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

Molecular Models02:00

Molecular Models

43.6K
Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
43.6K
The Bohr Model02:18

The Bohr Model

80.5K
Following the work of Ernest Rutherford and his colleagues in the early twentieth century, the picture of atoms consisting of tiny dense nuclei surrounded by lighter and even tinier electrons continually moving about the nucleus was well established. This picture was called the planetary model since it pictured the atom as a miniature “solar system” with the electrons orbiting the nucleus like planets orbiting the sun. The simplest atom is hydrogen, consisting of a single proton as the...
80.5K
Stereotype Content Model02:16

Stereotype Content Model

15.4K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
15.4K
Clearance Models: Physiological Models01:09

Clearance Models: Physiological Models

298
Drug clearance is a critical pharmacokinetic process involving the irreversible removal of drugs from the body through various organs over a specified time period. Physiological models are indispensable in determining organ-specific clearance, defined by the proportion of the drug eliminated per unit of time from the organ's blood volume.
The organ's clearance rate depends on the blood flow to the organ and the extraction ratio (E). The extraction ratio describes the organ's...
298
Clearance Models: Compartment Models01:25

Clearance Models: Compartment Models

304
Clearance measures drug elimination from the central compartment, including plasma and highly perfused organs like kidneys and liver. Its calculation varies depending on pharmacokinetic models and administration routes. The one-compartment model, for instance, portrays the pharmacokinetics of polar drugs such as aminoglycoside antibiotics administered intravenously and readily excreted in urine. In this case, clearance is influenced by the terminal rate constant (λz) and the total volume...
304
Compartment Models: Two-Compartment Model01:20

Compartment Models: Two-Compartment Model

7.0K
The two-compartment model divides the body into central and peripheral compartments to account for varying blood perfusion rates among organs and tissues, affecting drug distribution. The central compartment includes blood and highly perfused tissues with rapid drug distribution, while the peripheral compartment contains tissues with slower drug distribution. After a single IV bolus dose, the drug concentration is high in plasma and low in tissues. The drug distribution between compartments...
7.0K

You might also read

Related Articles

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

Sort by
Same author

CASP11 refinement experiments with ROSETTA.

Proteins·2015
Same author

Structure of a designed tetrahedral protein assembly variant engineered to have improved soluble expression.

Protein science : a publication of the Protein Society·2015
Same author

Unique double-ring structure of the peroxisomal Pex1/Pex6 ATPase complex revealed by cryo-electron microscopy.

Proceedings of the National Academy of Sciences of the United States of America·2015
Same author

Mechanistic Analysis of an Engineered Enzyme that Catalyzes the Formose Reaction.

Chembiochem : a European journal of chemical biology·2015
Same author

Design of ordered two-dimensional arrays mediated by noncovalent protein-protein interfaces.

Science (New York, N.Y.)·2015
Same author

Designing Two-Dimensional Protein Arrays through Fusion of Multimers and Interface Mutations.

Nano letters·2015
Same journal

Lactate as a Chemical Modification on Proteins and Metabolites.

Annual review of biochemistry·2026
Same journal

Nucleocytoplasmic Transport.

Annual review of biochemistry·2026
Same journal

Packaging of Single-Stranded RNA in Viruses and Virus-Like Particles.

Annual review of biochemistry·2026
Same journal

Shaping of the Infant Gut Microbiome by Milk Oligosaccharides.

Annual review of biochemistry·2026
Same journal

Proteostasis Deregulation by Metabolism Drives the Hallmarks of Cancer.

Annual review of biochemistry·2026
Same journal

JoAnne Stubbe's Radical Path: A Story of Passion, Curiosity, and Persistence.

Annual review of biochemistry·2026
See all related articles

Related Experiment Video

Updated: Jan 26, 2026

Optimization of Crystal Growth for Neutron Macromolecular Crystallography
12:29

Optimization of Crystal Growth for Neutron Macromolecular Crystallography

Published on: March 13, 2021

5.9K

Macromolecular modeling with rosetta.

Rhiju Das1, David Baker

  • 1Department of Biochemistry, University of Washington, Seattle, WA 98195, USA. rhiju@u.washington.edu

Annual Review of Biochemistry
|April 16, 2008
PubMed
Summary
This summary is machine-generated.

Accurate macromolecular structure prediction and design are now possible due to advances in all-atom potential functions and conformational sampling. The Rosetta program

More Related Videos

In Vitro Model of Human Cutaneous Hypertrophic Scarring using Macromolecular Crowding
08:20

In Vitro Model of Human Cutaneous Hypertrophic Scarring using Macromolecular Crowding

Published on: May 1, 2020

7.1K
Improving 2D and 3D Skin In Vitro Models Using Macromolecular Crowding
09:14

Improving 2D and 3D Skin In Vitro Models Using Macromolecular Crowding

Published on: August 22, 2016

13.0K

Related Experiment Videos

Last Updated: Jan 26, 2026

Optimization of Crystal Growth for Neutron Macromolecular Crystallography
12:29

Optimization of Crystal Growth for Neutron Macromolecular Crystallography

Published on: March 13, 2021

5.9K
In Vitro Model of Human Cutaneous Hypertrophic Scarring using Macromolecular Crowding
08:20

In Vitro Model of Human Cutaneous Hypertrophic Scarring using Macromolecular Crowding

Published on: May 1, 2020

7.1K
Improving 2D and 3D Skin In Vitro Models Using Macromolecular Crowding
09:14

Improving 2D and 3D Skin In Vitro Models Using Macromolecular Crowding

Published on: August 22, 2016

13.0K

Area of Science:

  • Computational Biology
  • Structural Biology
  • Biophysics

Background:

  • Recent advances enable near-atomic accuracy in predicting and designing macromolecular structures.
  • Progress is driven by improved potential functions and conformational sampling strategies.

Purpose of the Study:

  • To present a unified framework for molecular modeling using the Rosetta program.
  • To investigate diverse problems including fibril prediction, RNA folding, and protein interface design.
  • To highlight areas for methodological improvement.

Main Methods:

  • Development of accurate and efficient all-atom potential functions.
  • Implementation of effective conformational sampling for rugged energy landscapes.
  • Utilization of a unified energetic and kinematic framework within the Rosetta program.

Main Results:

  • Demonstration of the Rosetta program's capability across various molecular modeling tasks.
  • Successful application to fibril structure prediction, RNA folding, and protein interface design.
  • Identification of key areas for future methodological enhancements.

Conclusions:

  • The Rosetta framework facilitates investigation of complex molecular modeling problems.
  • The methodology supports the creation of novel molecules with desired functions.
  • This approach shows promise for accelerating experimental structural inference and integrating with other methods.