Tools for decoding the structure-function relationships of biopolymers in nanotechnology and glycobiology

Abstract

In this thesis, new tools have been developed for decoding structure-function relationships governing complex biopolymers that have emerged as key players in biology, biotechnology, and medicine. Specifically: (1.) The first part of this thesis addresses the structure-function relationship of synthetic biodegradable plastics that are at the forefront of nanotechnology for spatiotemporally-regulated targeting and sustained release of drugs to treat Cancer and other chronic diseases. A Voxel-based 3-D platform for accurately simulating all phases of polymeric nanoparticle erosion and drug release is introduced. Using the developed Voxel platform, the release of anti-inflammatory and anti-cancer drugs such as doxorubicin and dexamethasone from poly lactic-co-glycolic acid (PLGA) nanoparticles is precisely predicted. The Voxel platform emerges as a powerful and versatile tool for deducing the dynamics in interplay of polymer, drug, and water molecules, thus permitting the rational design of optimal nanotechnology treatments for cancer. (2.) The second part of this thesis is focused on development of tools to elucidate structure-function relationships of complex polysaccharides (glycans) that specifically interact with proteins to modulate a host of biological processes including growth, development, angiogenesis, cancer, anticoagulation, microbial pathogenesis, and viral infections. First, towards the fine structure determination of complex linear glycans (glycosaminoglycans or GAGs), enzymatic tools are developed for both depolymerizing GAGs at specific linkages and for effectively modulating their functional groups. Specifically, the development and integrated biochemical-structural characterization of the Chondroitinase ABC-II enzyme that depolymerizes dermatan sulfate and chondroitin sulfate GAGs (CSGAGs), and the 6-0- Sulfatase and N-Sulfamidase enzymes that de-sulfate functional groups on heparin and heparan sulfate GAGs (HSGAGs) are described. Second, the interaction of branched glycans with proteins is analyzed using the interplay of Influenza virus surface proteins (mainly Hemagglutinin and Neuraminidase) with host cell surface sialylated glycan receptors as a model system. For this purpose, the novel triple reassortant "Swine Flu" pandemic virus (or 2009 HINI virus) is studied. Finally, in order to overcome the challenges facing protein structure prediction in the "Twilight Zone" of low homology that is rampant in glycan-binding protein (lectin) families, a new tool is introduced for modeling the 3-D structure of proteins directly from sequence. Specifically, it is identified that protein core atomic interaction networks (PCAINs) are evolutionarily non-tinkered and fold-conserved, and this finding is utilized towards assignment of folds, structures, and potential glycan substrates to lectin sequences. It is further demonstrated that the developed tool is effective universally; thus emerging as a promising platform for generic protein sequence-to-structure and function mapping in a broad spectrum of biological applications.