Carbohydrates are central to the study of cancer. Glycosylation sites are used as biomarkers for cancer detection, and cell surface glycans play a role in metastasis, signaling, and transcription processes in tumor cells. Despite the importance of carbohydrates in cancer, structural knowledge of glycosylation is currently limited. Carbohydrates have proven difficult both to characterize chemically and to model computationally. They have a high degree of conformational freedom, multiple stereocenters, and in many cases complicated branching. Traditional modeling methods have focused on proteins and nucleic acids, which have distinct properties from carbohydrates, and much progress remains in modeling the interactions between proteins and carbohydrates, particularly in the case of glycoproteins. The major objectives of this proposed research are to develop tools to predict the interactions between carbohydrates and protein structures. Newly developed methods will handle the high degree of flexibility, stereochemistry, and branching inherent to carbohydrates. Available scoring functions for protein folding and docking will be improved, custom tailoring them to function as readily with glycopeptides as with non-glycosylated peptides. These improved and novel methods will be used to model the MUC1 protein, which plays several roles in cancer, including computational binding studies of adhesion molecules with MUC1 glycoforms involved in cancer and of proteolytic enzymes to MUC1. Collaborations with the Yarema lab will ensure the validity of the results. Success in these endeavors will lead to greater understanding of the role of glycosylation in human biology and could result ultimately in anti-cancer therapeutics and vaccines.

Public Health Relevance

Carbohydrates are foundational to human biology and play important roles for cancer cells, but their behavior is currently enigmatic and their structures ar difficult to characterize. This study will develop computational tools for the prediction of molecular structures of biological carbohydrates and their effect on binding. In particular, this research will determine how cell adhesion molecules and anti-cancer antibodies may target carbohydrates presented by tumor proteins, using cell surface protein MUC1 as a model system.

Agency
National Institute of Health (NIH)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
1F32CA189246-01
Application #
8780135
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Mcguirl, Michele
Project Start
Project End
Budget Start
Budget End
Support Year
1
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Johns Hopkins University
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21205