Jove
Visualize
Contáctanos

Videos de Conceptos Relacionados

Drug Discovery: Overview01:26

Drug Discovery: Overview

8.1K
Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
8.1K
Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

817
Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence...
817
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches01:14

Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches

192
Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
192
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis00:59

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

104
Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
104

También podría leer

Artículos Relacionados

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

Ordenar por
Same author

PLATE-VS: a web server for protein-ligand assay curation and cross-target virtual screening datasets.

Nucleic acids research·2026
Same author

Molecular mechanisms for subtype selectivity of kinin receptors' antagonists.

Nature communications·2026
Same author

Phosphorylation site topology governs the functional dynamics of arrestin recruitment to GPCRs.

Research square·2026
Same author

Differential Effects of Sodium on Agonist-Induced Conformational Transitions and Signaling at μ and κ Opioid Receptors.

Biochemistry·2025
Same author

Structural insights into the mechanism of activation and inhibition of the prostaglandin D2 receptor 1.

Nature communications·2025
Same author

Exceptionally Potent Chiral Anandamide Analogs.

Journal of medicinal chemistry·2025
Same journal

Incoming US science academy chief vows to 'double down' on research.

Nature·2026
Same journal

Author Correction: Synthesis of enantioenriched atropisomers by biocatalytic deracemization.

Nature·2026
Same journal

Electrodeposited self-assembled molecules for perovskite photovoltaics.

Nature·2026
Same journal

Neutrino's nursery found: the 'Shadow Blaster'.

Nature·2026
Same journal

Dementia risk in middle-aged people linked to a blood protein.

Nature·2026
Same journal

Daily briefing: What's really happening with trust in science.

Nature·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: Aug 1, 2025

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
08:49

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

421

Enfoques computacionales para agilizar el descubrimiento de fármacos

Anastasiia V Sadybekov1,2, Vsevolod Katritch3,4,5

  • 1Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.

Nature
|April 26, 2023
PubMed
Resumen
Este resumen es generado por máquina.

Las tecnologías computacionales están revolucionando el descubrimiento de fármacos. Los avances en el aprendizaje profundo y la detección virtual aceleran la identificación de fármacos potenciales candidatos, lo que hace que el desarrollo del tratamiento sea más accesible y rentable.

Más Videos Relacionados

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
05:10

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

9.7K
Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery
06:26

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Published on: May 16, 2021

4.9K

Videos de Experimentos Relacionados

Last Updated: Aug 1, 2025

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
08:49

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

421
Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
05:10

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

9.7K
Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery
06:26

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Published on: May 16, 2021

4.9K

Área de la Ciencia:

  • Química computacional
  • Farmacología
  • La bioinformática

Sus antecedentes:

  • El descubrimiento de fármacos asistido por computadora (CADD) ha evolucionado significativamente, impulsado por el aumento de la disponibilidad de datos y el poder computacional.
  • La integración de tecnologías computacionales está transformando la investigación académica y farmacéutica.
  • Los datos abundantes sobre las propiedades de los ligandos, las estructuras objetivo y las vastas bibliotecas virtuales son habilitadores clave.

Objetivo del estudio:

  • Revisar los avances recientes en las tecnologías de descubrimiento de ligandos.
  • Explorar el potencial de estas tecnologías para remodelar el descubrimiento y desarrollo de fármacos.
  • Para discutir los desafíos y oportunidades en el descubrimiento de fármacos computacionales.

Principales métodos:

  • Estructura basada en el cribado virtual de grandes espacios químicos.
  • Enfoques de cribado iterativos rápidos.
  • Aprendizaje profundo para predecir las propiedades de los ligandos y las actividades objetivo sin estructuras de receptores.

Principales resultados:

  • Identificación rápida de ligandos parecidos a fármacos diversos, potentes y selectivos para el objetivo.
  • Los avances sinérgicos en el aprendizaje profundo complementan los métodos basados en la estructura.
  • Facilitación de la exploración química del espacio a escala gigante.

Conclusiones:

  • Los métodos computacionales están democratizando el descubrimiento de medicamentos.
  • Existen nuevas oportunidades para el desarrollo rentable de fármacos de pequeñas moléculas más seguros y eficaces.
  • La revisión pone de relieve el impacto transformador de los enfoques computacionales modernos en la I+D farmacéutica.