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 Concept Videos

Synthetic Biology02:55

Synthetic Biology

Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
Golden rice is a genetically modified...

You might also read

Related Articles

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

Sort by
Same author

Adhesion G protein-coupled receptors.

Pharmacological reviews·2026
Same author

Binding of Glycyl-tRNA synthetase to Mengovirus RNA stimulates translation.

Nucleic acids research·2026
Same author

PARANOiD: Pipeline for Automated Read ANalysis of iCLIP Data.

Bioinformatics (Oxford, England)·2025
Same author

Author Correction: Computational design of synthetic receptors with programmable signalling activity for enhanced cancer T cell therapy.

Nature biomedical engineering·2025
Same author

Computational design of synthetic receptors with programmable signalling activity for enhanced cancer T cell therapy.

Nature biomedical engineering·2025
Same author

Minimal shuttle vectors for <i>Saccharomyces cerevisiae</i>.

Synthetic biology (Oxford, England)·2025

Related Experiment Video

Updated: Jun 19, 2026

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Membrane Protein Design: From Reprogramming Functions to AI-Guided De Novo Design Approaches.

Robert E Jefferson1, Patrick Barth2

  • 1Department of Chemistry, King's College London, London WC2R 2LS, U.K.

Chemical Reviews
|June 17, 2026
PubMed
Summary
This summary is machine-generated.

Computational membrane protein design now integrates AI and high-throughput screening. This advances engineering of cell functions, synthetic proteins, and biosensing platforms.

More Related Videos

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
05:08

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

Designing a Bio-responsive Robot from DNA Origami
13:32

Designing a Bio-responsive Robot from DNA Origami

Published on: July 8, 2013

Related Experiment Videos

Last Updated: Jun 19, 2026

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
05:08

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

Designing a Bio-responsive Robot from DNA Origami
13:32

Designing a Bio-responsive Robot from DNA Origami

Published on: July 8, 2013

Area of Science:

  • Biochemistry
  • Molecular Biology
  • Bioengineering

Background:

  • Computational protein design has advanced significantly.
  • Membrane proteins are crucial for cellular functions and therapeutic targets.
  • AI and experimental screening are key drivers of progress.

Purpose of the Study:

  • To review the evolution and current state of computational membrane protein design.
  • To highlight the potential of engineered membrane proteins for novel applications.
  • To discuss the integration of computational methods with experimental techniques.

Main Methods:

  • Physics-based modeling.
  • High-throughput experimental screening.
  • Artificial intelligence (AI) technologies.

Main Results:

  • Computational design now enables stabilization of therapeutic targets.
  • Engineered membrane proteins can rewire cellular behaviors.
  • Synthetic transmembrane architectures can be constructed de novo.
  • Reprogramming cellular signaling in response to custom ligands is achievable.

Conclusions:

  • Computational membrane protein design is a mature discipline.
  • These advancements pave the way for generalizable biosensing platforms.
  • The creation of de novo transmembrane proteins with tailored functions is now feasible.