Poster Presentation 30th Lorne Cancer Conference 2018

Knowledge-based scoring functions for predicting carbohydrate-protein interactions (#113)

Mark Agostino

Specific types of carbohydrates are often found on the surface of tumor cells. These carbohydrates are referred to as tumor-associated carbohydrate antigens (TACAs) and are of great interest for the development of cancer immunotherapeutics. Frequently encountered TACAs include Lewis antigens, atypical gangliosides (GD2, GD3, N-glycolyl GM3) and Tn antigen, all of which have been explored with varying degrees of success for targeting by monoclonal antibodies and vaccine-based approaches.

Although the development of therapeutics targeting or exploiting carbohydrate-protein recognition could be accelerated using structure-based techniques, accurately predicting carbohydrate-binding modes and carbohydrate-binding sites on proteins is challenging for both computational and experimental methods. These issues are mainly associated with the high flexibility of carbohydrates and large number of potential hydrogen bonding arrangments available to carbohydrate-protein interactions. Knowledge-based potentials show great performance in predicting drug-protein and protein-protein interactions, and may therefore be valuable for predicting carbohydrate-protein interactions; the body of solved carbohydrate-protein structural complexes is presently sufficient that such potentials could be derived to meaningfully investigate a wide variety of carbohydrate-protein interactions.

In this study, knowledge-based scoring functions for a wide variety of carbohydrates have been determined via surveying of carbohydrate-protein structural complexes, and validated against unbound protein crystal structures. By deriving these functions, trends in carbohydrate protein recognition were also observed, including: a reduced frequency of hydrogen bonding in non-terminal vs. terminal residues, frequent utilisation of the protein backbone for carbohydrate binding, and aromatic residues as the major mediators of non-polar interactions with carbohydrates. The functions generated in this study are anticipated to be valuable for the structure-based design of cancer immunotherapeutics targeting carbohydrate-protein interactions, as well as more broadly within glycobiology and glycomimetic drug design.