Date of Award

Spring 4-2021

Level of Access Assigned by Author

Open-Access Dissertation

Degree Name

Doctor of Philosophy (PhD)


Biomedical Sciences


Olgun Guvench

Second Committee Member

Dustin Updike

Third Committee Member

Sergey Ryzhov

Additional Committee Members

Lucy Liaw

Ronald Hills


Glycosaminoglycans (GAGs) are the linear carbohydrate components of proteoglycans (PGs) that mediate PG bioactivities, including signal transduction, tissue morphogenesis, and matrix assembly. To understand GAG function, it is important to understand GAG structure and biophysics at atomic resolution. This is a challenge for existing experimental and computational methods because GAGs are heterogeneous, conformationally complex, and polydisperse, containing up to 200 monosaccharides. Molecular dynamics (MD) simulations come close to overcoming this challenge but are only feasible for short GAG polymers. To address this problem, we developed an algorithm that applies conformations from unbiased all-atom explicit-solvent MD simulations of short GAG polymers to rapidly construct 3-D atomic-resolution models of GAGs of arbitrary length.

MD simulations of GAG 10-mers (i.e., polymers containing 10 monosaccharides) and 20-mers were run and conformations of all monosaccharide rings and glycosidic linkages were analyzed and compared to existing experimental data. These analyses demonstrated that (1) MD-generated GAG conformations are in agreement with existing experimental data; (2) MD-generated GAG 10-mer ring and linkage conformations match those in corresponding GAG 20-mers, suggesting that these conformations are representative of those in longer GAG biopolymers; and (3) rings and linkages in GAG 10- and 20-mers behave randomly and independently in MD simulation. Together, these findings indicate that MD-generated GAG 20-mer ring and linkage conformations can be used to construct thermodynamically-correct models of GAG polymers. Indeed, our findings demonstrate that our algorithm constructs GAG 10- and 20-mer conformational ensembles that accurately represent the backbone flexibility seen in MD simulations. Furthermore, within a day, our algorithm constructs conformational ensembles of GAG 200-mers that we would reasonably expect from MD simulation, demonstrating the efficiency of the algorithm and reduction in its time and computational cost compared to simulation.

While there are other programs that can quickly construct atomic-resolution models of GAGs, those programs use conformations from short GAG subunits in solid state. Our findings suggest that GAG 20-mers are more flexible than short GAG subunits, meaning our program constructs ensembles that more accurately represent GAG polymer backbone flexibility and provide valuable insights toward improving the understanding of the structure and biophysics of GAGs.

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