Dependence of the Size of a Protein−SDS Complex on Detergent and Na<sup>+</sup> Concentrations

Gangabadage, Chinthaka Sanath; Najda, Andżelika; Bogdan, Diana Felicia; Wijmenga, Sybren S.; Tessari, Marco

doi:10.1021/jp710045e

Cited by 14 publications

(15 citation statements)

References 31 publications

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“…The calculated aggregation numbers of 104, 135 and 154 show a similar tendency as measured by Lipfert et al using SAXS ( Table 2) [17]. To support our interpretation and the ease of our assay, we like to note that increasing aggregation numbers with increasing detergent concentrations were also observed for other detergents using different techniques for example SANS, NMR, and SAXS as well ( Table 2) [8] [17]- [19], but in our case they are determined using a standard equipment present in virtually any biochemically focused laboratory.…”

Section: Resultssupporting

confidence: 81%

Analyzing the Physico-Chemical Parameters of Detergents and Detergent Mixtures

Tschapek¹,

Smits²,

Schmitt³

2015

ACES

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The most important physico-chemical characteristics describing detergent micelles are the CMC value and the aggregation number. These parameters depend critically on external conditions such as pH, ionic strength, buffer composition or temperature. However, the influence of these conditions on CMC or aggregation number is a priori not to predict, but the most important parameter. This holds especially for the aggregation number. Here, we present a simple, reliable and fast method for the analysis of detergent containing buffer systems. It enables the determination of CMC values and aggregation numbers of detergents as well as detergent mixtures in a 96well plate standard device relying on steady state fluorescence and fluorescence quenching. To prove the general applicability of our approach, we analyzed DDM as a prime example of a detergent and mixtures of DDM with six other detergents at different ratios to demonstrate the potential of our method.

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Section: Resultssupporting

confidence: 81%

Analyzing the Physico-Chemical Parameters of Detergents and Detergent Mixtures

Tschapek¹,

Smits²,

Schmitt³

2015

ACES

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“…For comparison, free SDS micelles have a correlation time of ϳ5.5 ns at 35°C (50), and the correlation time of a complex formed between SDS micelles and a 22-residue peptide similar in size to the 37-residue amylin was 6.6 ns (51). Although the agreement observed is good, we note that the correlation time of SDS micelles depends on a number of variables, including detergent concentration, ionic strength, and the molecules complexed to the micelle (52). Nevertheless, the 6.7-ns rotational correlation time is most consistent with amylin binding to the SDS micelles as a monomer.…”

Section: Amylin Adopts An ␣-Helical Structure In the Presence Of Sdsmentioning

confidence: 64%

Dynamic α-Helix Structure of Micelle-bound Human Amylin

Patil

Sheftic

et al. 2009

Journal of Biological Chemistry

177

219

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Amylin is an endocrine hormone that regulates metabolism. In patients afflicted with type 2 diabetes, amylin is found in fibrillar deposits in the pancreas. Membranes are thought to facilitate the aggregation of amylin, and membrane-bound oligomers may be responsible for the islet ␤-cell toxicity that develops during type 2 diabetes. To better understand the structural basis for the interactions between amylin and membranes, we determined the NMR structure of human amylin bound to SDS micelles. The first four residues in the structure are constrained to form a hairpin loop by the single disulfide bond in amylin. The last nine residues near the C terminus are unfolded. The core of the structure is an ␣-helix that runs from about residues 5-28. A distortion or kink near residues 18 -22 introduces pliancy in the angle between the N-and C-terminal segments of the ␣-helix. Mobility, as determined by 15 N relaxation experiments, increases from the N to the C terminus and is strongly correlated with the accessibility of the polypeptide to spin probes in the solution phase. The spin probe data suggest that the segment between residues 5 and 17 is positioned within the hydrophobic lipid environment, whereas the amyloidogenic segment between residues 20 and 29 is at the interface between the lipid and solvent. This orientation may direct the aggregation of amylin on membranes, whereas coupling between the two segments may mediate the transition to a toxic structure. Type 2 diabetes affects over 100 million people worldwide (1) and is thought to cost upward of $130 billion dollars a year to treat in the United States alone (2). The endocrine hormone amylin (also known as islet amyloid polypeptide) appears to have key roles in diabetes pathology (3-5). The normal functions of amylin include the inhibition of glucagon secretion, slowing down the emptying of the stomach, and inducing a feeling of satiety through the actions of the hormone on neurons of the hypothalamus in the brain (5). The effects of amylin are exerted in concert with those of insulin and reduce the level of glucose in the blood (3, 5). Circulating amylin levels increase in a number of pathological conditions, including obesity, syndrome X, pancreatic cancer, and renal failure (3). Amylin levels together with insulin are raised initially in type 2 diabetes but fall as the disease progresses to a stage where the pancreatic islets of Langerhans ␤-cells that synthesize amylin no longer function (3).One of the hallmarks of type 2 diabetes, found in 90% of patients, is the formation of extracellular amyloid aggregates composed of amylin (3-5). The amyloid deposits accumulate in the interstitial fluid between islet cells and are usually juxtaposed with the ␤-cell membranes (3). Aggregates of amylin are toxic when added to cultures of ␤-cells, so that the amyloid found in situ may be responsible for ␤-cell death as type 2 diabetes progresses (6, 7). Genetic evidence that amylin is directly involved in pathology includes a familial S20G mutation that leads to early ...

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“…To illustrate this, concentrated surfactant solutions of SDS micelle systems were titrated into 20 mM buffer of pH 2 and 7.4. At concentrations below the CMC, the reaction is → micelles monomers (2) and at concentrations above the CMC, the reaction is…”

Section: Critical Micelle Concentration Determinationmentioning

confidence: 99%

pH-Dependent Differential Interacting Mechanisms of Sodium Dodecyl Sulfate with Bovine Serum Fetuin: A Biophysical Insight

et al. 2014

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Sodium dodecyl sulfate (SDS)-glycoprotein interaction serves as a model for a biological membrane. To get mechanistic insight into the interaction of SDS and glycoprotein, the effect of SDS on bovine serum fetuin (BSF) was studied in subcritical micellar concentrations at pH 7.4 and pH 2 using multiple approaches. SDS interacts electrostatically with BSF through its negatively charged head groups at pH 2 and hydrophobically via its alkyl chains at pH 7.4 up to a 1:20 molar ratio of BSF to SDS. However, at higher concentrations of SDS, BSF undergoes amyloid fibril formation at pH 2, as confirmed by enhanced ThT fluorescence, β-sheet formation, and TEM microscopy, whereas BSF undergoes induction of an α-helical structure in the presence of higher SDS concentration at pH 7.4. The increase in α-helical content with increasing SDS concentrations constrains the environment around tryptophan. As a consequence, the interconversion of tryptophan conformers decreases, resulting in a decrement of the fluorescence lifetime for BSF in the presence of SDS at pH 7.4.

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Dependence of the Size of a Protein−SDS Complex on Detergent and Na⁺ Concentrations

Cited by 14 publications

References 31 publications

Analyzing the Physico-Chemical Parameters of Detergents and Detergent Mixtures

Analyzing the Physico-Chemical Parameters of Detergents and Detergent Mixtures

Dynamic α-Helix Structure of Micelle-bound Human Amylin

pH-Dependent Differential Interacting Mechanisms of Sodium Dodecyl Sulfate with Bovine Serum Fetuin: A Biophysical Insight

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Dependence of the Size of a Protein−SDS Complex on Detergent and Na+ Concentrations

Cited by 14 publications

References 31 publications

Analyzing the Physico-Chemical Parameters of Detergents and Detergent Mixtures

Analyzing the Physico-Chemical Parameters of Detergents and Detergent Mixtures

Dynamic α-Helix Structure of Micelle-bound Human Amylin

pH-Dependent Differential Interacting Mechanisms of Sodium Dodecyl Sulfate with Bovine Serum Fetuin: A Biophysical Insight

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Dependence of the Size of a Protein−SDS Complex on Detergent and Na⁺ Concentrations