SWISS PDB VIEWER Flashcards
(2 cards)
Swiss PDB Viewer (DeepView)
Type: Bioinformatics software for protein structure visualization. By Nicholas Guex
3D Visualization: Interactive display of protein structures in 3D.
Molecular Editing: Modify protein structures (e.g., change side chains).
Display Options: Various visualization modes (ribbon, cartoon, ball-and-stick).
Sequence Alignment: Tools for comparing protein sequences.
Energy Minimization: Optimize protein structures to reduce energy and improve geometry.
Compatibility: Supports multiple file formats (PDB, CIF).
Applications: Used in structural biology, molecular modeling, and drug design.
Energy Minimization
Definition: Technique to optimize molecular geometry by minimizing potential energy.
Importance: Reduces steric clashes, identifies stable conformations, and improves model accuracy.
Methods:
Steepest Descent: Iterative adjustment in the direction of energy decrease.
Conjugate Gradient: Considers previous steps for optimization.
Newton-Raphson: Uses second-order derivative information for faster convergence.
Process:
- Start with initial structure.
- Compute potential energy.
- Apply optimization algorithm.
- Stop when changes in energy/position are minimal.
Outcome: Refined protein structure ready for further analysis.
Swiss PDB Viewer (DeepView)
Type: Bioinformatics software for protein structure visualization.
3D Visualization: Interactive display of protein structures in 3D.
Molecular Editing: Modify protein structures (e.g., change side chains).
Display Options: Various visualization modes (ribbon, cartoon, ball-and-stick).
Sequence Alignment: Tools for comparing protein sequences.
Energy Minimization: Optimize protein structures to reduce energy and improve geometry.
Compatibility: Supports multiple file formats (PDB, CIF).
Applications: Used in structural biology, molecular modeling, and drug design.
Energy Minimization
Definition: Technique to optimize molecular geometry by minimizing potential energy.
Importance: Reduces steric clashes, identifies stable conformations, and improves model accuracy.
Methods:
Steepest Descent: Iterative adjustment in the direction of energy decrease.
Conjugate Gradient: Considers previous steps for optimization.
Newton-Raphson: Uses second-order derivative information for faster convergence.
Process:
- Start with initial structure.
- Compute potential energy.
- Apply optimization algorithm.
- Stop when changes in energy/position are minimal.
Outcome: Refined protein structure ready for further analysis.
