Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...

Models, Theories, and Laws

Models, Theories, and Laws

Scientists frequently use models to help them comprehend a specific collection of phenomena. In physics, a model is a condensed version of a physical system that is too complex to study thoroughly. One such example is the light wave model; unlike water waves, light waves are typically invisible to us. Nonetheless, it is helpful to think of light as being composed of waves, since investigations show that light behaves like water waves. Since it is impossible to visually see what is genuinely...

Mechanistic Models: Overview of Compartment Models

Mechanistic Models: Overview of Compartment Models

Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...

Multicompartment Models: Overview

Multicompartment Models: Overview

Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...

Typical Model Studies

Typical Model Studies

Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.

Pharmacodynamic Models: Overview

Pharmacodynamic Models: Overview

Pharmacodynamic (PD) responses describe the interaction between a drug and its biological target, culminating in a physiological effect. These responses can be classified into different types: continuous variables, such as blood glucose levels; categorical outcomes, like survival rates; and time-to-event metrics, such as disease progression. Understanding and modeling PD responses are critical for optimizing drug efficacy and safety.PD models describe the relationship between drug concentration...

You might also read

Related Articles

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

Sort by

Same author

Using protein blocks to build custom fragment libraries from protein structures.

Biochimie·2025

Same author

Are Most Human-Specific Proteins Encoded by Long Noncoding RNAs?

Journal of molecular evolution·2024

Same author

On the Unknown Proteins of Eukaryotic Proteomes.

Journal of molecular evolution·2023

Same author

At least three xenon binding sites in the glycine binding domain of the N-methyl D-aspartate receptor.

Archives of biochemistry and biophysics·2022

Same author

Normal-mode driven exploration of protein domain motions.

Journal of computational chemistry·2021

Same author

Rational Enzyme Design without Structural Knowledge: A Sequence-Based Approach for Efficient Generation of Transglycosylases.

Chemistry (Weinheim an der Bergstrasse, Germany)·2021

Search research articles

Related Experiment Video

Updated: May 18, 2026

Finite Element Modelling of a Cellular Electric Microenvironment

Finite Element Modelling of a Cellular Electric Microenvironment

Published on: May 18, 2021

Elastic network models: theoretical and empirical foundations.

Yves-Henri Sanejouand¹

¹University of Nantes, Nantes, France. yves-henri.sanejouand@univ-nantes.fr

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

|October 5, 2012

Summary

Elastic Network Models simplify protein dynamics by replacing interactions with springs. This approach, while coarse-grained, offers valuable insights into biological macromolecule behavior and dynamics.

Area of Science:

Biophysics
Computational Biology
Protein Dynamics

Background:

Monique Tirion's foundational work demonstrated that low-frequency protein normal modes are robust to replacing nonbonded interactions with Hookean springs below a cutoff distance.
Coarse-grained Elastic Network Models (ENMs) derived from this principle have since proven effective in analyzing biological macromolecule dynamics.

Purpose of the Study:

To detail the theoretical underpinnings of Elastic Network Models for studying protein dynamics.
To address practical considerations and potential artifacts associated with ENM simulations.
To present a review of representative findings from ENM studies.

Main Methods:

Utilizing Hookean springs to approximate nonbonded interactions in protein structures.

Related Experiment Videos

Last Updated: May 18, 2026

Finite Element Modelling of a Cellular Electric Microenvironment

Finite Element Modelling of a Cellular Electric Microenvironment

Published on: May 18, 2021

Applying coarse-graining techniques to simplify complex biological macromolecules.

Analyzing low-frequency normal modes to infer dynamical properties.

Main Results:

Demonstration of the robustness of protein low-frequency normal modes under simplified interaction potentials.
Validation of coarse-grained ENMs for providing significant insights into macromolecule dynamics.
Identification and discussion of practical issues and artifacts in ENM analysis.

Conclusions:

Elastic Network Models offer a computationally tractable yet informative approach to understanding protein and macromolecule dynamics.
The theoretical framework and practical considerations of ENMs are crucial for reliable biological simulations.
ENMs continue to be a valuable tool for exploring the dynamical properties of biological systems.