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Related Concept Videos

Rab Cascades01:25

Rab Cascades

Rab GTPases act in a regulated cascade during membrane fusion, helping the lipid bilayers mix. The Rab family of proteins are active when bound to GTP, and inactive when bound to GDP. Hence, they act as guanine nucleotide-dependent molecular switches. Rab-GTP recognizes and binds to long or short-range tethering proteins to capture the target vesicle. These tethers coordinate with SNAREs on the vesicle and the target membrane to assemble the trans SNARE complex that locks the mixing bilayers.
Rab Proteins01:14

Rab Proteins

Rab proteins constitute the largest family of monomeric GTPases, of which 70 members are present in humans. Rab proteins and their effectors regulate consecutive stages of vesicle transport such as vesicle transport, docking, and fusion to the correct recipient membrane.
Rab proteins switch between a cytosolic, GDP-bound inactive state and a membrane-anchored, GTP-bound active state. By themselves, Rabs show slow rates of GDP/GTP exchange and GTP hydrolysis. Thus, Rab proteins are considered...
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...
Insertion of Multi-pass Transmembrane Proteins in the RER01:29

Insertion of Multi-pass Transmembrane Proteins in the RER

The rough ER membrane synthesizes, assembles, and embeds transmembrane proteins in diverse topologies. These proteins function as transporters or channels and can remain in the ER membrane or are sent to the Golgi complex, lysosome, and cell membrane.
The multipass transmembrane proteins are the type IV integral membrane proteins with multiple topogenic sequences determining their spatial arrangement in the ER membrane. Nearly all multipass proteins lack a cleavable signal sequence and use...
Insertion of Single-pass Transmembrane Proteins in the RER01:26

Insertion of Single-pass Transmembrane Proteins in the RER

Integral membrane proteins are proteins adhered to the lipid bilayer of a cell organelle or membrane. They can be of two types: transmembrane integral proteins that span the lipid bilayer and monotopic proteins that are attached to either side of the membrane but do not pass through it.
Integral transmembrane proteins possess transmembrane and extra membrane domains. The transmembrane domains are primarily made of 20-25 hydrophobic amino acids arranged in a helical secondary confirmation. These...
Export of Misfolded Proteins out of the ER01:32

Export of Misfolded Proteins out of the ER

After folding, the ER assesses the quality of secretory and membrane proteins. The correctly folded proteins are cleared by the calnexin cycle for transport to their final destination, while misfolded proteins are held back in the ER lumen. The ER chaperones attempt to unfold and refold the misfolded proteins but sometimes fail to achieve the correct native conformation. Such terminally misfolded proteins are then exported to the cytosol by ER-associated degradation or ERAD pathway for...

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Updated: Jun 4, 2026

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
09:43

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

MolMeDB RDF: transforming a relational database about biological membranes to the RDF format to increase

Dominik Martinát1, Jakub Juračka2, Jakub Galgonek3

  • 1Department of Physical Chemistry, Faculty of Science, Palacký University Olomouc, 17. Listopadu 12, 771 46, Olomouc, Czech Republic. dominik.martinat@upol.cz.

Journal of Cheminformatics
|June 3, 2026
PubMed
Summary
This summary is machine-generated.

MolMeDB now offers compound-membrane interaction data in Resource Description Framework (RDF) format. This enables enhanced data federation and complex queries for predictive pharmacology and drug discovery.

Keywords:
DatabaseMembraneRDFSPARQLSmall moleculeTransporter

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09:43

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Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases
07:26

Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases

Published on: March 19, 2018

Area of Science:

  • Pharmacology and Cheminformatics
  • Computational Biology
  • Data Science

Background:

  • Predictive pharmacology relies on understanding molecular behavior within biological membranes.
  • Accurate modeling of bioavailability and target engagement is crucial for drug development.
  • Existing compound-membrane interaction data requires better integration and accessibility.

Purpose of the Study:

  • To semantically transform the MolMeDB database into Resource Description Framework (RDF) format.
  • To expose the RDF data through a public SPARQL endpoint for automated reasoning and data federation.
  • To enhance semantic interoperability by incorporating community-standard ontologies.

Main Methods:

  • Curated compound-membrane interaction data from MolMeDB was converted into RDF.
  • The RDF schema was designed to align with ontologies used by PubChem and ChEMBL.
  • A public SPARQL endpoint was established to serve the RDF dataset.

Main Results:

  • MolMeDB is now available as machine-readable graph data, linking molecules, membranes, and transporters.
  • The SPARQL endpoint facilitates flexible federated querying, including structural queries via SACHEM.
  • Enhanced semantic interoperability allows for complex cross-database queries.

Conclusions:

  • The MolMeDB RDF dataset significantly improves the accessibility and integration of compound-membrane interaction data.
  • This resource empowers advanced computational pharmacology and drug discovery research.
  • The adoption of standard ontologies ensures broad compatibility and future-proofs the data resource.