Chemistry and Materials Science and Engineering 2020 Projects

Project Title:  Molecular Insight into the Stabilization of Glucose Oxidase via Polymer Conjugation

Faculty Mentor’s Name: Coray Colina 

Student Name: Akshay Mathavan 

Research Project Description:

Type 2 diabetes mellitus is a serious chronic disease that currently affects more than 400 million people worldwide and is projected to affect nearly 200 million more within the next few decades [1]. The prevalence of the illness, as well as the increased risk for a plethora of ailments such as cardiovascular and renal disease, imposes a significant burden on healthcare resources. In the management of this life-time condition, adequate glycemic control (maintenance of target blood sugar levels) has become an important aspect of the continuum of care. Consequently, biotechnological research has emphasized the development of accurate glucose-sensing devices. Such devices typically employ the enzyme glucose oxidase (GOx), a dimeric oxido-reductase that catalyzes the oxidation of glucose to hydrogen peroxide and gluconic acid, which can be used to quantify free glucose concentrations [1]. While GOx has been successfully utilized in in vitro optical glucose biosensors, the development of long-term implantable glucose sensors for glycemic control in diabetes patients is a long-sought application that currently faces numerous challenges, such as in vivo stability of only 10-14 days [1]. It is not only the utility of GOx in glucose monitoring that has spurred current interest in stability enhancement; GOx is also currently utilized for its antibacterial properties in wound dressing agents such as Flaminal® [2]. Still, GOx stability depends on a variety of environmental and internal factors. For example, the environment of GOx in an antimicrobial application can consist of bacteria with negatively charged cell walls. Several studies have attempted to solve the problem of in vivo GOx instability through approaches such as engineered membranes or direct manipulation of the protein itself, but significant enhancement of stability has not yet been achieved [3].

Recently, the advent of augmentation of proteins, and other therapeutic macromolecules, with synthetic polymers, termed bioconjugates, has created new opportunities for enzyme modification [5-7]. Protein-polymer systems can impart favorable therapeutic properties such as increased non-immunogenicity, enhanced stability, and improved efficacy. Indeed, an experimental study recently evaluated the effects of attaching polyethylene glycol (PEG), a traditional synthetic polymer used in bioconjugates, to GOx [5]. Specifically, 4.5 kDa methoxy-poly(ethylene glycol)-hydrazide polymers were covalently attached to glycosylation sites of GOx. Gel electrophoresis data showed a significant increase in the molecular mass of the resulting conjugate. Enzymatic activity assays were performed at multiple time points, both in the absence and presence of 5% glucose. While PEGylated GOx activity initially improved compared to native GOx, the authors emphasized that bioconjugate performance was statistically equivalent to native GOx by the 29th day, and ultimately concluded that PEGylation is a viable yet understudied approach towards GOx modification. While the results seem promising, there is still a significant deficit in an understanding of the molecular interactions and binding patterns involved in GOx bioconjugates, as evidenced in the other experimental works that show reduced or enhanced GOx activity upon conjugation [6, 7]. Particularly, the effects of polymer architecture in conjunction with surface properties of the conjugated protein have not been completely elucidated. PEG based architectures can include the attachment of single or multiple linear chains, branched chains with varying linker moieties, and comb-shaped structures, each of which may impact bioconjugate properties such as protein surface coverage and accessibility of binding sites [8]. Non-PEG based polymers include zwitterionic polymers, which consist of oppositely charged cationic and anionic groups along the chain or side chain. Such polymers have been investigated for use in biomedical applications due to their high hydration capacity, which promotes a protein-repulsive nature that allows added stability [9]. Additionally, the nature of the chains can impart stability to the conjugate within charged environments.

Computational studies, including molecular dynamics (MD) simulations, have increasingly been utilized to model, simulate, and analyze important biomolecules at the molecular level in order to generate insight into the dynamic patterns of interaction. For instance, a recent MD study used GOx derived from P. amagasakiense to simulate the dimer’s denaturation process and identified a common set of amino acids involved in its instability [10]. Additionally, work from our lab has likewise employed MD simulations on PEGylated Bovine Serum Albumin and identified several conjugation sites and polymer sizes that facilitate preferential protein-polymer interactions [11, 12]. Clearly, MD simulations possess the potential to provide atomistic characterization and an improved understanding of such processes. In this project, we propose utilizing MD simulations to model GOx conjugated to a spectrum of synthetic polymers, including PEG based structures as well as zwitterionic polymers, in order to characterize the preferential interactions and changes in stability of the bioconjugates, which has direct relevance to its use in glucose monitoring. Such an analysis will serve to provide atomistic resolution to interactions and findings seen in previous experimental work [6]. The proposed study will evaluate the resulting bioconjugates’ dynamics with reference to efficacy of the GOx-substrate (glucose) structure.

[1] Harris JM, Reyes C, and Lopez GP. Common Causes of Glucose Oxidase Instability in In Vivo Biosensing: A Brief Review, J Diabetes Sci Technol. 2013, 7, 1030-1038.

[2] Rashaan ZM, Krijnen P, Elske van den Akker- van Marle M, E. van Baar M, Vloemans A, Dokter J, Tempelman F, H. van der Vlies C, and Breederveld RS. Clinical effectiveness, quality of life and cost-effectiveness of Flaminal® versus Flamazine® in the treatment of partial thickness burns: study protocol for a randomized controlled trial, Trials, 2016, 17, 122.

[3] Chang G, Tatsu Y, Goto T, Imaishi H, and Morigaki K. Glucose concentration determination based on silica sol-gel encapsulated glucose oxidase optical biosensor arrays, Talanta, 2010, 83, 61-65.

[5] Ritter DW, Roberts JR, and McShane MJ. Glycosylation site-targeted PEGylation of glucose oxidase retains native enzymatic activity, Enzyme and Microbial Tech, 2013, 279-285.

[6] Xu G, Xu Y, Li A, Chen T, and Liu J. Enzymatic bioactivity investigation of glucose oxidase modified with hydrophilic or hydrophobic polymers via in situ RAFT polymerization, J POLYM SCI POL CHEM, 2017, 55, 1289-1293.

[7] Campbell AS, Islam MF, and Russell AJ. Intramolecular Electron Transfer through Poly-Ferrocenyl Glucose Oxidase Conjugates to Carbon Electrodes: 1. Sensor Sensitivity, Selectivity and Longevity, Electrochim. Acta, 2017, 248, 578-584.

[8] Lu X and Zhang K. PEGylation of therapeutic oligonucletides: From linear to highly branched PEG architectures, Nano Research, 2018, 11, 5519-5534.

[9] Chang D and Olsen B. Self-assembly of protein-zwitterionic polymer bioconjugates into nanostructured materials, Polymer Chemistry, 2016, 13, 2410-2418.

[10] Todde G, Hovmoller S, Laaksonen A, and Mocci F. Glucose oxidase from Penicillium amagasakiense: Characterization of the transition state of its denaturation from molecular dynamics simulations, Proteins, 2014, 10, 2353-2363.

[11] Munasinghe A, Mathavan A, Mathavan A, Lin P, and Colina C. PEGylation within a confined hydrophobic cavity of a protein, PCCP, 2019, 21, 25584-25596.

[12] Munasinghe A, Mathavan A, Mathavan A, Lin P, and Colina C. Molecular Insight into the Protein−Polymer Interactions in N‑Terminal PEGylated Bovine Serum Albumin, J. Phys. Chem. B, 2019, 123, 5193-5205. Front Cover

[13] Salomon-Ferrer R, Case D, and Walker R. An overview of the Amber biomolecular simulation package, WIREs Comput. Mol. Sci., 2013, 3, 198-210.

[14] Humphrey W, Dalke A, and Schulten K. VMD: Visual molecular dynamics, J. Mol. Graphics, 1996, 14, 33-38.

[15] Bakan A, Meireles LM and Bahar I. ProDy: Protein Dynamics Inferred from Theory and Experiments, Bioinformatics, 2011, 27, 1575-1577.

[16] Mathavan A, Mathavan A, Fortunato M and Colina CM. An All-Atomistic Molecular Dynamics Study to Determine the Structural Importance of Disulfide Bonds in Immunoglobulin G and Bovine Serum Albumin, AJUR, 2018, 15, 6-22.

Project Title: Characterizing Polymer Conjugated Substrate-Opioid Receptor Interactions

Faculty Mentor’s Name: Coray Colina 

Student Name: Akash  Mathavan 

Research Project Description:

For the past two decades, the epidemic of drug overdose involving opioids has become a severe public health crisis for numerous countries, including the United States. The consequences of these sweeping outbreaks have posed significant economic and societal implications that are as of yet unsolved [1]. The functional basis of available opioids is to serve as opioid receptor (OR) modulators, in which relevant targets are members of the GPCR (G-protein-coupled-receptors) family. Activation of GPCRs by these agonists facilitate the desired processes of pain management, but also trigger debilitating side effects such as gastrointestinal dysfunction, respiratory depression, and rewarding pathways that form the basis of addiction. Opioid receptors come in several subtypes (μ, δ, and κ), of which the μ-OR subtype is particularly researched due to targeting by existing drugs such as morphine [1]. Consequently, contemporary research has focused on the development of more precise agonists that preferentially activate pain-modulating pathways and has also explored the application of selective antagonists that can mitigate the severe side effects from therapeutic use of opioids [2-4]. The application of synthesized drugs targeting μ-OR have been studied due to the preferential activation or avoidance of downstream pathways associated with analgesia [2, 3]. However, the complexity in the profiles of such interactions has been a major barrier in identifying μ-opioid biased compounds. More recently, the potential of bioconjugates – biologic molecular hybrids consisting of macromolecular proteins or nucleic acids covalently bound to synthetic polymers – has been recognized and proposed to help survey functional selectivity in a variety of fields, including drug delivery [5]. Synthetic enhancement of therapeutic drugs via polymer conjugation has not only showed increased circulation time by increased hydrodynamic radii, but also indicated optimized activity through interactions with the polymer. However, underlying molecular mechanisms involved in such interactions are poorly understood. For example, Naloxol® is a recently developed opioid antagonist that was enhanced through conjugation with polyethylene glycol (PEG), termed Naloxegol® [4]. Addition of the polymer showed improved inhibitory activity in the gastrointestinal tract for morphine-induced constipation as well as reduced blood-brain barrier penetration; however, the binding pattern between PEGylated opioid and the OR has not been adequately characterized to elucidate induced changes in conformation or stability. Additionally, while PEG has been historically utilized in bioconjugates, other polymer architectures such as zwitterionic chains have been employed due to their unique properties, such as charged groups along the chain [6]. The complexity of polymer-macromolecule interactions in bioconjugates demands greater insight into the associated molecular mechanisms. As such, computational science, including molecular dynamics (MD) have been increasingly employed to examine the dynamics of these hybrids at the molecular level. Indeed, MD simulations of a variety of polymer linked bioconjugates, especially in protein-polymer formulations, have yielded greater understanding of specific interactions, particularly in regards to the impact of protein surface composition and geometry on the resulting polymer architecture and potential to cover key binding sites [7, 8]. Furthermore, while MD studies
have been performed to investigate the dynamics of opioid-OR binding [9], no current studies have investigated the impact of polymer conjugated opioids on opioid-OR interactions. We propose developing and employing MD simulations of a spectrum of polymer conjugated OR substrates. Polymers such as PEG or zwitterionic molecules will be covalently bound to substrates including Naloxol®/Naloxegol® [9], as well as model agonists such as Buprenorphine® [10], along with the μ-OR to elucidate resulting interactions and determine the optimal conjugation setup for receptor-substrate interactions.

  1. Rudd R.A., Aleshire N., Zibbell J.E., Gladden R.M. Increases in drug and opioid overdose deaths—United States, 2000–2014. MMWR Morb Mortal Wkly Rep. 2016, 64, 1378-1382.
  2. Madariaga-Mazón, A., Marmolejo-Valencia A.F., Li Y., Toll L., Houghten R.A., Martinez-Mayorga K. Mu-Opioid receptor biased ligands: A safer and painless discovery of analgesics? Drug Discovery Today 2017, 22, 1719-1729.
  3. Marmolejo-Valencia A. F., Martínez-Mayorga K. Allosteric modulation model of the mu opioid receptor by herkinorin, a potent not alkaloidal agonist, J Comput Aided Mol Des 2017, 31467-31482.
  4. Webster L., Chey W.D., Tack J., Lappalainen J., Diva U., Sostek M. Randomised clinical trial: the long-term safety and tolerability of naloxegol in patients with pain and opioid-induced constipation, Aliment Pharmacol Ther 2014, 40, 771-779.
  5. Veronese F.M., Mero A. The impact of PEGylation on biological therapies, BioDrugs 2008, 22, 315-329.
  6. Nguyen A.T., Baggerman J., Paulusse J., Zuilhof H., Rijn C. Bioconjugation of Protein-Repellent Zwitterionic Polymer Brushes Grafted from Silicon Nitride, Langmuir, 2012, 28, 604-610.
  7. Munasinghe A., Mathavan A., Mathavan A., Lin P., Colina C. Molecular Insight into the Protein−Polymer Interactions in N‑Terminal PEGylated Bovine Serum Albumin, J. Phys. Chem. B 2019, 123, 5196-5205.
  8. Munasinghe A., Mathavan A., Mathavan A., Lin P., Colina C. PEGylation within a confined hydrophobic cavity of a protein, PCCP, 2019, 21, 25584-25596.
  9. “Naloxegol.” DrugBank, 2019,
  10. “Buprenorphine.” DrugBank, 2016,
  11. Lipinski P., Jaroncyzk M., Dobrowolski J., Sadlej J. Molecular dynamics of fentanyl bound to μ-opioid receptor, J. Mol. Model 2019, 25, 143-161.
  12. Fortunato M.E., Colina C.M, pysimm: A python package for simulation of molecular systems, SoftwareX, 2017, 6, 7-12.
  13. Trott O., Olson A.J. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem, 2010, 31, 455-461.
  14. Salomon-Ferrer R., Case D., Walker R. An overview of the Amber biomolecular simulation package, WIREs Comput. Mol. Sci., 2013, 3, 198-210.
  15. Humphrey W., Dalke A., and Schulten K. VMD: Visual molecular dynamics, J. Mol. Graphics, 1996, 14, 33-38.
  16. Bakan A., Meireles L.M., and Bahar I. ProDy: Protein Dynamics Inferred from Theory and Experiments, Bioinformatics, 2011, 27, 1575-1577.