The document discusses molecular docking, focusing on the prediction of protein-ligand interactions and the stability of complex formations. It compares different docking methodologies, including flexible and rigid docking, and outlines various scoring functions and docking tools used in the process. Additionally, it highlights applications like virtual screening, hit identification, and lead optimization in drug discovery.

1. MOLECULAR
DOCKING
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Submitted By:
Aashu Vijay
M.Pharm PC 2nd Sem
INDINAVIR

2. INTRODUCTION
Formation of a stable complex due to the prediction of orientation or posing of one
molecule to another (with minimal energy) so that they will bind together to give desired
effect i.e. prediction of protein-ligand activities. Or prediction of ligand conformation and
Posing within target binding site.
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SAQUINAVIR

3. PROTEIN-PROTEIN DOCKING PROTEIN-SMALL MOLECULE DOCKING
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4. TYPES OF DOCKING
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5. FLEXIBLE DOCKING
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6. A) View of P-gp from above (i.e. viewed from the luminal face, perpendicular to the membrane plane) of the top-scored
saquinavir pose (yellow) from the primary round of the flexible receptor docking. Phe71, Phe332, and Phe728 were mutated
to Ala in the 1st Glide docking stage. The final positions of the three residues and Phe974 are shown in pink, while those of
the original crystal structure are in green. B) Top-scored poses from second round of flexible receptor docking (red), Glide
XP = −17.8 kcal/mol compared to top the pose from rigid docking (blue), Glide XP = −10.0 kcal/mol for saquinavir.
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FLEXIBLE Vs RIGID DOCKING

7. INDUCED-FIT DOCKING
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8. MECHANISM
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9. MECHANICS OF DOCKING
To derive 3D structure
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10. SCORING FUNCTION- Aim to describe and quantify the association.
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Force-Field-Based Empirical Knowledge-Based
DOCK AutoDock SMoG
AutoDock GlideScore DrugScore
GoldScore ChemScore PMF_Score
LigandFit X_Score MotifScore
ICM F_Score RF_Score
SYBYL_G-Score LUDI PESD_SVM
Molegro Virtual Docker LigScore PoseScore
SYBYL_D-Score SFCscore
MedusaScore PLP

11. Example of pose docking selection using crossing information between ligand volume overlap and fingerprint
interaction between the ligand in the cocrystallized suvorexant, represented in surface and poses of suvorexant
redocked using Glide. (A) Graphic representation of crossing information between Jaccard similarity scores of
interaction fingerprint and ShaEP scores, normalized on the distribution, between each pose and the reference co-
crystalized ligand. The rank of poses based on GlideScore is also indicated. (B) Representation of the poses ranked
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12. DOCKING ALGORITHMS
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13. EXAMPLE
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Sno
.
Name of the
docking tool
Licence Pose Generation method Scoring function
1. Auto Dock Free Lamarckian Genetic algorithm
(LGA)
Empirical+Knowledge based
2. Swiss Dock Free Evolutionary optimization
(genetic algorithm+evolution
strategy)
Molecular mechanics Force
Field
3. GOLD Commercial Genetic algorithm Chemscore (emperical)
4. DOCK Free Shape matching (Geometric
algorithm)
Force fields
5. FlexX Commercial Shape matching (geometric
algorithm)
FlexX SF (empirical)
6. ICM Commercial Monte carlo (Energy based) PMF (Potential mean force)
(empirical)

14. APPLICATIONS
1. Direct conception- exploring a protein cavity with several moieties.
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15. AMITY INSTITUTE OF PHARMACY
VIRTUAL
SCREENING
Ranking
Ligand
database
Molecular
Docking
2. Virtual Screening
3. Hit Identification
4. Lead Optimization

16. THANK YOU !!
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