Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

A model for mucus glycoprotein structure.

A Silberberg1

  • 1Department of Polymer Research, Weizmann Institute of Science Rehovot, Israel.

Biorheology
|January 1, 1987
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Tradeoffs in choice between risk and delay depend on monetary amounts.

Journal of the experimental analysis of behavior·2006
Same author

Stock optimizing in choice when a token deposit is the operant.

Journal of the experimental analysis of behavior·2002
Same author

Natural choice in nonhuman primates.

Journal of experimental psychology. Animal behavior processes·1998
Same author

Pointing At Smaller Food Amounts In An Analogue Of Boysen And Berntson's (1995) Procedure.

Journal of the experimental analysis of behavior·1996
Same author

Stock optimizing: maximizing reinforcers per session on a variable-interval schedule.

Journal of the experimental analysis of behavior·1993
Same author

A.L. Copley, the medical scientist and biorheologist.

Biorheology·1992
Same journal

Layer-specific residual stretch changes along the human aorta: Effects of age, gender, and circumferential quadrant.

Biorheology·2025
Same journal

The effect of particle seeding on the rheological properties of blood Analog fluid used during laser Doppler velocimetry.

Biorheology·2025
Same journal

Biomechanical changes in abdominal aortic aneurysms involve a prolonged post-failure phase.

Biorheology·2025
Same journal

Examination of hemorheological and exerkine concentrations at four-week whole body vibration exercise in obese women: A pilot study.

Biorheology·2025
Same journal

Measurement of adhesive strength between the epidermal and inner tissues of plant stems using a tensile tester.

Biorheology·2025
Same journal

Blood rheology and systemic oxidative status in patients with acromegaly.

Biorheology·2025
See all related articles

Mucus glycoproteins form chain-like aggregates through a lectin-binding mechanism. This model explains the polymer-like behavior of mucus structural subunits.

Area of Science:

  • Biochemistry
  • Biophysics
  • Materials Science

Background:

  • Mucus glycoproteins are large, heavily glycosylated proteins crucial for biological lubrication and protection.
  • The structural organization of these glycoproteins dictates their viscoelastic properties.

Purpose of the Study:

  • To propose and analyze a model for the structural glycoprotein subunit of mucus.
  • To investigate the self-assembly mechanism of mucus glycoproteins based on their molecular structure.

Main Methods:

  • Analysis of existing literature data on mucus glycoprotein structure and behavior.
  • Development of a lectin-based model for subunit interaction and aggregation.
  • Application of polymer physics principles (Kuhn statistical element) to model aggregation.

Related Experiment Videos

Main Results:

  • The structural glycoprotein subunit (~500,000Da) features a glycosylated rod with a cysteine-rich region.
  • A proposed lectin model, involving disulfide-stabilized folds, explains subunit binding.
  • Literature data supports finite-sized, separate chain aggregates, consistent with the lectin model.

Conclusions:

  • The lectin model provides a plausible mechanism for mucus glycoprotein aggregation.
  • The model successfully predicts the polymer-like behavior of mucus at low binding site density.
  • Subunit aggregation is driven by specific, rare sugar sequence recognition via lectin interactions.