Protein ligand Docking with explanations of Bioinformatics Tools

1. Protein – Ligand Docking
Submitted by:-
Usha
M.Sc.
Bioinformatics

2. Docking
It predicts the best bounding orientation of
one molecule to other to form a stable
complex.

3. Protein ligand docking
• Given a protein structure & predict its ligand binding site.
• Finds the best conformation with minimum energy and maximum
stability.

4. Components of docking software
• Search algorithm
Generates a large number of poses of molecule in binding site.
• Scoring function
Calculate a score or binding affinity for particular pose.

5. Algorithm
• AutoDock
• GOLD

6. AutoDock
• Search methods
Genetic algorithm
 Stimulated annealing
Global – local search method based by Lamarckian genetic algorithm
• Finds the binding free energy for predicting the conformation

7. Genetic algorithm
• Finds the best binding pose
• Ligands are the state variables that correspond to a gene
• An initial population is generated randomly

8. Genetic algorithm
• Crossovers occurs in the individual
• Offspring are mutated randomly
• Selection of the fittest to next generation
• Repeat the generation until some improvement is observed

9. N = (F – E)/ (F - <F>), when F ≠ <F>
Where :
N - number of offspring to be allocated to individual
<F> - mean fitness of individual
F – fitness of worst individual or highest energy in n
generations
E - fitness of individual (energy of protein & ligand)
• F > E or <F>
• If E = F than E < <F>
• If (F – E) > (F - <F>) ; these individual will allocate at least one
offspring.

10. Stimulated annealing
• Start with random or specific pose
• Make random state changes, accepting uphill move with probability
dictated by temperature.
• Reduce temperature after each move
• Stop after temperature gets very small

11. Lamarckian genetic algorithm
Hybrid of genetic algorithm & adaptive local
search is LGA

12. Energy evaluation
ΔG= ΔGvdw + ΔGhbond +ΔGelect + ΔGconfor
+ΔGtor +ΔGsol
ΔGelect – electrostatic forces
ΔGconfor – deviation from covalent bond
ΔGsol – solvation & binding effect
ΔGvdw – vanderwal forces (dispersive/repulsive forces)
ΔGhbond – hydrogen bonding
ΔGtor – torsion angles

13. Observed vs predicted binding free energies

14. GOLD
• Scoring function
Goldscore
Chemscore
• Local scoring
Standard scoring
Local optimization
• Mechanism for protein ligand binding
• Search algorithm
It occur by genetic algorithm

15. Scoring function
• Goldscore
Gold fitness = Shbond-ext + Svdw-ext +Shbond-int +Svdw-int
Shbond – hydrogen bond score due intramolecular force & protein ligand
binding score
Svdw – vanderwal forces score due to intramolecular force and protein
ligand binding score

16. Scoring function
• Chemscore
ΔG = ΔG0 + ΔGhbondShbond + ΔGmetalSmetal + ΔGlipoSlipo +
ΔGrotSrot
ΔGhbondShbond – free energy for binding & score for hydrogen bond
ΔGmetalSmetal - free energy for binding & score for metal interaction
ΔGlipoSlipo - free energy for binding & score for
lipid interaction
ΔGrotHrot - - free energy for binding & score for
rotational movement

17. Tools for protein ligand docking
• HADDOCK
• Cluspro
• PatchDock
• PyDock
• SwissDock