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
• 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
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.
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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