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

Molecular Docking & Pharmacophore Modelling

Molecular Docking & Pharmacophore Modelling

Molecular Docking & Pharmacophore Modelling

Pharmacophore modeling

       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

Pharmacophore modeling

       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

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

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

Molecular docking

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.


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

Theory of Docking

Molecular Docking

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

Molecular Docking

NEP: Nevirapine

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

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.

Flixible Docking (Induced fit)

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.


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


GOLD – University of Cambridge, UK (

AUTODOCK – Scripps Research Institute, USA (

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 (

Hex Protein Docking – University of Aberdeen, UK (

GRAMM (Global Range Molecular Matching) Protein Docking – A Center for Bioinformatics, University of Kansas, USA (


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.


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

FAQs: Unraveling Common Misconceptions

Q: How does Molecular Docking differ from other drug design techniques? A: Molecular Docking stands out by predicting the optimal orientation of molecules, enabling precise insights into their interactions. Unlike other techniques, it offers a structural perspective, crucial for designing effective pharmaceuticals.

Q: Can Pharmacophore Modelling be applied to all drug targets? A: While versatile, Pharmacophore Modelling is tailored to specific targets. Its effectiveness depends on understanding the target’s essential features, making it highly adaptable but not universally applicable to all drug targets.

Q: What challenges do researchers face in implementing Molecular Docking in drug discovery? A: Challenges include accounting for the dynamic nature of molecules and ensuring accurate predictions. Researchers navigate complexities such as receptor flexibility and solvent effects to enhance the reliability of Molecular Docking outcomes.

Q: Are there limitations to the accuracy of Pharmacophore Modelling? A: Yes, limitations exist, mainly in accurately predicting subtle variations in molecular structures. Overcoming these limitations requires a nuanced understanding of the target’s intricacies, emphasizing the need for continuous refinement.

Q: How do Molecular Docking and Pharmacophore Modelling complement each other in drug design? A: Molecular Docking predicts interactions, while Pharmacophore Modelling identifies essential features. Together, they form a synergistic approach, providing a holistic understanding of molecular interactions crucial for designing effective drugs.

Q: Can these techniques be applied to personalized medicine? A: Absolutely. Molecular Docking & Pharmacophore Modelling adapt well to personalized medicine, allowing tailoring of drug design to individual genetic profiles. This personalized approach holds great promise for more effective and targeted treatments.

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