Molecular Docking & Pharmacophore Modelling – Medicinal Chemistry III B. Pharma 6th Semester

Molecular Docking & Pharmacophore Modelling

Pharmacophore modelling

       Common
features in a molecule:

       Hydrogen
bond donors

       Hydrogen
bond acceptors

       Aromatic
rings

       Acidic
groups

       Basic
groups

       Positively
charged centers

       Negatively
charged centers

       Hydrophobic
centers

       First
definition of pharmacophore by Paul Ehrlich- a molecular framework that carrier
the essential features responsible for drugs biological activity

       Modified
by Peter Gund- a set of structural features in a molecule that is recognized at
a receptor site and is responsible for that molecules biological activity

       Phe82
and Leu83 through two hydrogen bonds

       Hydrophobic
region through cyclopentyl group

       Asp145
and Asn132 through hydrogen bonds

       In
addition to distances that describe the 3D relationship among pharmacophore
points, angles, dihedrals, and exclusion volumes are also used

3D Pharmacophore Modelling

Interactions between human cyclin-dependent kinase 2
and the adenine-derived inhibitor H717 as observed in the X-ray structure of
the complex (PDB entry 1G5S).

       Structure
based pharmacophore modelling

       Crystal
structure of a target protein with its ligand bound to binding site can be used
to identify the 3D pharmacophore

       Protein-ligand
structure can be loaded into the computer and complex is studied to identify
the bonding interactions which hold the ligand in binding site

       Done
by measuring the distance between likely binding groups in drug with
complementary binding groups i.e., amino acids in binding site

       Positions
can be mapped to generate the pharmacophore 

       Database
of compounds can be screened to identify the best matches

Ligand based Pharmacophore Modelling

4-hydroxyl piperidinol derivatives

       If
structure of target is unknown

       Can
be identified based on the structures of a range of active compounds

       Molecules
can be overlaid to ensure that important binding groups are matched up as
closely as possible

       All
the chemical structures and IC50 values will be loaded to program

       It
identifies the different important centers and their positions

       Program
generates different set of conformations

       Adding
all these together, gives a possible pharmacophore model  

       Database
of compounds can be screened to identify the best matches

Molecular docking

Docking addresses interaction of drug and receptors:
Formation of non-covalent ligand-receptor complexes

The docking problem predict the structure of the resulting
complex based on the given structure of receptor and ligand.

What is Protein – Ligand
Docking?

Computationally predict the structures of protein-ligand
complexes from their conformation and orientations.

The orientation that maximzed the interaction reveals the
most accurate structure of the complex.

Docking

Given two molecules
find their correct association:

Theory of Docking

Lock and key

Finding the correct
relative orientation of the key which will open up lock.

On the surface of
the lock is the key hole

In which direction
to turn the key after it is inserted

Molecular Docking

The protein can be
thought of as the lock and the ligand can be thought of as a key.

NEP: Nevirapine

Crystallographic
structure of HIV-1 reverse transcriptase: green colour P51 subunit & red
coloured P66 subunit

Type of Docking

Rigid Docking (Lock and Key)

In rigid docking, the internal geometry of both the receptor
and ligand are treated as rigid.

Flixible Docking (Induced fit)

An enumeration on the rotations of one of the molecules
(usually smaller one) is performed. Every rotation the energy is calculated;
later the most optimum pose is selected.

Receptor selection
and preparation

Building the receptor

The 3D structure of the receptor should be considered which
can be downloaded from PDB.

The available structure should be processed.

The receptor should be biologically active and stable.

Identification of the Active Site

The active site within the receptor should be identified.

The receptor may have many active sites but the one of the
interest should be selected.

Legend selection and preparation

Ligands can be obtained from various databases like ZINC,
PubChem or can be selected using tool like Chemsketch.

Docking

The ligand is docked onto the receptor and the interactions
are checked. The scoring function generates score, depending on which the best
fit ligand is selected.

Software’s available

SANJEEVINI – IIT
Delhi (
www.scfbio-iitd.res.in/sanjeevini/sanjeevini.jsp)

GOLD –
University of Cambridge, UK (
www.ccdc.com.ac.uk/GoldSuite/Pages/Gold.aspx)

AUTODOCK –
Scripps Research Institute, USA (
www.autodock.scripps.edu/)

GemDock (Generic Evolutionary Method of Molecular
Docking) –
A tool, developed by
Jinn-Moon Yong, a professor of the Institute of Bioinformatics, National Chiao
Tung University, Taiwan (
www.gemdock.life.nctu.edu.tw/dock/)

Hex Protein Docking – University of Aberdeen, UK (www.hex.loria.fr/)

GRAMM (Global Range Molecular Matching) Protein Docking – A Center for Bioinformatics, University of
Kansas, USA (
www.bioinformatics.ku.edu/files/vakser/gramm/)

Applications

Virtual Screening
(hit identification)

Docking with a
scoring function can be used to quickly screen large database of potential drug
in silico to identify molecule that are likely to bind to protein target of
interest.

Drug Discovery
(lead optimization)

Docking can be used
to predict in where and in which relative orientation a ligand binds to a
protein (binding mode or pose). This information may in turn be used to design
more potent and selective analogs.

Bioremediation

Protein ligand
docking can also be used to predict pollutants that can be degraded by enzymes.

 

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