CHARMM-GUI Multicomponent Assembler for Modeling and Simulation of Complex Multicomponent Systems
Nathan R Kern1, Jumin Lee2, Yeol Kyo Choi2
1Department of Computer Science & Engineering, Lehigh University, Bethlehem, PA, USA.
Biorxiv : the Preprint Server for Biology
|September 11, 2023
Summary
CHARMM-GUI
Area of Science:
- Computational biology
- Biophysics
- Materials science
Background:
- Atomic-scale molecular modeling is crucial for computational biology.
- Complex systems with large molecules, non-water solvents, and multiple biomaterials are challenging to model.
- Existing tools lack support for periodic boundary conditions (PBC) in complex assemblies.
Conclusions:
- Multicomponent Assembler simplifies the creation of complex molecular models.
- The tool supports diverse biomolecular and materials science applications.
- It serves as a cyberinfrastructure for studying intricate molecular interactions.
More Related Videos
09:17Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
Published on: March 1, 2022
3.2K
15:05Deciphering the Structural Effects of Activating EGFR Somatic Mutations with Molecular Dynamics Simulation
Published on: May 20, 2020
8.7K
Related Concept Videos
Assembly of Signaling Complexes
5.8K
Multiprotein signaling complexes are formed in a dynamic process involving protein-protein interactions at the cytoplasmic domain of transmembrane receptors or enzymatic and non-enzymatic proteins associated with the receptor. These complexes ensure the activation and propagation of intracellular signals that regulate cell functions.
Interaction domains in cell signaling
Interaction domains recognize exposed features of their binding partners containing post-translationally modified sequences,...
Interaction domains in cell signaling
Interaction domains recognize exposed features of their binding partners containing post-translationally modified sequences,...
5.8K
Molecular Models
38.6K
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.
38.6K
Assembly of Complex Microtubule Structures
1.9K
Complex microtubule structures are present in resting cells and in dividing cells. In resting cells, they are responsible for maintaining the cellular architecture, tracks for intracellular transport, positioning of organelles, assembly of cilia and flagella. They mediate the bipolar spindle assembly for chromosomal segregation and positioning of the cell division plate in dividing cells. The formation of microtubule complex structures depends on the cell type, cell stage, and cell function.
1.9K
Protein Complexes with Interchangeable Parts
1.9K
1.9K
Mechanistic Models: Overview of Compartment Models
111
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...
111
Multicompartment Models: Overview
178
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,...
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
178
