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Predicting Molecular Geometry

Predicting Molecular Geometry

VSEPR Theory for Determination of Electron Pair Geometries

Ligand Binding Sites

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.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...

Conserved Binding Sites

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...

The Equilibrium Binding Constant and Binding Strength

The Equilibrium Binding Constant and Binding Strength

The equilibrium binding constant (Kb) quantifies the strength of a protein-ligand interaction. Kb can be calculated as follows when the reaction is at equilibrium:

Molecular Geometry and Dipole Moments

Molecular Geometry and Dipole Moments

The VSEPR theory can be used to determine the electron pair geometries and molecular structures as follows:

Molecular Models

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.

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

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

Published on: June 20, 2025

Molecular dynamics analysis to evaluate docking pose prediction.

Takako Sakano¹, Md Iqbal Mahamood¹, Takefumi Yamashita¹

¹Laboratory for Systems Biology and Medicine, Research Center for Advanced Science and Technology, the University of Tokyo, Tokyo 153-8904, Japan.

Biophysics and Physicobiology

|December 8, 2016

Summary

Molecular dynamics (MD) simulations can assess the accuracy of ligand-protein docking poses. MD analysis confirmed that docking predictions are more reliable for rigid proteins and similar ligands.

Keywords:

G-protein coupled receptor drug design histone methyltransferase ligand–protein complex molecular dynamics simulation

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Area of Science:

Computational chemistry
Structural biology
Drug discovery

Background:

Accurate prediction of ligand-protein complex structures is crucial for computer-assisted drug development.
Existing docking methods have limitations in predicting binding poses accurately.

Purpose of the Study:

To evaluate the utility of molecular dynamics (MD) simulations in assessing docking poses.
To investigate the influence of protein flexibility and ligand similarity on docking accuracy.

Main Methods:

Utilized molecular dynamics (MD) simulations to analyze ligand-protein complexes.
Investigated two therapeutic targets: β2 adrenergic receptor (β2AR) and PR-Set7.
Assessed docking pose stability in aqueous environments.

Main Results:

MD simulations indicated that docking predictions are more accurate for rigid proteins (like β2AR) with ligands similar to a template.
For flexible proteins (like PR-Set7) with diverse ligands, docking accuracy was less reliable.
MD simulations showed that unstable docking poses are often resolved by ligand displacement.

Conclusions:

MD simulations are a valuable tool for validating docking poses in drug discovery.
Protein flexibility and ligand structural similarity significantly impact the reliability of docking predictions.
MD simulations offer potential for predicting ligand binding poses.