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Related Experiment Video

Updated: Jun 10, 2026

Production of Disulfide-stabilized Transmembrane Peptide Complexes for Structural Studies

Production of Disulfide-stabilized Transmembrane Peptide Complexes for Structural Studies

Published on: March 6, 2013

3D structural models of transmembrane proteins.

Alexandre G de Brevern¹

¹INSERM UMR-S 665, Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), Institut National de Transfusion Sanguine (INTS), Université Paris Diderot - Paris 7, Paris, France. alexandre.debrevern@univ-paris-diderot.fr

Methods in Molecular Biology (Clifton, N.J.)

|July 29, 2010

Summary

This summary is machine-generated.

Accurate structural models of transmembrane proteins are crucial for understanding biological processes and diseases. Current methods combine comparative modeling with secondary structure prediction, emphasizing experimental data for reliable results.

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Last Updated: Jun 10, 2026

Production of Disulfide-stabilized Transmembrane Peptide Complexes for Structural Studies

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Expression and Purification of the Human Lipid-sensitive Cation Channel TRPC3 for Structural Determination by Single-particle Cryo-electron Microscopy

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Method to Visualize and Analyze Membrane Interacting Proteins by Transmission Electron Microscopy

Method to Visualize and Analyze Membrane Interacting Proteins by Transmission Electron Microscopy

Published on: March 5, 2017

Area of Science:

Structural Biology
Biochemistry
Computational Biology

Background:

Transmembrane proteins play vital roles in biological processes and disease pathogenesis.
Limited availability of experimental 3D structures hinders research on these critical macromolecules.
The unique membrane environment presents challenges for structural determination.

Purpose of the Study:

To outline effective strategies for building structural models of transmembrane proteins.
To address the limitations of automatic homology modeling for these proteins.
To highlight the importance of integrating experimental data in structural modeling.

Main Methods:

Utilizing comparative modeling combined with secondary structure prediction for transmembrane protein modeling.
Employing refinement and assessment steps, potentially iterating through comparative modeling.
Incorporating analysis of helix-helix and helix-lipid interactions, and quaternary structure assembly.

Main Results:

A multi-step protocol involving secondary structure prediction enhances comparative modeling accuracy.
Iterative refinement and assessment are crucial for improving structural model quality.
Consideration of specific interactions and oligomeric states contributes to more comprehensive models.

Conclusions:

Complex protocols integrating prediction and modeling are necessary for transmembrane protein structures.
Experimental data integration is paramount for validating and refining structural models.
Advanced modeling approaches can now account for complex interactions and quaternary structures.