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PHARMACOPHORE
MAPPING AND
VIRTUAL SCREENING
Presented by-
Mr. Akshay Ramchandra Yadav
( First year M.pharm).
Pharmaceutical chemistry Dept.
Rajarambapu College of Pharmacy, Kasegaon.
Concept of pharmacophore
Pharmacophore mapping
Identification of pharmacophore features and
pharmacophore modeling
Conformation search used in pharmacophore
mapping
Virtual screening
 IUPAC defines a pharmacophore to be "an ensemble of
steric and electronic features that is necessary to ensure the
optimal supramolecular interactions with a specific biological
target and to trigger (or block) its biological response".
 With pharmacophoric models one can define special
properties (pharmacophoric points) based on the structure of
the receptor or based on the structure of a known agent.
 MolSign is a complete module for pharmacophore
identification and modeling. Identification of the
pharmacophoric features such as H-bond donor, H-bond
acceptor, positive charge, negative charge and hydrophobe
facilitate the complete pharmacophoric mapping of the
molecule.
EXAMPLE-
 An example of a pharmacophore model of the benzodiazepine binding site
on the GABAAreceptor.
 White sticks represent the carbon atoms of the benzodiazepine diazepam,
while green represents carbon atoms of the nonbenzodiazepine CGS-9896..
 Red and blue sticks are oxygen and nitrogen atoms that are present in both
structures.
The goal of Pharmacophore mapping is to establish the bioactive
conformations of the Ligand and how to superimpose the mapping,
one needs structure-activity relationships of structurally diverse and
conformation informative molecules.
Software use for Pharmacophore
mapping:
 Disco
 Hip-hop
 Aladdin
 Apex Gasp
 Accelary
 Apollo Rapid 21
 Application:
Application of Pharmacophore
mapping is used to understand the
biological activity observed in
series of compounds. So that we
can design new and more potent
compound.
TYPICAL FEATURES
 Hydrophobic
 Aromatic
 H-bond acceptor
 H-bond donor
 Cationic or
 Anionic moieties
A pharmacophore model consists of a few features
organized in a specific 3D pattern.
50 The features can be labeled as a single feature or any
logic combination consisting of “AND,” “OR,” and “NOT”
to combine different interaction patterns within one label.
Each of these conformations is fitted to the pharmacophore
query by aligning the pharmacophore features of the
molecule and the query is composed.
If a molecule can be fitted inside the spheres representing
the query features it is considered a hit molecule.
Depending on how much is known about the particular protein target,
different options are available to construct such a query.
Four different situations for the pharmacophore search.
 Limitations of pharmacophore methods
The major limitation in virtual screening by
pharmacophore is the absence of good scoring
metrics.
A second limitation is the dependency of a
pharmacophore-based virtual screen on a pre-
computed conformation database. These databases
only contain a limited number of low-energy
conformations per molecule.
Conformation generally means structural arrangement.
Conformations are different three dimensional structure of
molecules that arises from.
-rotations about single bonds (torsional angles).
-different rings conformations.
The biological activity of molecules is strongly dependent on their
conformations.
Done by exploring the energy surface of a molecule and
determining the conformation with minimal energy,
Conformational analysis is needed to identify the ideal conformation
of the molecule.
Different methods
the conformations search can be quite large and can be
approaches using following methods
1.Systemic search method
2.Distance geometry method
3.Clique detection alogorithm
Virtual screening (VS) is a computational technique
used in drug discovery to search libraries of small
molecules in order to identify those structures which
are most likely to bind to a drug target, typically a
protein receptor or enzyme.
Pharmacophore-based virtual screening is nowadays a
mature technology, very well accepted in the medicinal
chemistry laboratory.
like any empirical approach, it has specific limitations
and efforts to improve the methodology are still
ongoing.
 Methods
There are two broad categories of screening
techniques: ligand-based and structure-based.
 Ligand-based-
Given a set of structurally diverse ligands that binds to a
receptor, a model of the receptor can be built by exploiting
the collective information contained in such set of ligands.
These are known as pharmacophore models.
 Structure-based-
Structure-based virtual screening involves docking of
candidate ligands into a protein target followed by applying
a scoring function to estimate the likelihood that the ligand
will bind to the protein with high affinity.
References-
Rester U (July 2008). "From virtuality to reality - Virtual
screening in lead discovery and lead optimization: a medicinal
chemistry perspective". Current Opinion in Drug Discovery &
Development. 11 (4): 559–68. PMID 18600572.
 Rollinger JM, Stuppner H, Langer T (2008). Virtual screening
for the discovery of bioactive natural products. Progress in Drug
Research.
Fortschritte der Arzneimittelforschung. Progres des Recherches
Pharmaceutiques. Progress in Drug Research. 65. pp. 211, 213–
49.
Walters WP, Stahl MT, Murcko MA (1998). "Virtual screening –
an overview". Drug Discov. Today. 3 (4): 160–178.
Pharmacophore Mapping and Virtual Screening (Computer aided Drug design)

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Pharmacophore Mapping and Virtual Screening (Computer aided Drug design)

  • 1. PHARMACOPHORE MAPPING AND VIRTUAL SCREENING Presented by- Mr. Akshay Ramchandra Yadav ( First year M.pharm). Pharmaceutical chemistry Dept. Rajarambapu College of Pharmacy, Kasegaon.
  • 2. Concept of pharmacophore Pharmacophore mapping Identification of pharmacophore features and pharmacophore modeling Conformation search used in pharmacophore mapping Virtual screening
  • 3.  IUPAC defines a pharmacophore to be "an ensemble of steric and electronic features that is necessary to ensure the optimal supramolecular interactions with a specific biological target and to trigger (or block) its biological response".  With pharmacophoric models one can define special properties (pharmacophoric points) based on the structure of the receptor or based on the structure of a known agent.  MolSign is a complete module for pharmacophore identification and modeling. Identification of the pharmacophoric features such as H-bond donor, H-bond acceptor, positive charge, negative charge and hydrophobe facilitate the complete pharmacophoric mapping of the molecule.
  • 4. EXAMPLE-  An example of a pharmacophore model of the benzodiazepine binding site on the GABAAreceptor.  White sticks represent the carbon atoms of the benzodiazepine diazepam, while green represents carbon atoms of the nonbenzodiazepine CGS-9896..  Red and blue sticks are oxygen and nitrogen atoms that are present in both structures.
  • 5. The goal of Pharmacophore mapping is to establish the bioactive conformations of the Ligand and how to superimpose the mapping, one needs structure-activity relationships of structurally diverse and conformation informative molecules.
  • 6. Software use for Pharmacophore mapping:  Disco  Hip-hop  Aladdin  Apex Gasp  Accelary  Apollo Rapid 21
  • 7.  Application: Application of Pharmacophore mapping is used to understand the biological activity observed in series of compounds. So that we can design new and more potent compound.
  • 8. TYPICAL FEATURES  Hydrophobic  Aromatic  H-bond acceptor  H-bond donor  Cationic or  Anionic moieties
  • 9. A pharmacophore model consists of a few features organized in a specific 3D pattern. 50 The features can be labeled as a single feature or any logic combination consisting of “AND,” “OR,” and “NOT” to combine different interaction patterns within one label. Each of these conformations is fitted to the pharmacophore query by aligning the pharmacophore features of the molecule and the query is composed. If a molecule can be fitted inside the spheres representing the query features it is considered a hit molecule.
  • 10. Depending on how much is known about the particular protein target, different options are available to construct such a query. Four different situations for the pharmacophore search.
  • 11.  Limitations of pharmacophore methods The major limitation in virtual screening by pharmacophore is the absence of good scoring metrics. A second limitation is the dependency of a pharmacophore-based virtual screen on a pre- computed conformation database. These databases only contain a limited number of low-energy conformations per molecule.
  • 12. Conformation generally means structural arrangement. Conformations are different three dimensional structure of molecules that arises from. -rotations about single bonds (torsional angles). -different rings conformations. The biological activity of molecules is strongly dependent on their conformations. Done by exploring the energy surface of a molecule and determining the conformation with minimal energy, Conformational analysis is needed to identify the ideal conformation of the molecule.
  • 13. Different methods the conformations search can be quite large and can be approaches using following methods 1.Systemic search method 2.Distance geometry method 3.Clique detection alogorithm
  • 14. Virtual screening (VS) is a computational technique used in drug discovery to search libraries of small molecules in order to identify those structures which are most likely to bind to a drug target, typically a protein receptor or enzyme. Pharmacophore-based virtual screening is nowadays a mature technology, very well accepted in the medicinal chemistry laboratory. like any empirical approach, it has specific limitations and efforts to improve the methodology are still ongoing.
  • 15.  Methods There are two broad categories of screening techniques: ligand-based and structure-based.
  • 16.  Ligand-based- Given a set of structurally diverse ligands that binds to a receptor, a model of the receptor can be built by exploiting the collective information contained in such set of ligands. These are known as pharmacophore models.  Structure-based- Structure-based virtual screening involves docking of candidate ligands into a protein target followed by applying a scoring function to estimate the likelihood that the ligand will bind to the protein with high affinity.
  • 17. References- Rester U (July 2008). "From virtuality to reality - Virtual screening in lead discovery and lead optimization: a medicinal chemistry perspective". Current Opinion in Drug Discovery & Development. 11 (4): 559–68. PMID 18600572.  Rollinger JM, Stuppner H, Langer T (2008). Virtual screening for the discovery of bioactive natural products. Progress in Drug Research. Fortschritte der Arzneimittelforschung. Progres des Recherches Pharmaceutiques. Progress in Drug Research. 65. pp. 211, 213– 49. Walters WP, Stahl MT, Murcko MA (1998). "Virtual screening – an overview". Drug Discov. Today. 3 (4): 160–178.