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Docking
Virtual High Throughput In silico screening
Abhijeet Kadam
TSEC
BioTechnology
Drug Discovery
● Tedious process
● Many stages
● Lead identification – most imp
● Virtal screening or in silica database screening
used to discover novel lead compound
Virtual Screening (VS)
● Many advantages
– Used for lead discovery
– Cost effective
– Good results
– Less time consuming
● In silico virtual HTS = HTS screening
● Accesses new chemical compounds from large
Database (virtual library)
Virtual Screening
● Helps select molecules for lab testing
● Exploits structural properties of ligand molecule
(proteins)
● Virtual screening involves
– Creation of large in silico virtual library
– Which is Screened
– Docking program is applied
– Most active momber is selected
– Lab testing
HTS
● Thousands of sample screened against target
● Improves lead identification
● Fastens the process
VS techniques
● Requires knowlwdge of binding criteria
– Geometry
– Ligand binding
– Molecular similarity
– Biosteric functional group replacement
● 2 fundamental approaches
– 1) docking / molecular docking (3D str available)
– 2) similarity based VS (when 3D str not available)
Molecular Docking
● Requires knowlwdge of 3D structure of the target
protein binding site
● Basic requirements
– 1) A target protein structure with/without ligand
– 2) A database of virtual compounds
– 3) A computational framework to work out desired
docking and scoring procedures
● Ligand – flexible
● Protein – rigid
Molecular Docking
● Docking performed by placing rigid molecules or
fragments into the targets active site by using
– Clique search
– Geometry configrations
– Pose clustering
● Docking as VS technique
● Many advantages (as discussed)
Molecular Docking
● Ligands are designed according to the structure
and modelled as per demand of target binding
pocket
● Docking helps investigate the active site as well
as to detect uncovered binding pockets
● Examples
– GROWMOL – for ligand construction & docking
– Ilib diverse – generates focussed virtual library range
After creating virtual library
● Target is prepared
● Compound is docked into target site
● Evaluation for goodness of fit (2steps)
– Docking which include search for conformation and
configuration of ligand
– Scoring which include energies between target and
ligand
Scoring
● Of docked poses
● PL interactions
● Difficult step
● 3 methods
– Imperical scoring function – from training sets of PL
– Force feild scoring function – potential energy &
entropy
– Knowledge based Scoring function – atom pair
potentials from structure database
Classes of Virtual screening
methods
● Ligand based VS
● Fragment based VS
● Receptor based VS

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Virtual High Throughput In silico screening for Drug Discovery

  • 1. Docking Virtual High Throughput In silico screening Abhijeet Kadam TSEC BioTechnology
  • 2. Drug Discovery ● Tedious process ● Many stages ● Lead identification – most imp ● Virtal screening or in silica database screening used to discover novel lead compound
  • 3. Virtual Screening (VS) ● Many advantages – Used for lead discovery – Cost effective – Good results – Less time consuming ● In silico virtual HTS = HTS screening ● Accesses new chemical compounds from large Database (virtual library)
  • 4. Virtual Screening ● Helps select molecules for lab testing ● Exploits structural properties of ligand molecule (proteins) ● Virtual screening involves – Creation of large in silico virtual library – Which is Screened – Docking program is applied – Most active momber is selected – Lab testing
  • 5. HTS ● Thousands of sample screened against target ● Improves lead identification ● Fastens the process
  • 6. VS techniques ● Requires knowlwdge of binding criteria – Geometry – Ligand binding – Molecular similarity – Biosteric functional group replacement ● 2 fundamental approaches – 1) docking / molecular docking (3D str available) – 2) similarity based VS (when 3D str not available)
  • 7. Molecular Docking ● Requires knowlwdge of 3D structure of the target protein binding site ● Basic requirements – 1) A target protein structure with/without ligand – 2) A database of virtual compounds – 3) A computational framework to work out desired docking and scoring procedures ● Ligand – flexible ● Protein – rigid
  • 8. Molecular Docking ● Docking performed by placing rigid molecules or fragments into the targets active site by using – Clique search – Geometry configrations – Pose clustering ● Docking as VS technique ● Many advantages (as discussed)
  • 9. Molecular Docking ● Ligands are designed according to the structure and modelled as per demand of target binding pocket ● Docking helps investigate the active site as well as to detect uncovered binding pockets ● Examples – GROWMOL – for ligand construction & docking – Ilib diverse – generates focussed virtual library range
  • 10. After creating virtual library ● Target is prepared ● Compound is docked into target site ● Evaluation for goodness of fit (2steps) – Docking which include search for conformation and configuration of ligand – Scoring which include energies between target and ligand
  • 11. Scoring ● Of docked poses ● PL interactions ● Difficult step ● 3 methods – Imperical scoring function – from training sets of PL – Force feild scoring function – potential energy & entropy – Knowledge based Scoring function – atom pair potentials from structure database
  • 12. Classes of Virtual screening methods ● Ligand based VS ● Fragment based VS ● Receptor based VS