Interaction of phospholipids with proteins and peptides. New advances III

Cserháti, Tibor; Szőgyi, M.

doi:10.1016/0020-711x(93)90001-u

Cited by 8 publications

(2 citation statements)

References 261 publications

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“…Lipids and lipid–protein interactions play an increasingly appreciated and recognized role in many biological processes (see for reviews [9–11]). One interesting recent development is the bioinformatics approach, which enables the identification of lipid binding helical regions in proteins using the Heliquest web-server [6].…”

Section: Introductionmentioning

confidence: 99%

New User-Friendly Approach to Obtain an Eisenberg Plot and Its Use as a Practical Tool in Protein Sequence Analysis

Keller¹

2011

IJMS

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The Eisenberg plot or hydrophobic moment plot methodology is one of the most frequently used methods of bioinformatics. Bioinformatics is more and more recognized as a helpful tool in Life Sciences in general, and recent developments in approaches recognizing lipid binding regions in proteins are promising in this respect. In this study a bioinformatics approach specialized in identifying lipid binding helical regions in proteins was used to obtain an Eisenberg plot. The validity of the Heliquest generated hydrophobic moment plot was checked and exemplified. This study indicates that the Eisenberg plot methodology can be transferred to another hydrophobicity scale and renders a user-friendly approach which can be utilized in routine checks in protein–lipid interaction and in protein and peptide lipid binding characterization studies. A combined approach seems to be advantageous and results in a powerful tool in the search of helical lipid-binding regions in proteins and peptides. The strength and limitations of the Eisenberg plot approach itself are discussed as well. The presented approach not only leads to a better understanding of the nature of the protein–lipid interactions but also provides a user-friendly tool for the search of lipid-binding regions in proteins and peptides.

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Section: Introductionmentioning

confidence: 99%

New User-Friendly Approach to Obtain an Eisenberg Plot and Its Use as a Practical Tool in Protein Sequence Analysis

Keller¹

2011

IJMS

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“…When FB is secreted into the alveolar lining layer due to alveolar stress or lung injury, it can inhibit the lung surfactant DST lowering function and can be a contributing cause of the Adult or Acute Respiratory Distress Syndrome (ARDS) . In addition to reported interfacial interactions, ,,− there have been several reports about the interactions of serum proteins (FB or bovine serum albumin) with DPPC or other lipids in aqueous solution. − Thus, understanding interactions of FB with DPPC and other lipids may have impact in elucidating the etiology and possible treatment strategies for alveolar respiratory diseases. It is known that when DPPC monolayers are prepared on an aqueous surface, no protein (BSA or FB) injected in solution is adsorbed. , When protein is preadsorbed on the air/water interface, no DPPC vesicles adsorb.…”

Section: Introductionmentioning

confidence: 99%

Stability and State of Aggregation of Aqueous Fibrinogen and Dipalmitoylphosphatidylcholine Lipid Vesicles

et al. 2007

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The stability and state of aggregation of aqueous fibrinogen (FB) and dipalmitoylphosphatidylcholine (DPPC) vesicles in water or buffer at 25 degrees C were studied with dynamic light scattering (DLS), UV-vis spectroturbidimetry (ST), and cryo-transmission electron microscopy (cryo-TEM). In water, when 1000 ppm (0.10 wt %) DPPC dispersions were prepared with a protocol including extensive sonication, they contained mostly vesicles and were quite clear, transparent, and stable for at least 30 days. FB mixtures with water (0.075 wt %) were quite unstable and biphasic. They formed large aggregates which eventually precipitated. The addition of DPPC vesicles into these unstable FB dispersions reversed FB aggregation and precipitation and produced stable translucent microdispersions. The inferred lipid/protein aggregates were limited in size, with average diameters ranging from 200 to 300 nm. In buffer, DPPC dispersions were also clear and quite stable, with average dispersed particles diameter of ca. 90 nm. FB dissolved in aqueous buffer and formed transparent and stable solutions. Adding salt to an aggregated FB dispersion in water reversed the aggregation. FB aggregated and redissolved in the presence of the citrate and after the citrate was removed. There was no effect of citrate (present in FB initially) in the FB aggregation or redissolution. FB molecules in buffer form dimers or higher aggregates. Their average aggregation number is 2, determined with Rayleigh scattering analysis of turbidity data. The average hydrodynamic diameter of FB solutions from DLS was 30 nm. Mixing a stable FB solution in buffer and a stable DPPC dispersion in buffer produced highly unstable mixtures, in which large aggregates precipitated. These results have implications in understanding the interactions of lipids and proteins in many biological applications and food processing applications.

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Active vs. passive resistance, dose-response relationships, high dose chemotherapy, and resistance modulation: a hypothesis

Stewart

Raaphorst

et al. 1996

Invest New Drugs

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With chemotherapy, the in vitro and clinical dose-response curve is steep in some situations, but is relatively flat in others, possibly due to the mechanism by which tumors are resistant to chemotherapy. For tumors with resistance due to factors that actively decrease chemotherapy efficacy (e.g., p-glycoprotein, glutathione, etc.), one would predict that high dose chemotherapy and therapy with some resistance modulating agents would increase therapeutic efficacy. Such "active" resistance would most likely generally arise from gene amplification or over expression, and would be characterized by a shoulder on the log response vs. dose curve, with eventual saturation of the protective mechanism. On the other hand, one would expect that high dose chemotherapy and most resistance modulating agents would be of little value for tumors with resistance due to defective apoptosis or due to a deficiency in or decreased drug affinity for a drug target, drug activating enzyme, drug active uptake system, or essential cofactor. Such "passive" resistance would most likely generally arise from gene down regulation, deletion, or mutation, and would probably be characterized by a relatively flat log response vs. dose curve, or by a curve in which a steep initial section is followed by a plateau, as target, etc., is saturated. (If response were plotted vs. log dose, then compared to the curve for a sensitive cell line, the curve for active resistance would be analogous to the pharmacodynamic curve seen with competitive antagonism [i.e., a sigmoid curve shifted to the right], and the curve for most types of passive resistance would be analogous to the pharmacodynamic curve seen with noncompetitive antagonism [i.e., a sigmoid curve with reduced maximal efficacy]. As such, one might also refer to active vs. passive resistance as competitive vs. noncompetitive resistance, respectively.) Many tumor types probably possess a combination of active and passive mechanisms of resistance. New in vivo strategies could be helpful in defining dose-response relationships, mechanisms of resistance, and targets for resistance modulation. Such in vivo studies would be conducted initially in animals, but might also be tested clinically if animal studies demonstrated them to be feasible and useful. These in vivo studies would be conducted by randomizing 5-25 subjects to one of 10-20 dose levels over a potentially useful therapeutic range. Nonlinear regression analysis would then be used to define the characteristics of a curve generated by plotting against dose the log percent tumor remaining after the first course of therapy. While this might offer insight into the nature of resistance mechanisms present initially, plotting further tumor shrinkage vs. dose-intensity vs. course number for each later treatment course (or plotting dose-intensity vs. time to tumor progression) might provide information on how tumors become increasingly resistant to drugs following treatment.

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Interaction of phospholipids with proteins and peptides. New advances III

Cited by 8 publications

References 261 publications

New User-Friendly Approach to Obtain an Eisenberg Plot and Its Use as a Practical Tool in Protein Sequence Analysis

New User-Friendly Approach to Obtain an Eisenberg Plot and Its Use as a Practical Tool in Protein Sequence Analysis

Stability and State of Aggregation of Aqueous Fibrinogen and Dipalmitoylphosphatidylcholine Lipid Vesicles

Active vs. passive resistance, dose-response relationships, high dose chemotherapy, and resistance modulation: a hypothesis

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