Jove
Visualize
Contáctanos

Videos de Conceptos Relacionados

Protein-protein Interfaces02:04

Protein-protein Interfaces

13.2K
Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
13.2K
Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

11.3K
Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to...
11.3K
Protein Networks02:26

Protein Networks

4.1K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.1K
Protein Organization01:13

Protein Organization

143.4K
Overview
143.4K
Protein Complex Assembly02:41

Protein Complex Assembly

10.8K
Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...
10.8K
Mechanical Protein Functions01:58

Mechanical Protein Functions

5.1K
Proteins perform many mechanical functions in a cell. These proteins can be classified into two general categories- proteins that generate mechanical forces and proteins that are subjected to mechanical forces. Proteins providing mechanical support to the structure of the cell, such as keratin, are subjected to mechanical force, whereas proteins involved in cell movement and transport of molecules across cell membranes, such as an ion pump, are examples of generating mechanical force. 
5.1K

También podría leer

Artículos Relacionados

Artículos vinculados a este trabajo por autores compartidos, revista y gráfico de citas.

Ordenar por
Same author

Evaluating the role of pretraining dataset size and diversity on single-cell foundation model performance.

Nature methods·2026
Same author

Scalable and cost-efficient custom gene library assembly from oligopools.

Science advances·2026
Same author

Closing the loop: Experimentally validated methods in artificial intelligence-driven protein design.

Current opinion in structural biology·2026
Same author

Tackling the complexity of cancer with generative models.

Cell·2026
Same author

Sequence Display enables large-scale sequence-activity datasets for rapid protein evolution.

Nature biotechnology·2026
Same author

Scalable nonparametric clustering with unified marker gene selection for single-cell RNA-seq data.

Cell reports methods·2026
Same journal

Whole-cell particle-based digital twin simulations from 4D lattice light-sheet microscopy data.

Cell·2026
Same journal

Systematic discovery of pathogen effector functions across human pathogens and pathways.

Cell·2026
Same journal

Structural basis for host membrane binding and remodeling by invading malaria parasites.

Cell·2026
Same journal

Multiscale integration of tissue and chromatin context converts cell heterogeneity into stable intestinal patterning.

Cell·2026
Same journal

Arc mediates intercellular tau transmission via extracellular vesicles.

Cell·2026
Same journal

Electromagnetic field-inducible in vivo gene switch for remote spatiotemporal control of gene expression.

Cell·2026
Ver todos los artículos relacionados
JoVE
x logofacebook logolinkedin logoyoutube logo
ACERCA DE JoVE
Visión GeneralLiderazgoBlogCentro de Ayuda JoVE
AUTORES
Proceso de PublicaciónConsejo EditorialAlcance y PolíticasRevisión por ParesPreguntas FrecuentesEnviar
BIBLIOTECARIOS
TestimoniosSuscripcionesAccesoRecursosConsejo Asesor de BibliotecasPreguntas Frecuentes
INVESTIGACIÓN
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchivo
EDUCACIÓN
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualCentro de Recursos para ProfesoresSitio de Profesores
Términos y Condiciones de Uso
Política de Privacidad
Políticas

Video Experimental Relacionado

Updated: Sep 10, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.3K

Simplificar la ingeniería de proteínas con el aprendizaje profundo

Kevin K Yang1, Ava P Amini1

  • 1Microsoft Research, Cambridge, MA 02142, USA.

Cell
|August 22, 2025
PubMed
Resumen
Este resumen es generado por máquina.

Los modelos de aprendizaje profundo simplifican la ingeniería de proteínas para la edición del genoma. Los investigadores mejoraron los sistemas de edición del genoma utilizando un diseño de secuencia de columna vertebral fija, lo que permite modificaciones genéticas precisas y a gran escala.

Más Videos Relacionados

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

17.1K
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

340

Videos de Experimentos Relacionados

Last Updated: Sep 10, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.3K
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

17.1K
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

340

Área de la Ciencia:

  • Bioquímica y Biología Molecular
  • La bioingeniería
  • La genómica

Sus antecedentes:

  • La ingeniería de proteínas aprovecha modelos computacionales para diseñar nuevas funciones de proteínas.
  • Los modelos de diseño de secuencias de columna vertebral fijas existentes ofrecen una base para las tareas de ingeniería de proteínas.
  • Las tecnologías de edición del genoma requieren componentes de proteínas precisos y funcionales.

Objetivo del estudio:

  • Diseñar diversos sistemas de edición del genoma con una funcionalidad mejorada.
  • Para demostrar el poder de los enfoques simplificados de aprendizaje profundo en la ingeniería de proteínas.
  • Para permitir capacidades de edición del genoma a gran escala y a gran escala.

Principales métodos:

  • Desarrollo de modelos de diseño de secuencias fijas existentes.
  • Aplicación de estrategias de aprendizaje profundo para el diseño de secuencias de proteínas.
  • Validación experimental de sistemas de edición de genoma diseñados.

Principales resultados:

  • Ingeniería exitosa de diversos sistemas de edición del genoma con una funcionalidad mejorada.
  • Demostración de las capacidades de edición del genoma de grano fino.
  • Presentación de aplicaciones de edición del genoma a gran escala.
  • Validación experimental sólida de los sistemas diseñados.

Conclusiones:

  • La simplicidad en los enfoques de aprendizaje profundo es efectiva para la ingeniería de proteínas.
  • Los sistemas de edición del genoma ofrecen herramientas poderosas para la investigación genética.
  • Este trabajo avanza las capacidades de la ingeniería de proteínas para aplicaciones biotecnológicas.