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Related Concept Videos

Membrane Fluidity01:23

Membrane Fluidity

Cell membranes are composed of phospholipids, proteins, and carbohydrates loosely attached to one another through chemical interactions. Molecules are generally able to move about in the plane of the membrane, giving the membrane its flexible nature called fluidity. Two other features of the membrane contribute to membrane fluidity: the chemical structure of the phospholipids and the presence of cholesterol in the membrane.Fatty acids tails of phospholipids can be either saturated or...
Cell Specific Gene Expression01:58

Cell Specific Gene Expression

Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
Membrane Fluidity01:26

Membrane Fluidity

Membrane fluidity is explained by the fluid mosaic model of the cell membrane, which describes the plasma membrane structure as a mosaic of components—including phospholipids, cholesterol, proteins, and carbohydrates—that gives the membrane a fluid character.
Mosaic nature of the membrane
The mosaic characteristic of the membrane helps the plasma membrane remain fluid. The integral proteins and lipids exist as separate but loosely-attached molecules in the membrane. The membrane is a relatively...
Membrane Asymmetry Regulating Transporters01:19

Membrane Asymmetry Regulating Transporters

Enzymes like flippase, floppase, and scramblase transfer phospholipids from one layer to another in the membrane, thereby affecting membrane asymmetry.
Flippase
Eukaryotic flippases are type-IV P-type ATPases or P4-ATPases belonging to P-type ATPase family proteins that are membrane-bound pumps involved in the ATP-mediated transport of ions and molecules across the membrane. Flippases flip specific phospholipids from the outer to the inner leaflet of a membrane. All P4-ATPases have one...
Diversity in Cell Signaling Responses01:22

Diversity in Cell Signaling Responses

The physiological function of a cell and cellular communication are outcomes of a range of extrinsic signals, intracellular signaling pathways, and cellular responses. No two cell types express the same repertoire of signaling components. Receptors are highly selective for their cognate ligands, but once activated, they can alter multiple cellular processes such as DNA transcription, protein synthesis, and metabolic activity. 
Graded and Abrupt Responses
Some signaling systems generate...

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Related Experiment Video

Updated: Jun 28, 2026

Mapping Molecular Diffusion in the Plasma Membrane by Multiple-Target Tracing MTT
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Valency-affinity mapping of multivalent liposomes for tunable target cell discrimination.

Victor A Garcia1, Paulina M Eberts2, Brenda M Ogle1

  • 1Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota, USA.

Drug Delivery
|June 23, 2025
PubMed
Summary

High-affinity, high-valency nanoparticles show optimal binding to target cells. Researchers developed a binding performance index (BPI) to assess nanoparticle targeting efficiency and tune ligand properties for improved therapeutic applications.

Keywords:
DARPinsHER2Multivalencynanoparticlesreceptor-targetingselectivity

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A Quantitative Fluorescence Microscopy-based Single Liposome Assay for Detecting the Compositional Inhomogeneity Between Individual Liposomes
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Area of Science:

  • Biotechnology
  • Nanomedicine
  • Molecular Biology

Background:

  • Multivalency in ligand-functionalized nanoparticles enhances target cell binding but risks off-target interactions.
  • Optimizing nanoparticle binding requires balancing ligand affinity and nanoparticle valency for specific cell targets.

Purpose of the Study:

  • To investigate how ligand affinity and liposome valency influence nanoparticle binding performance.
  • To develop and validate a Binding Performance Index (BPI) for assessing nanoparticle targeting efficacy.
  • To demonstrate the ability to rationally tune nanoparticle binding properties for therapeutic applications.

Main Methods:

  • Designed ankyrin repeat proteins (DARPins) with varying HER2-binding affinities were conjugated to PEGylated liposomes at different concentrations.
  • Binding performance was evaluated using mixed cell suspensions (HER2-high SKBR3 and HER2-low T47D) and HEK293T cells with heterogeneous HER2-EGFP expression.
  • A HER2 expression threshold was varied to determine optimal binding performance and analyze BPI sensitivity.

Main Results:

  • High-valency liposomes with high-affinity DARPins achieved the highest BPI (>0.8) in mixed cell suspensions.
  • Continuous binding response curves revealed maximum BPI values (>0.85) and optimal HER2 thresholds (HER2_OPT).
  • BPI proved more sensitive than traditional selectivity measures to off-target binding and on-target binding efficiency.
  • DARPin valency and affinity were shown to be tunable parameters for adjusting HER2_OPT.

Conclusions:

  • The Binding Performance Index (BPI) provides a sensitive metric for evaluating nanoparticle targeting efficacy.
  • Ligand affinity and nanoparticle valency are critical, tunable parameters for optimizing targeted delivery.
  • The developed approach facilitates rapid optimization of nanoparticle ligand properties for specific therapeutic targets.