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Related Concept Videos

Molecular Models02:00

Molecular Models

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.
Drug Products: Biologics, Biosimilars and Interchangeables01:28

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Biologics, derived from living sources such as humans, animals, or microorganisms, represent a significant category of pharmaceuticals. These complex molecules, developed through advanced biotechnological methods or purified from natural sources, include essential medical treatments like insulin and growth hormones. The complexity of biologics arises from their large molecular structures and the intricate processes required for their production, making them distinct from conventional...
Pharmacokinetic Models: Comparison and Selection Criterion01:26

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Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
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Ligand Binding Sites02:40

Ligand Binding Sites

Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
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Physiological Pharmacokinetic Models: Assumption with Protein Binding01:13

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Physiological models with protein binding in pharmacokinetics offer a sophisticated approach to understanding drug disposition. These models consider drug-protein interactions, enabling them to effectively predict drug concentrations in different organs and tissues. This precision aids in accurate drug dosing, providing a significant advantage over conventional models. A key process within these models is equilibration, which ensures that drug concentrations achieve a steady state within the...
The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

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Updated: Jul 10, 2026

Realistic Membrane Modeling Using Complex Lipid Mixtures in Simulation Studies
07:31

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Published on: September 1, 2023

Molecular Modeling and Simulations of Biologics.

Dariya Baizhigitova1, Pin-Kuang Lai2

  • 1Department of Chemical Engineering and Materials Science, Stevens Institute of Technology, Hoboken, NJ, USA.

Methods in Molecular Biology (Clifton, N.J.)
|July 9, 2026
PubMed
Summary

This study provides a practical protocol for molecular dynamics (MD) simulations of large biomolecules like antibodies. It equips researchers with computational tools and knowledge for studying dynamic biological systems.

Keywords:
AntibodiesBiologicsExcipientsMolecular dynamics simulations

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Analyzing Protein Architectures and Protein-Ligand Complexes by Integrative Structural Mass Spectrometry
07:33

Analyzing Protein Architectures and Protein-Ligand Complexes by Integrative Structural Mass Spectrometry

Published on: October 15, 2018

Area of Science:

  • Computational Biology
  • Structural Biology
  • Biophysics

Background:

  • Molecular dynamics (MD) simulations are crucial for studying biomolecular dynamics at atomic resolution.
  • MD simulations are applied in protein folding, conformational changes, ligand interactions, and structure determination.

Purpose of the Study:

  • To present an end-to-end protocol for performing MD simulations on large biomolecules.
  • To introduce essential software tools for molecular modeling and MD simulations.
  • To demonstrate modeling antibody-excipient interactions and identifying binding sites.

Main Methods:

  • Utilizing a full-length antibody as a case study for MD simulations.
  • Employing foundational software such as PyMOL, VMD, NAMD, and MDAnalysis.
  • Applying protocols for modeling biomolecular interactions and analyzing simulation trajectories.

Main Results:

  • A practical and reproducible framework for conducting MD simulations on large biomolecules.
  • Demonstration of antibody-excipient interaction modeling.
  • Identification of binding sites from MD trajectories.

Conclusions:

  • The presented framework equips researchers with tools and knowledge for complex biomolecular system studies.
  • MD simulations are an indispensable tool for understanding dynamic biological processes.
  • Integration of MD simulations enhances biological research capabilities.