Effects of Stereochemistry and Hydrogen Bonding on Glycopolymer–Amyloid-β Interactions

Bristol, Ashleigh N.; Saha, Jhinuk; George, Hannah E.; Das, Pradipta; Kemp, Lisa K.; Jarrett, William L.; Rangachari, Vijayaraghavan; Morgan, Sarah E.

doi:10.1021/acs.biomac.0c01077

Cited by 16 publications

(20 citation statements)

References 69 publications

(95 reference statements)

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“…Nevertheless, it is evident that GM1 ganglioside enrichment promotes oligomers vis-à-vis membrane disruption as opposed to unenriched liposomes. To specifically see whether glycoform distributions on the gangliosides have an effect on these properties, as we had seen before with Aβ-glycopolymer interactions 43,44 , TBE liposomes were also enriched with GM3 gangliosides which have significant sugar distribution differences with GM1 (Figure S2). By doing so, none or minimal leakage of dye upon incubation of Aβ monomers with 50% GM3 enriched TBE LUVs (; Figure 4e) was observed.…”

Section: Resultsmentioning

confidence: 87%

Ganglioside enriched phospholipid vesicles induce cooperative Aβ oligomerization and membrane disruption

Saha

Bose

Dhakal

et al. 2022

Preprint

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A major hallmark of Alzheimer disease (AD) is the accumulation of extracellular aggregates of amyloid-β (Aβ). Structural polymorphism observed among Aβ fibrils in AD brains seem to correlate with the clinical sub-types suggesting a link between fibril polymorphism and pathology. Since fibrils emerge from a templated growth of low-molecular weight oligomers, understanding the factors affecting oligomer generation is important. The membrane lipids are key factors that influence early stages of Aβ aggregation and oligomer generation, and cause membrane disruption. We have previously showed that conformationally discrete Aβ oligomers can be generated by modulating the charge, composition, chain length of lipids and surfactants. Here, we extend our studies into liposomal models by investigating Aβ oligomerization on large unilamellar vesicles (LUVs) of total brain extracts (TBE), reconstituted lipid rafts (LRs) or 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC). Specifically, we varied the vesicle composition by varying the amount of GM1 gangliosides added as a constituent. We found that liposomes enriched in GM1 induce the formation of toxic, low-molecular weight oligomers that are isolable in a lipid-complexed form. Importantly, the data indicate that the oligomer formation and membrane disruption are highly cooperative processes. Numerical simulations on the experimental data confirm cooperativity and reveal that GM1-enriched liposomes form twice as many numbers of pores as those without GM1. Overall, this study uncovers mechanisms of cooperativity between oligomerization and membrane disruption under specific lipid compositional bias, and refocuses the significance of the early stages of Aβ aggregation in polymorphism, propagation, and toxicity in AD.

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Section: Resultsmentioning

confidence: 87%

Ganglioside enriched phospholipid vesicles induce cooperative Aβ oligomerization and membrane disruption

Saha

Bose

Dhakal

et al. 2022

Preprint

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“…Helical wrapping of SWCNTs by natural polysaccharides and synthetic glycopolymers is an effective approach to preserve nanotube properties while stabilizing tubes in an aqueous environment ( Star et al, 2002 ; Hasegawa et al, 2004 ; Dohi et al, 2006 ; Cantwell et al, 2020 ). In addition to van der Waals attractions and hydrophobic interactions between the hydrophobic faces of the pyranose rings and the hydrophobic surface of nanotubes, intra- and inter-molecular hydrogen bonds of carbohydrates with neighboring sugar units and water molecules further stabilize the helical conformation of polymers on the surface of nanotubes ( Çarçabal et al, 2005 ; Bristol et al, 2020 ; Liu et al, 2012 ).…”

Section: Resultsmentioning

confidence: 99%

“…Due to the relatively weak interactions between monomeric saccharide and CBPs featuring hydrogen bonding and chelation with ions, biological systems employ a saccharide-assembly structure of oligosaccharides to amplify carbohydrate-protein interactions ( Zhang et al, 2010 ; Cecioni et al, 2015 ; Bernardi et al, 2013 ). Therefore, developing biomimetic synthetic materials that feature multivalent carbohydrate-protein interactions has vast potential in biomedical applications, including biosensing, drug delivery, therapeutics, and pathogen inhibition ( Zhang et al, 2010 ; Richards et al, 2012 ; Miura et al, 2016 ; Bristol et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Glycopolymer-Wrapped Carbon Nanotubes Show Distinct Interaction of Carbohydrates With Lectins

et al. 2022

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Glyconanomaterials with unique nanoscale property and carbohydrate functionality show vast potential in biological and biomedical applications. We investigated the interactions of noncovalent complexes of single-wall carbon nanotubes that are wrapped by disaccharide lactose-containing glycopolymers with the specific carbohydrate-binding proteins. The terminal galactose (Gal) of glycopolymers binds to the specific lectin as expected. Interestingly, an increased aggregation of nanotubes was also observed when interacting with a glucose (Glc) specific lectin, likely due to the removal of Glc groups from the surface of nanotubes resulting from the potential binding of the lectin to the Glc in the glycopolymers. This result indicates that the wrapping conformation of glycopolymers on the surface of nanotubes potentially allows improved accessibility of the Glc for specific lectins. Furthermore, it shows that the interaction between Glc groups in the glycopolymers and nanotubes play a key role in stabilizing the nanocomplexes. Overall, our results demonstrate that nanostructures can enable conformation-dependent interactions of glycopolymers and proteins and can potentially lead to the creation of versatile optical sensors for detecting carbohydrate-protein interactions with enhanced specificity and sensitivity.

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“…The blue surfaces of the P0A223 indicates that the interpolated charge of the entire P0A223 is higher than that of P0A223. In general, the interpolated charge surface are often used to determine hydrogen bonding patterns, electrostatic interaction and strengths of salt bridges in biomolecular simulations 59 . Many studies have also confirmed that amino acids with charged side chains could be regarded as the important factor for the increase of the thermostability of proteins 35 , 57 where positively and negatively charged amino acids contain (Arg, His and Lys) and (Asp and Glu), respectively.…”

Section: Resultsmentioning

confidence: 99%

A novel sequence-based predictor for identifying and characterizing thermophilic proteins using estimated propensity scores of dipeptides

Charoenkwan

Chotpatiwetchkul

Lee

et al. 2021

Sci Rep

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Owing to their ability to maintain a thermodynamically stable fold at extremely high temperatures, thermophilic proteins (TTPs) play a critical role in basic research and a variety of applications in the food industry. As a result, the development of computation models for rapidly and accurately identifying novel TTPs from a large number of uncharacterized protein sequences is desirable. In spite of existing computational models that have already been developed for characterizing thermophilic proteins, their performance and interpretability remain unsatisfactory. We present a novel sequence-based thermophilic protein predictor, termed SCMTPP, for improving model predictability and interpretability. First, an up-to-date and high-quality dataset consisting of 1853 TPPs and 3233 non-TPPs was compiled from published literature. Second, the SCMTPP predictor was created by combining the scoring card method (SCM) with estimated propensity scores of g-gap dipeptides. Benchmarking experiments revealed that SCMTPP had a cross-validation accuracy of 0.883, which was comparable to that of a support vector machine-based predictor (0.906–0.910) and 2–17% higher than that of commonly used machine learning models. Furthermore, SCMTPP outperformed the state-of-the-art approach (ThermoPred) on the independent test dataset, with accuracy and MCC of 0.865 and 0.731, respectively. Finally, the SCMTPP-derived propensity scores were used to elucidate the critical physicochemical properties for protein thermostability enhancement. In terms of interpretability and generalizability, comparative results showed that SCMTPP was effective for identifying and characterizing TPPs. We had implemented the proposed predictor as a user-friendly online web server at http://pmlabstack.pythonanywhere.com/SCMTPP in order to allow easy access to the model. SCMTPP is expected to be a powerful tool for facilitating community-wide efforts to identify TPPs on a large scale and guiding experimental characterization of TPPs.

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Effects of Stereochemistry and Hydrogen Bonding on Glycopolymer–Amyloid-β Interactions

Cited by 16 publications

References 69 publications

Ganglioside enriched phospholipid vesicles induce cooperative Aβ oligomerization and membrane disruption

Ganglioside enriched phospholipid vesicles induce cooperative Aβ oligomerization and membrane disruption

Glycopolymer-Wrapped Carbon Nanotubes Show Distinct Interaction of Carbohydrates With Lectins

A novel sequence-based predictor for identifying and characterizing thermophilic proteins using estimated propensity scores of dipeptides

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