (50-100 times over other sugars) for fructose, which is surprisingly good considering the simplicity of the receptor.

A much more challenging approach was attempted by employing short peptides as scaffolds in DCC experiments. The benefits of using peptides are numerous but can be summarised in three bullet points: customisability, flexibility, and easiness in their synthesis. Unfortunately, we encountered many difficulties for the complete functionalisation of the peptides within the Dynamic Combinatorial Library (DCL) and this approach did not yield the desired results before the research project came to an end. However, we believe in its potential and the knowledge that we gained on the topic helped to stablish the foundations on which new research will be carried out in the near future within the research group.

In summary, this thesis reports the development of a rapid methodology for the discovery of selective receptors for monosaccharides, employing a library of simple and inexpensive starting building blocks. While this was a proof-of-concept study, it can be scalable to larger library sizes and to target more complex biomolecules, becoming a useful tool that could accelerate the discovery of new molecules with biomedical applications.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):