Molecular docking is a method to predict how two molecules, such as a ligand and a protein, will interact and bind to one another. The key steps in molecular docking include preparing the protein and ligand, analyzing the binding site, docking the ligand to the protein, scoring the docked poses, and validating the docking results. Molecular docking can be used for applications like hit identification in drug discovery and lead optimization.

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MOLECULAR DOCKING
P R E S E N T E D B Y
E . P O O VA R A S A N
M . P H A R M F I R S T Y E A R
P S G C O L L E G E O F P H A R M A C Y

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MOLECULAR DOCKING
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Docking is a method which predicts the preferred orientation of one
molecule to a second,
When a ligand and a target are bound to each other to form a stable
complex.
Preferred orientation used to predict the strength of association or
binding affinity between two molecules using scoring functions

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Overview Of Molecular Docking:
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Steps involved in Molecular Docking:
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Protein Preparation
Binding site analysis
Ligand Preparation
Docking
 Docking analysis and Scoring functions
Validation of docking protocol

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Protein Preparation
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3D structure of a protein is downloaded from the data bank (
www.rcsb.org)
Protein data Bank ( PDB) maintained by research collaboratory for
Structural Bioinformatics (RCSB)
It contains various X-ray crystal structures for Proteins and other
biomolecules.

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Cleaning of Protein:
Once, the protein is downloaded, it is to be corrected for missing
residues, missing atoms, alternate locations, added water molecules
and incorrect bonding types and charges are to be balanced.
When , protein has been cleaned , it is then further refined by
molecular mechanics calculations to be finally prepared for use in
docking purposes.

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Binding Site Analysis:
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• Binding site is the part of the protein where the ligand binds
• It is generally a cavity on the protein surface. It can be identified by
looking at the crystal structure of the protein bound with a known
inhibitor.
• The binding site can be predicted by
Static approach
Dyanamic approaches
Mixed approaches

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Ligand Preparations:
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The type of ligands chosen for docking will depends on goal.
For docking the ligand to be prepared in a particular format even after
energy minimization and conformational anlalysis, for correct visualization
of hydrogen bonds and other interactions.
It can be obtained from various data bases ( e.g Zinc or and Pubchem) or
it can Sketched by means of Chemsketch tool or prepared in PRODRG
server.
It is necessary to apply filters to reduce the number of molecules to be
docked.
Examples: net charge, molecular weight, polar surface area, solubility,
commercial availability, similarity thresholds, pharmacophores, synthetic
accessibility, and ADMET properities.

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Docking :
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• Select a receptor and a ligand from your library
• Modify advanced parameters during simulation, such as number of
runs, number of evaluations, etc,.
• Where ligand is docked onto the receptor and the interactions are
checked.
• The scoring function generates a score depending on the best
selected ligands.

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Docking analyses and Scoring :
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• Docking is carried out by searching for the correct binding mode of
a molecule with a number of trials and keepings the energetically
favourable poses.
• After a certain number of trials have been carried out and a
sufficient number of poses have for a molecule – the search Stops
• The decision to keep a trial pose is based on the computed ligand
receptor interaction energy ( score) of that pose.

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Scoring Function
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• The nature of interactions ( van der waals , hydrogen bonding,
electrostatic, etc,.) between the ligands and their protein or nucleic
acid targets, termed as “ scoring function”.
• Scoring refers to evaluation and ranking of all configurations which
are generated during a search process.
• The actual free energy is preferred one.
• The free energy of binding of complex should be less than the sum
of their individual free energy

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Knowledge of interaction energies and forces flows into an assigned
score.
Scoring functions have a two – fold task
They serve as an objective function to differentiate between diverse
poses of a single ligand in the receptor- binding site
After docking a compound database, they are required to estimate
binding affinities of different receptor- ligand and to rank – order the
compounds.
Hydrophobic effects, van der waal’s and dispersion interactions ,
hydrogen bonding, steric, electrostatic interactions and solvation
effects are among the factors that contribute to ligand binding,
which in turn are governed by kinetic and thermodynamic principles.

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Types of scoring Function:
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1.Empirical Based:
• Empirical scoring functions sum enthalpic and entropic interactions with
the relative weights of the terms based on a training set of protein –
ligand complexes.
• The weights are assigned by regression methods that are used to fit the
experimentally determined affinities.
• The interactions terms often include van der waals, electrostatic
interactions and hydrogen bonds
• ▲Gbind = ▲Gsolvent + ▲Gconf + ▲Gint + ▲Grot + ▲Gtran+ ▲Gvib
• Example: PLP , ChemScore , FlexX

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2.Force-field based:
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• They predict the binding free energy of protein-ligand complex by
adding up individual contributions from different type of interactions.
• The interaction terms are derived from physical-chemical
phenomena as opposed to experimental affinities.
• E = E stretching + E bending + E torision + E van der waals + E electrostatic + E
hydrogen bonding + cross terms
• Examples :
• Energy score in DOCK, score function used for single ligand docking in
DOCKVISION and that used in GOLD

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3.KNOWLEDGE BASED:
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• It relays on statistical means to extract rules on preferred, and non-
preferred, atom pair interactions from experimentally determined
protein-ligand complexes.
• The rules are interpreted as pair – potentials that are subsequently
used to score ligand binding poses.
• Examples: PMF score

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4. CONSENSUS SCORING:
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• This applies a number of score functions to the same docked
pose identified by docking to eliminate false positives.
• Protein- ligand docking is so difficult due to tremendous complexity
of the system; one must take into account hundreds of thousands of
degrees of freedom in the two molecules, as well as the not-
completely – known combination of energetic forces acting on them.

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FACTORS AFFECTING THE DOCKING SCORE:
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Orientation of residues
Protonation states ( ligand and protein)
Tautomeric forms
Protein flexibility
Involvement energy of ligand
De-solvation penalties
Crystal packing of initial X-ray structure.

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Validation of the docking Protocol:
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• Validation requires that the co-crystallized ligand should be
extracted from protein, corrected and redocked to the same protein.
• The redocked conformer is then compared with the original one by
superimposition or by visualization as well as the RMSD ( Root
mean square deviation) is calculated.
• RMSD provides deviation between conformer and the original
conformer and original co-crystallized ligand with protein.
• RMSD is acceptable upto 3A0 , it always better less than 1A0.

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SOFTWARES FOR DOCKING:
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FREEWARES INCLUDE:
• DOCK 6.1 – http://dock.compbio.ucsf.edu/
• AUTODOCK – http://autodock.scripps.edu/
• HEX - http://www.csd.abdn.ac.uk/hex/ ( protein-protein docking)
• SLIDE – http://www.bch.msu.edu/~Kuhn/projects/slide/home.html
COMMERCIAL:
• GOLD- Cambridge Crystallographic data centre
• FLEXX – Tripos, Inc
• GLIDE – schrodinger, Inc
• ICM- molsoft, Inc
• LIGANDFIT – Accelrys, Inc
• OPEN EYE

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DOCKING TYPES:
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Manual Docking
Automatic Docking
Rigid ligand and rigid receptor docking( Rigid docking)
Flexible ligand and rigid protein( Flexible Ligand docking)
Rigid ligand and Flexible protein ( flexible protein docking)
Flexible protein and Flexible Ligand ( Flexible Docking)
Most commonly used docking algorithms use the rigid receptor/ flexible
ligand model

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MANUAL DOCKING:
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• Molecules may be docked manually with the aid of computer
graphics or automatically by using computer algorithms.
• Manual docking is done using molecular visualization software,
• Here bindings groups on the ligand and the active site are known, in
which the binding group in ligand is paired with its complimentary
group in binding stie.
• The user manually moves, rotates, translates the compound inside
the protein cavity. A new association energy is recorded… etc.

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Advantages:
• Quick
• Can be very efficient if the user knows well the interacting site
Disadvantages:
• Users dependant
• You can really obtain stupid results.

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Automatic Docking:
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• It is an unbiased type of docking in which the user does not specify
the active site, neither has to direct a ligand to an active and can
place a ligand randomly.
• The system automatically finds an optimal position in which ligand
and receptor bind , auto dock is used .
• Depending upon the flexibility, a docking algorithm may be,
• Ligand and protein rigid
• Flexible ligand and rigid protein
• Rigid ligand and flexible protein
• Both ligand and protein flexible.

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Based on the search algorithms, the principal methods are
• Molecular dynamics
• Monte Carlo methods
• Genetic algorithms
• Fragment based methods
• Point complementary methods
• Distance geometry methods
• Tabu searches
• Systematic searches

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RIGID DOCKING:
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• Here the molecules are rigid, in 3D space of one of the molecule
which brings it to an optimal fit with the other molecules in terms of a
scoring function.
Rigid Ligand and Rigid Receptor Docking:
• when the ligand and receptor are both treated as rigid bodies,
the search space is very limited considering only 3 translational
and 3 rotational degrees of freedom .
• In this case, ligand flexibility could be addressed by using a
precomputed a set ligand conformations or by allowing for a degree
of atom-atom overlap between the protein and ligand.

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DOCK:
• It is the first automated procedure for docking a molecule into a
receptor site and is being continuously developed
• FLOG- It generates ligand conformations on the basis of distance
geometry and uses a clique – finding algorithm to calculate the sets
of distances.
• This approach is useful if an important interaction is already known
before docking.

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Flexible ligand and rigid receptor docking( semiflexible
induced fit)
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• For systems whose behaviour follows the induced fit paradigm, it is
of vital importance to consider the flexibilities of both the ligand and
receptor since in that case both the ligand and receptor change their
conformations to form a minimum energy perfect fit complex.
• But, the cost is very high when the receptor is also flexible.
• Thus the common approach is treating the ligand as flexible while
the receptor is kept is rigid docking
• Example; AutoDock, Flex

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Flexible docking:
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• In flexible docking molecules are flexible, confirmations of the
receptor and the ligand molecules, as they appear in complex.
• Protein – ligand docking
• Flexible ligand, rigid receptor
• Search space much larger
• Either reduce flexible ligand
• An enumeration on the rotations of one of the molecules ( usually
smaller one ) is performed.
• Every rotation the energy is calculated , the most optimum pose is
selected

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APPLICATIONS OF MOLECULAR DOCKING:
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Hit identification :
• Docking combined with a scoring function can be used to quickly
screen large databases of potential drugs in silico to identify
molecules that are likely to bind to protein target of interest
• In reverse pharmacology docking used target identification.
Lead optimization:
• Docking can be used to predict in where and in which relative
orientation a ligand binds to a protein

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DRUG-DNA INTERACTIONS:
• This information establishes the correlation between drug’s
molecular structure and its cytotoxicity
• So it is aid in the development of anticancer drugs.
Knowledge of molecular associations aids in understanding a
variety of pathways taking place in the living and in revealing of the
possible pharmacological targets
Identification of haloperidol as lead compound in a structure based
design for non-peptide inhibitor of HIV
Dihydrofolate reductase ( anitbacterial0
Carbonic anhydrase inhibitor( treatment of glaucoma)
Renin ( treatment of hypertension)

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REFERENCES:
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Molecular modelling and Drug Design by K Anand Solomon
Drug Design by Balkishen Razdan
www. Google.com

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